Security and Privacy in Communication Networks: 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I.
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing AG
2020
|
| Series: | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Ser.
v.335 |
| Subjects: | |
| Physical Description: | 1 Online-Ressource (543 Seiten) |
| ISBN: | 9783030630867 |
Staff View
MARC
| LEADER | 00000nmm a2200000 cb4500 | ||
|---|---|---|---|
| 001 | BV048323353 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 220712s2020 |||| o||u| ||||||eng d | ||
| 020 | |a 9783030630867 |q (electronic bk.) |9 9783030630867 | ||
| 035 | |a (ZDB-30-PQE)EBC6424396 | ||
| 035 | |a (ZDB-30-PAD)EBC6424396 | ||
| 035 | |a (ZDB-89-EBL)EBL6424396 | ||
| 035 | |a (OCoLC)1228648812 | ||
| 035 | |a (DE-599)BVBBV048323353 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 100 | 1 | |a Park, Noseong |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Security and Privacy in Communication Networks |b 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| 264 | 1 | |a Cham |b Springer International Publishing AG |c 2020 | |
| 264 | 4 | |c ©2020 | |
| 300 | |a 1 Online-Ressource (543 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Ser. |v v.335 | |
| 505 | 8 | |a Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Email Address Mutation for Proactive Deterrence Against Lateral Spear-Phishing Attacks -- 1 Introduction -- 2 Related Work -- 3 Threat Model -- 3.1 Attack Taxonomy -- 3.2 Attack Model -- 4 Email Mutation System -- 4.1 Overview -- 4.2 Architecture -- 4.3 Algorithm -- 4.4 Protocol -- 4.5 Identifying Lateral Spear-Phishing Attack -- 5 Email Mutation - Challenges and Solutions -- 6 Scalable Implementation and Security Measurement -- 6.1 Email Mutation Agent -- 6.2 Email Mutation Gateway -- 7 Email Mutation Verification and Evaluation -- 7.1 System Verification -- 7.2 Performance Evaluation -- 8 Limitations and Future Work -- 9 Conclusion -- References -- ThreatZoom: Hierarchical Neural Network for CVEs to CWEs Classification -- 1 Introduction -- 1.1 Motivation Example -- 1.2 Related Works -- 1.3 Challenges -- 1.4 Contribution -- 2 Methodology -- 2.1 Preprocessing -- 2.2 Feature Extraction -- 2.3 Hierarchical Decision-Making -- 3 Results -- 3.1 Dataset Specification -- 3.2 Experiments -- 4 Discussion -- 4.1 ThreatZoom and Unlabeled CVEs -- 4.2 More Fine-Grain Classification by ThreatZoom -- 5 Conclusion and Future Work -- References -- Detecting Dictionary Based AGDs Based on Community Detection -- 1 Introduction -- 2 Methodology -- 2.1 Word Graph -- 2.2 Community Detection on Word Graph -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Experiments -- References -- On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 BLE-based Contact Tracing -- 2.2 Proximity Measurement in BLE-based Contact Tracing -- 3 Analysis of BLE Software Configurations -- 4 Analysis of Proximity Measurement Approaches -- 4.1 Data Collected for Proximity Measurement -- 4.2 Data Used in Distance Calculation -- 5 Discussion | |
| 505 | 8 | |a 6 Related Work -- 7 Conclusion -- References -- A Formal Verification of Configuration-Based Mutation Techniques for Moving Target Defense -- 1 Introduction -- 2 Preliminaries -- 2.1 System Modeling Language -- 2.2 Duration Calculus -- 3 RHM Protocol -- 4 Verification Methodology -- 5 RHM Components Modeling -- 5.1 Moving Target Gateway -- 5.2 Moving Target Controller -- 6 MTD Verification -- 6.1 Evaluation Methodology -- 6.2 Properties Verification -- 6.3 Evaluation -- 7 Related Work -- 8 Conclusions -- References -- Coronavirus Contact Tracing App Privacy: What Data Is Shared by the Singapore OpenTrace App? -- 1 Introduction -- 2 Threat Model: What Do We Mean by Privacy? -- 3 Measurement Setup -- 3.1 Viewing Content of Encrypted Web Connections -- 3.2 Hardware and Software Used -- 3.3 Test Design -- 3.4 Finding Identifiers in Network Connections -- 4 Google Firebase -- 5 Cryptography -- 6 Measurements of Data Transmitted by OpenTrace App -- 6.1 Data Sent on Initial Startup -- 6.2 Data Sent upon Phone Number Entry -- 6.3 Data Sent When Permissions Are Granted -- 6.4 Data Sent When Sitting Idle at Main Screen -- 6.5 Data Sent by TraceTogether (v1.0.33) -- 7 Summary and Conclusions -- References -- The Maestro Attack: Orchestrating Malicious Flows with BGP -- 1 Introduction -- 2 Background -- 2.1 Border Gateway Protocol -- 2.2 BGP Poisoning -- 2.3 Link Flooding Attacks -- 3 Can Botnets Target Any Link? -- 3.1 Simulation Methodology -- 3.2 Vulnerability Experiments -- 4 The Maestro Attack -- 4.1 Poison Selection Algorithm -- 4.2 Evaluation -- 5 Internet Experiments -- 6 Attack Scope and Vulnerability -- 7 Towards Defenses -- 8 Related Work -- 9 Conclusion -- References -- pyDNetTopic: A Framework for Uncovering What Darknet Market Users Talking About -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 LDA -- 3.2 BTM -- 3.3 GSDMM. | |
| 505 | 8 | |a 4 Filtered Bi-Term Topic Model -- 4.1 Motivation -- 4.2 Methodology -- 5 Framework Architecture -- 5.1 Data Extraction and Preprocessing -- 5.2 Topic Models -- 5.3 Relevance Metric -- 6 Experiment -- 6.1 Evaluation Metrics -- 6.2 Performance Comparison -- 6.3 Result Analysis -- 7 Conclusion -- A List of Additional Stop Words -- B Full Topic Results of Agora Forums in 2014 -- References -- MisMesh: Security Issues and Challenges in Service Meshes -- 1 Introduction -- 2 Background -- 3 Threat Model and Experimental Design -- 4 Evaluation of Modern Service Meshes -- 5 Related Work -- 6 Conclusions -- References -- The Bitcoin Hunter: Detecting Bitcoin Traffic over Encrypted Channels -- 1 Introduction -- 2 Background on Bitcoin Traffic and Its Network Traffic -- 3 Characterizing Bitcoin Traffic -- 3.1 Proportion and Distribution of Messages -- 3.2 Shape of Traffic -- 4 Designing Bitcoin Classifiers -- 4.1 Size-Based Classifier -- 4.2 Shape-Based Classifier -- 4.3 Neural Network-Based Classifier (NN-Based) -- 4.4 Combined Classifier -- 5 Experimental Setup -- 5.1 Datasets -- 5.2 Metrics -- 5.3 Modeling Normal Users -- 6 Results -- 6.1 User Profiles and False Data -- 6.2 Size-Based Classifiers -- 6.3 Shape-Based Classifier -- 6.4 Neural Network-Based Classifier -- 6.5 Combined Classifier -- 6.6 Summary and Comparison of the Results -- 7 Countermeasures -- 7.1 Bitcoin over Tor -- 7.2 Evaluating Bitcoin Over Tor -- 8 Related Work -- 8.1 Protocol Classification -- 8.2 Attacks on Bitcoin Cryptocurrency -- 9 Conclusions -- References -- MAAN: A Multiple Attribute Association Network for Mobile Encrypted Traffic Classification -- 1 Introduction -- 2 Background -- 2.1 SSL/TLS Basics -- 2.2 Related Work -- 3 Architecture of MAAN -- 3.1 Segment Preprocessor -- 3.2 Message Feature Extractor -- 3.3 Flow Feature Extractor -- 3.4 Dense Layer | |
| 505 | 8 | |a 3.5 Classification Layer -- 4 Experiment -- 4.1 Dataset -- 4.2 Experiment Setting -- 4.3 Comparisons with Existing Approaches -- 4.4 Analysis of MAAN -- 4.5 The Efficiency of MAAN -- 5 Discussion -- 6 Conclusion -- A Parameters Selection -- References -- Assessing Adaptive Attacks Against Trained JavaScript Classifiers -- 1 Introduction -- 2 Problem Overview -- 2.1 Existing Classification Approaches -- 2.2 Objectives and Challenges -- 3 Threat Models -- 4 Attacks -- 4.1 Subtree Editing Mimicry Attack -- 4.2 Script Stitching Mimicry Attack -- 4.3 Gadget Composition Mimicry Attack -- 4.4 Correctness -- 5 Implementation -- 6 Experimental Evaluation -- 6.1 Dataset and Infrastructure -- 6.2 Baseline Classifier Performance -- 6.3 Evaluation of Attacks -- 6.4 Per-domain Analysis -- 6.5 Knowledge of Dataset vs Model -- 6.6 Impact of Adversarial Training -- 6.7 Execution Times -- 6.8 Analysis of Results -- 7 Related Work -- 8 Conclusion -- References -- An Encryption System for Securing Physical Signals -- 1 Introduction -- 2 Related Work -- 3 Cryptographic Model -- 4 The Vernam Physical Signal Cipher -- 4.1 Noise Mitigation -- 4.2 Key Sharing -- 5 Cryptanalysis -- 6 Signal Synchronization -- 7 Complexity and Performance -- 8 Evaluation -- 8.1 Wireless - Simulation -- 8.2 Wired - Proof of Concept -- 9 Conclusion -- 10 Appendix - Additional Figures -- References -- A Cooperative Jamming Game in Wireless Networks Under Uncertainty -- 1 Introduction -- 1.1 Related Works -- 1.2 Summary of Contributions -- 2 System Model and Game Formulation -- 2.1 System Model -- 2.2 Formulation of the Game -- 3 Best Response Functions -- 4 Nonzero-Sum Game Under Uncertainty -- 5 Numerical Illustrations -- 6 Conclusions and Future Research -- References -- SmartSwitch: Efficient Traffic Obfuscation Against Stream Fingerprinting -- 1 Introduction -- 2 Background | |
| 505 | 8 | |a 3 Stream Fingerprinting Attack -- 4 SmartSwitch: Our Proposed Defense Mechanism -- 5 Which Packets Are More Significant? -- 5.1 Permutation Feature Importance -- 5.2 Mutual-Information-Based Algorithms -- 6 Evaluation of Feature Selection -- 7 Evaluation of SmartSwitch -- 7.1 Defense Performance of NDSS19 on YouTube Dataset -- 7.2 Defense Performance of SmartSwitch on YouTube Dataset -- 8 Related Work -- 9 Conclusion -- References -- Misreporting Attacks in Software-Defined Networking -- 1 Introduction -- 2 Background -- 3 Attacking the Load Balancer -- 3.1 Threat Model and Overview -- 3.2 Attack Model -- 3.3 Max-Flooding Attack -- 3.4 Stealthy Attack -- 3.5 Assessing the Impact -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Effects on Network Performance -- 4.4 Discussion -- 5 Conclusion -- References -- A Study of the Privacy of COVID-19 Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 Digital Contact Tracing -- 2.2 BLE in Proximity Tracing -- 2.3 Centralized vs. Decentralized Mobile Contact Tracing -- 3 Methodology -- 3.1 Scope and Overview -- 3.2 Contact Tracing Relevant API Recognition -- 3.3 Privacy Information Identification -- 3.4 Cross-Platform Comparison -- 4 Evaluation -- 4.1 COVID-19 Mobile App Collection -- 4.2 Evaluation Result -- 4.3 Evaluation Result of Cross-Platform Comparison -- 5 Discussion -- 5.1 Limitations -- 5.2 Mitigation on the Privacy Issues Identified -- 6 Related Work -- 7 Conclusion -- References -- Best-Effort Adversarial Approximation of Black-Box Malware Classifiers -- 1 Introduction -- 2 Background and Threat Model -- 2.1 Model Approximation Attacks -- 2.2 Threat Model and Problem Statement -- 3 Approach -- 3.1 Approximation Set Labeling -- 3.2 Representation Mapping -- 3.3 Progressive Approximation -- 3.4 Similarity Comparison -- 4 Evaluation -- 4.1 Datasets | |
| 505 | 8 | |a 4.2 Experimental Setup | |
| 650 | 4 | |a Computer networks-Security measures-Congresses | |
| 650 | 4 | |a Telecommunication systems-Security measures-Congresses | |
| 650 | 4 | |a Computer security | |
| 653 | 6 | |a Electronic books | |
| 700 | 1 | |a Sun, Kun |e Sonstige |4 oth | |
| 700 | 1 | |a Foresti, Sara |e Sonstige |4 oth | |
| 700 | 1 | |a Butler, Kevin |e Sonstige |4 oth | |
| 700 | 1 | |a Saxena, Nitesh |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Park, Noseong |t Security and Privacy in Communication Networks |d Cham : Springer International Publishing AG,c2020 |z 9783030630850 |
| 912 | |a ZDB-30-PQE | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-033702649 | ||
Record in the Search Index
| _version_ | 1804184182243459072 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Park, Noseong |
| author_facet | Park, Noseong |
| author_role | aut |
| author_sort | Park, Noseong |
| author_variant | n p np |
| building | Verbundindex |
| bvnumber | BV048323353 |
| collection | ZDB-30-PQE |
| contents | Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Email Address Mutation for Proactive Deterrence Against Lateral Spear-Phishing Attacks -- 1 Introduction -- 2 Related Work -- 3 Threat Model -- 3.1 Attack Taxonomy -- 3.2 Attack Model -- 4 Email Mutation System -- 4.1 Overview -- 4.2 Architecture -- 4.3 Algorithm -- 4.4 Protocol -- 4.5 Identifying Lateral Spear-Phishing Attack -- 5 Email Mutation - Challenges and Solutions -- 6 Scalable Implementation and Security Measurement -- 6.1 Email Mutation Agent -- 6.2 Email Mutation Gateway -- 7 Email Mutation Verification and Evaluation -- 7.1 System Verification -- 7.2 Performance Evaluation -- 8 Limitations and Future Work -- 9 Conclusion -- References -- ThreatZoom: Hierarchical Neural Network for CVEs to CWEs Classification -- 1 Introduction -- 1.1 Motivation Example -- 1.2 Related Works -- 1.3 Challenges -- 1.4 Contribution -- 2 Methodology -- 2.1 Preprocessing -- 2.2 Feature Extraction -- 2.3 Hierarchical Decision-Making -- 3 Results -- 3.1 Dataset Specification -- 3.2 Experiments -- 4 Discussion -- 4.1 ThreatZoom and Unlabeled CVEs -- 4.2 More Fine-Grain Classification by ThreatZoom -- 5 Conclusion and Future Work -- References -- Detecting Dictionary Based AGDs Based on Community Detection -- 1 Introduction -- 2 Methodology -- 2.1 Word Graph -- 2.2 Community Detection on Word Graph -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Experiments -- References -- On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 BLE-based Contact Tracing -- 2.2 Proximity Measurement in BLE-based Contact Tracing -- 3 Analysis of BLE Software Configurations -- 4 Analysis of Proximity Measurement Approaches -- 4.1 Data Collected for Proximity Measurement -- 4.2 Data Used in Distance Calculation -- 5 Discussion 6 Related Work -- 7 Conclusion -- References -- A Formal Verification of Configuration-Based Mutation Techniques for Moving Target Defense -- 1 Introduction -- 2 Preliminaries -- 2.1 System Modeling Language -- 2.2 Duration Calculus -- 3 RHM Protocol -- 4 Verification Methodology -- 5 RHM Components Modeling -- 5.1 Moving Target Gateway -- 5.2 Moving Target Controller -- 6 MTD Verification -- 6.1 Evaluation Methodology -- 6.2 Properties Verification -- 6.3 Evaluation -- 7 Related Work -- 8 Conclusions -- References -- Coronavirus Contact Tracing App Privacy: What Data Is Shared by the Singapore OpenTrace App? -- 1 Introduction -- 2 Threat Model: What Do We Mean by Privacy? -- 3 Measurement Setup -- 3.1 Viewing Content of Encrypted Web Connections -- 3.2 Hardware and Software Used -- 3.3 Test Design -- 3.4 Finding Identifiers in Network Connections -- 4 Google Firebase -- 5 Cryptography -- 6 Measurements of Data Transmitted by OpenTrace App -- 6.1 Data Sent on Initial Startup -- 6.2 Data Sent upon Phone Number Entry -- 6.3 Data Sent When Permissions Are Granted -- 6.4 Data Sent When Sitting Idle at Main Screen -- 6.5 Data Sent by TraceTogether (v1.0.33) -- 7 Summary and Conclusions -- References -- The Maestro Attack: Orchestrating Malicious Flows with BGP -- 1 Introduction -- 2 Background -- 2.1 Border Gateway Protocol -- 2.2 BGP Poisoning -- 2.3 Link Flooding Attacks -- 3 Can Botnets Target Any Link? -- 3.1 Simulation Methodology -- 3.2 Vulnerability Experiments -- 4 The Maestro Attack -- 4.1 Poison Selection Algorithm -- 4.2 Evaluation -- 5 Internet Experiments -- 6 Attack Scope and Vulnerability -- 7 Towards Defenses -- 8 Related Work -- 9 Conclusion -- References -- pyDNetTopic: A Framework for Uncovering What Darknet Market Users Talking About -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 LDA -- 3.2 BTM -- 3.3 GSDMM. 4 Filtered Bi-Term Topic Model -- 4.1 Motivation -- 4.2 Methodology -- 5 Framework Architecture -- 5.1 Data Extraction and Preprocessing -- 5.2 Topic Models -- 5.3 Relevance Metric -- 6 Experiment -- 6.1 Evaluation Metrics -- 6.2 Performance Comparison -- 6.3 Result Analysis -- 7 Conclusion -- A List of Additional Stop Words -- B Full Topic Results of Agora Forums in 2014 -- References -- MisMesh: Security Issues and Challenges in Service Meshes -- 1 Introduction -- 2 Background -- 3 Threat Model and Experimental Design -- 4 Evaluation of Modern Service Meshes -- 5 Related Work -- 6 Conclusions -- References -- The Bitcoin Hunter: Detecting Bitcoin Traffic over Encrypted Channels -- 1 Introduction -- 2 Background on Bitcoin Traffic and Its Network Traffic -- 3 Characterizing Bitcoin Traffic -- 3.1 Proportion and Distribution of Messages -- 3.2 Shape of Traffic -- 4 Designing Bitcoin Classifiers -- 4.1 Size-Based Classifier -- 4.2 Shape-Based Classifier -- 4.3 Neural Network-Based Classifier (NN-Based) -- 4.4 Combined Classifier -- 5 Experimental Setup -- 5.1 Datasets -- 5.2 Metrics -- 5.3 Modeling Normal Users -- 6 Results -- 6.1 User Profiles and False Data -- 6.2 Size-Based Classifiers -- 6.3 Shape-Based Classifier -- 6.4 Neural Network-Based Classifier -- 6.5 Combined Classifier -- 6.6 Summary and Comparison of the Results -- 7 Countermeasures -- 7.1 Bitcoin over Tor -- 7.2 Evaluating Bitcoin Over Tor -- 8 Related Work -- 8.1 Protocol Classification -- 8.2 Attacks on Bitcoin Cryptocurrency -- 9 Conclusions -- References -- MAAN: A Multiple Attribute Association Network for Mobile Encrypted Traffic Classification -- 1 Introduction -- 2 Background -- 2.1 SSL/TLS Basics -- 2.2 Related Work -- 3 Architecture of MAAN -- 3.1 Segment Preprocessor -- 3.2 Message Feature Extractor -- 3.3 Flow Feature Extractor -- 3.4 Dense Layer 3.5 Classification Layer -- 4 Experiment -- 4.1 Dataset -- 4.2 Experiment Setting -- 4.3 Comparisons with Existing Approaches -- 4.4 Analysis of MAAN -- 4.5 The Efficiency of MAAN -- 5 Discussion -- 6 Conclusion -- A Parameters Selection -- References -- Assessing Adaptive Attacks Against Trained JavaScript Classifiers -- 1 Introduction -- 2 Problem Overview -- 2.1 Existing Classification Approaches -- 2.2 Objectives and Challenges -- 3 Threat Models -- 4 Attacks -- 4.1 Subtree Editing Mimicry Attack -- 4.2 Script Stitching Mimicry Attack -- 4.3 Gadget Composition Mimicry Attack -- 4.4 Correctness -- 5 Implementation -- 6 Experimental Evaluation -- 6.1 Dataset and Infrastructure -- 6.2 Baseline Classifier Performance -- 6.3 Evaluation of Attacks -- 6.4 Per-domain Analysis -- 6.5 Knowledge of Dataset vs Model -- 6.6 Impact of Adversarial Training -- 6.7 Execution Times -- 6.8 Analysis of Results -- 7 Related Work -- 8 Conclusion -- References -- An Encryption System for Securing Physical Signals -- 1 Introduction -- 2 Related Work -- 3 Cryptographic Model -- 4 The Vernam Physical Signal Cipher -- 4.1 Noise Mitigation -- 4.2 Key Sharing -- 5 Cryptanalysis -- 6 Signal Synchronization -- 7 Complexity and Performance -- 8 Evaluation -- 8.1 Wireless - Simulation -- 8.2 Wired - Proof of Concept -- 9 Conclusion -- 10 Appendix - Additional Figures -- References -- A Cooperative Jamming Game in Wireless Networks Under Uncertainty -- 1 Introduction -- 1.1 Related Works -- 1.2 Summary of Contributions -- 2 System Model and Game Formulation -- 2.1 System Model -- 2.2 Formulation of the Game -- 3 Best Response Functions -- 4 Nonzero-Sum Game Under Uncertainty -- 5 Numerical Illustrations -- 6 Conclusions and Future Research -- References -- SmartSwitch: Efficient Traffic Obfuscation Against Stream Fingerprinting -- 1 Introduction -- 2 Background 3 Stream Fingerprinting Attack -- 4 SmartSwitch: Our Proposed Defense Mechanism -- 5 Which Packets Are More Significant? -- 5.1 Permutation Feature Importance -- 5.2 Mutual-Information-Based Algorithms -- 6 Evaluation of Feature Selection -- 7 Evaluation of SmartSwitch -- 7.1 Defense Performance of NDSS19 on YouTube Dataset -- 7.2 Defense Performance of SmartSwitch on YouTube Dataset -- 8 Related Work -- 9 Conclusion -- References -- Misreporting Attacks in Software-Defined Networking -- 1 Introduction -- 2 Background -- 3 Attacking the Load Balancer -- 3.1 Threat Model and Overview -- 3.2 Attack Model -- 3.3 Max-Flooding Attack -- 3.4 Stealthy Attack -- 3.5 Assessing the Impact -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Effects on Network Performance -- 4.4 Discussion -- 5 Conclusion -- References -- A Study of the Privacy of COVID-19 Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 Digital Contact Tracing -- 2.2 BLE in Proximity Tracing -- 2.3 Centralized vs. Decentralized Mobile Contact Tracing -- 3 Methodology -- 3.1 Scope and Overview -- 3.2 Contact Tracing Relevant API Recognition -- 3.3 Privacy Information Identification -- 3.4 Cross-Platform Comparison -- 4 Evaluation -- 4.1 COVID-19 Mobile App Collection -- 4.2 Evaluation Result -- 4.3 Evaluation Result of Cross-Platform Comparison -- 5 Discussion -- 5.1 Limitations -- 5.2 Mitigation on the Privacy Issues Identified -- 6 Related Work -- 7 Conclusion -- References -- Best-Effort Adversarial Approximation of Black-Box Malware Classifiers -- 1 Introduction -- 2 Background and Threat Model -- 2.1 Model Approximation Attacks -- 2.2 Threat Model and Problem Statement -- 3 Approach -- 3.1 Approximation Set Labeling -- 3.2 Representation Mapping -- 3.3 Progressive Approximation -- 3.4 Similarity Comparison -- 4 Evaluation -- 4.1 Datasets 4.2 Experimental Setup |
| ctrlnum | (ZDB-30-PQE)EBC6424396 (ZDB-30-PAD)EBC6424396 (ZDB-89-EBL)EBL6424396 (OCoLC)1228648812 (DE-599)BVBBV048323353 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>11149nmm a2200493 cb4500</leader><controlfield tag="001">BV048323353</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">220712s2020 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783030630867</subfield><subfield code="q">(electronic bk.)</subfield><subfield code="9">9783030630867</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PQE)EBC6424396</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PAD)EBC6424396</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-89-EBL)EBL6424396</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1228648812</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV048323353</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Park, Noseong</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Security and Privacy in Communication Networks</subfield><subfield code="b">16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham</subfield><subfield code="b">Springer International Publishing AG</subfield><subfield code="c">2020</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2020</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (543 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Ser.</subfield><subfield code="v">v.335</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Email Address Mutation for Proactive Deterrence Against Lateral Spear-Phishing Attacks -- 1 Introduction -- 2 Related Work -- 3 Threat Model -- 3.1 Attack Taxonomy -- 3.2 Attack Model -- 4 Email Mutation System -- 4.1 Overview -- 4.2 Architecture -- 4.3 Algorithm -- 4.4 Protocol -- 4.5 Identifying Lateral Spear-Phishing Attack -- 5 Email Mutation - Challenges and Solutions -- 6 Scalable Implementation and Security Measurement -- 6.1 Email Mutation Agent -- 6.2 Email Mutation Gateway -- 7 Email Mutation Verification and Evaluation -- 7.1 System Verification -- 7.2 Performance Evaluation -- 8 Limitations and Future Work -- 9 Conclusion -- References -- ThreatZoom: Hierarchical Neural Network for CVEs to CWEs Classification -- 1 Introduction -- 1.1 Motivation Example -- 1.2 Related Works -- 1.3 Challenges -- 1.4 Contribution -- 2 Methodology -- 2.1 Preprocessing -- 2.2 Feature Extraction -- 2.3 Hierarchical Decision-Making -- 3 Results -- 3.1 Dataset Specification -- 3.2 Experiments -- 4 Discussion -- 4.1 ThreatZoom and Unlabeled CVEs -- 4.2 More Fine-Grain Classification by ThreatZoom -- 5 Conclusion and Future Work -- References -- Detecting Dictionary Based AGDs Based on Community Detection -- 1 Introduction -- 2 Methodology -- 2.1 Word Graph -- 2.2 Community Detection on Word Graph -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Experiments -- References -- On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 BLE-based Contact Tracing -- 2.2 Proximity Measurement in BLE-based Contact Tracing -- 3 Analysis of BLE Software Configurations -- 4 Analysis of Proximity Measurement Approaches -- 4.1 Data Collected for Proximity Measurement -- 4.2 Data Used in Distance Calculation -- 5 Discussion</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">6 Related Work -- 7 Conclusion -- References -- A Formal Verification of Configuration-Based Mutation Techniques for Moving Target Defense -- 1 Introduction -- 2 Preliminaries -- 2.1 System Modeling Language -- 2.2 Duration Calculus -- 3 RHM Protocol -- 4 Verification Methodology -- 5 RHM Components Modeling -- 5.1 Moving Target Gateway -- 5.2 Moving Target Controller -- 6 MTD Verification -- 6.1 Evaluation Methodology -- 6.2 Properties Verification -- 6.3 Evaluation -- 7 Related Work -- 8 Conclusions -- References -- Coronavirus Contact Tracing App Privacy: What Data Is Shared by the Singapore OpenTrace App? -- 1 Introduction -- 2 Threat Model: What Do We Mean by Privacy? -- 3 Measurement Setup -- 3.1 Viewing Content of Encrypted Web Connections -- 3.2 Hardware and Software Used -- 3.3 Test Design -- 3.4 Finding Identifiers in Network Connections -- 4 Google Firebase -- 5 Cryptography -- 6 Measurements of Data Transmitted by OpenTrace App -- 6.1 Data Sent on Initial Startup -- 6.2 Data Sent upon Phone Number Entry -- 6.3 Data Sent When Permissions Are Granted -- 6.4 Data Sent When Sitting Idle at Main Screen -- 6.5 Data Sent by TraceTogether (v1.0.33) -- 7 Summary and Conclusions -- References -- The Maestro Attack: Orchestrating Malicious Flows with BGP -- 1 Introduction -- 2 Background -- 2.1 Border Gateway Protocol -- 2.2 BGP Poisoning -- 2.3 Link Flooding Attacks -- 3 Can Botnets Target Any Link? -- 3.1 Simulation Methodology -- 3.2 Vulnerability Experiments -- 4 The Maestro Attack -- 4.1 Poison Selection Algorithm -- 4.2 Evaluation -- 5 Internet Experiments -- 6 Attack Scope and Vulnerability -- 7 Towards Defenses -- 8 Related Work -- 9 Conclusion -- References -- pyDNetTopic: A Framework for Uncovering What Darknet Market Users Talking About -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 LDA -- 3.2 BTM -- 3.3 GSDMM.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4 Filtered Bi-Term Topic Model -- 4.1 Motivation -- 4.2 Methodology -- 5 Framework Architecture -- 5.1 Data Extraction and Preprocessing -- 5.2 Topic Models -- 5.3 Relevance Metric -- 6 Experiment -- 6.1 Evaluation Metrics -- 6.2 Performance Comparison -- 6.3 Result Analysis -- 7 Conclusion -- A List of Additional Stop Words -- B Full Topic Results of Agora Forums in 2014 -- References -- MisMesh: Security Issues and Challenges in Service Meshes -- 1 Introduction -- 2 Background -- 3 Threat Model and Experimental Design -- 4 Evaluation of Modern Service Meshes -- 5 Related Work -- 6 Conclusions -- References -- The Bitcoin Hunter: Detecting Bitcoin Traffic over Encrypted Channels -- 1 Introduction -- 2 Background on Bitcoin Traffic and Its Network Traffic -- 3 Characterizing Bitcoin Traffic -- 3.1 Proportion and Distribution of Messages -- 3.2 Shape of Traffic -- 4 Designing Bitcoin Classifiers -- 4.1 Size-Based Classifier -- 4.2 Shape-Based Classifier -- 4.3 Neural Network-Based Classifier (NN-Based) -- 4.4 Combined Classifier -- 5 Experimental Setup -- 5.1 Datasets -- 5.2 Metrics -- 5.3 Modeling Normal Users -- 6 Results -- 6.1 User Profiles and False Data -- 6.2 Size-Based Classifiers -- 6.3 Shape-Based Classifier -- 6.4 Neural Network-Based Classifier -- 6.5 Combined Classifier -- 6.6 Summary and Comparison of the Results -- 7 Countermeasures -- 7.1 Bitcoin over Tor -- 7.2 Evaluating Bitcoin Over Tor -- 8 Related Work -- 8.1 Protocol Classification -- 8.2 Attacks on Bitcoin Cryptocurrency -- 9 Conclusions -- References -- MAAN: A Multiple Attribute Association Network for Mobile Encrypted Traffic Classification -- 1 Introduction -- 2 Background -- 2.1 SSL/TLS Basics -- 2.2 Related Work -- 3 Architecture of MAAN -- 3.1 Segment Preprocessor -- 3.2 Message Feature Extractor -- 3.3 Flow Feature Extractor -- 3.4 Dense Layer</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">3.5 Classification Layer -- 4 Experiment -- 4.1 Dataset -- 4.2 Experiment Setting -- 4.3 Comparisons with Existing Approaches -- 4.4 Analysis of MAAN -- 4.5 The Efficiency of MAAN -- 5 Discussion -- 6 Conclusion -- A Parameters Selection -- References -- Assessing Adaptive Attacks Against Trained JavaScript Classifiers -- 1 Introduction -- 2 Problem Overview -- 2.1 Existing Classification Approaches -- 2.2 Objectives and Challenges -- 3 Threat Models -- 4 Attacks -- 4.1 Subtree Editing Mimicry Attack -- 4.2 Script Stitching Mimicry Attack -- 4.3 Gadget Composition Mimicry Attack -- 4.4 Correctness -- 5 Implementation -- 6 Experimental Evaluation -- 6.1 Dataset and Infrastructure -- 6.2 Baseline Classifier Performance -- 6.3 Evaluation of Attacks -- 6.4 Per-domain Analysis -- 6.5 Knowledge of Dataset vs Model -- 6.6 Impact of Adversarial Training -- 6.7 Execution Times -- 6.8 Analysis of Results -- 7 Related Work -- 8 Conclusion -- References -- An Encryption System for Securing Physical Signals -- 1 Introduction -- 2 Related Work -- 3 Cryptographic Model -- 4 The Vernam Physical Signal Cipher -- 4.1 Noise Mitigation -- 4.2 Key Sharing -- 5 Cryptanalysis -- 6 Signal Synchronization -- 7 Complexity and Performance -- 8 Evaluation -- 8.1 Wireless - Simulation -- 8.2 Wired - Proof of Concept -- 9 Conclusion -- 10 Appendix - Additional Figures -- References -- A Cooperative Jamming Game in Wireless Networks Under Uncertainty -- 1 Introduction -- 1.1 Related Works -- 1.2 Summary of Contributions -- 2 System Model and Game Formulation -- 2.1 System Model -- 2.2 Formulation of the Game -- 3 Best Response Functions -- 4 Nonzero-Sum Game Under Uncertainty -- 5 Numerical Illustrations -- 6 Conclusions and Future Research -- References -- SmartSwitch: Efficient Traffic Obfuscation Against Stream Fingerprinting -- 1 Introduction -- 2 Background</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">3 Stream Fingerprinting Attack -- 4 SmartSwitch: Our Proposed Defense Mechanism -- 5 Which Packets Are More Significant? -- 5.1 Permutation Feature Importance -- 5.2 Mutual-Information-Based Algorithms -- 6 Evaluation of Feature Selection -- 7 Evaluation of SmartSwitch -- 7.1 Defense Performance of NDSS19 on YouTube Dataset -- 7.2 Defense Performance of SmartSwitch on YouTube Dataset -- 8 Related Work -- 9 Conclusion -- References -- Misreporting Attacks in Software-Defined Networking -- 1 Introduction -- 2 Background -- 3 Attacking the Load Balancer -- 3.1 Threat Model and Overview -- 3.2 Attack Model -- 3.3 Max-Flooding Attack -- 3.4 Stealthy Attack -- 3.5 Assessing the Impact -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Effects on Network Performance -- 4.4 Discussion -- 5 Conclusion -- References -- A Study of the Privacy of COVID-19 Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 Digital Contact Tracing -- 2.2 BLE in Proximity Tracing -- 2.3 Centralized vs. Decentralized Mobile Contact Tracing -- 3 Methodology -- 3.1 Scope and Overview -- 3.2 Contact Tracing Relevant API Recognition -- 3.3 Privacy Information Identification -- 3.4 Cross-Platform Comparison -- 4 Evaluation -- 4.1 COVID-19 Mobile App Collection -- 4.2 Evaluation Result -- 4.3 Evaluation Result of Cross-Platform Comparison -- 5 Discussion -- 5.1 Limitations -- 5.2 Mitigation on the Privacy Issues Identified -- 6 Related Work -- 7 Conclusion -- References -- Best-Effort Adversarial Approximation of Black-Box Malware Classifiers -- 1 Introduction -- 2 Background and Threat Model -- 2.1 Model Approximation Attacks -- 2.2 Threat Model and Problem Statement -- 3 Approach -- 3.1 Approximation Set Labeling -- 3.2 Representation Mapping -- 3.3 Progressive Approximation -- 3.4 Similarity Comparison -- 4 Evaluation -- 4.1 Datasets</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4.2 Experimental Setup</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer networks-Security measures-Congresses</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Telecommunication systems-Security measures-Congresses</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer security</subfield></datafield><datafield tag="653" ind1=" " ind2="6"><subfield code="a">Electronic books</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sun, Kun</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Foresti, Sara</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Butler, Kevin</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Saxena, Nitesh</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Park, Noseong</subfield><subfield code="t">Security and Privacy in Communication Networks</subfield><subfield code="d">Cham : Springer International Publishing AG,c2020</subfield><subfield code="z">9783030630850</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033702649</subfield></datafield></record></collection> |
| id | DE-604.BV048323353 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T20:12:42Z |
| indexdate | 2024-07-10T09:35:16Z |
| institution | BVB |
| isbn | 9783030630867 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033702649 |
| oclc_num | 1228648812 |
| open_access_boolean | |
| physical | 1 Online-Ressource (543 Seiten) |
| psigel | ZDB-30-PQE |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Springer International Publishing AG |
| record_format | marc |
| series2 | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Ser. |
| spelling | Park, Noseong Verfasser aut Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. Cham Springer International Publishing AG 2020 ©2020 1 Online-Ressource (543 Seiten) txt rdacontent c rdamedia cr rdacarrier Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Ser. v.335 Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Email Address Mutation for Proactive Deterrence Against Lateral Spear-Phishing Attacks -- 1 Introduction -- 2 Related Work -- 3 Threat Model -- 3.1 Attack Taxonomy -- 3.2 Attack Model -- 4 Email Mutation System -- 4.1 Overview -- 4.2 Architecture -- 4.3 Algorithm -- 4.4 Protocol -- 4.5 Identifying Lateral Spear-Phishing Attack -- 5 Email Mutation - Challenges and Solutions -- 6 Scalable Implementation and Security Measurement -- 6.1 Email Mutation Agent -- 6.2 Email Mutation Gateway -- 7 Email Mutation Verification and Evaluation -- 7.1 System Verification -- 7.2 Performance Evaluation -- 8 Limitations and Future Work -- 9 Conclusion -- References -- ThreatZoom: Hierarchical Neural Network for CVEs to CWEs Classification -- 1 Introduction -- 1.1 Motivation Example -- 1.2 Related Works -- 1.3 Challenges -- 1.4 Contribution -- 2 Methodology -- 2.1 Preprocessing -- 2.2 Feature Extraction -- 2.3 Hierarchical Decision-Making -- 3 Results -- 3.1 Dataset Specification -- 3.2 Experiments -- 4 Discussion -- 4.1 ThreatZoom and Unlabeled CVEs -- 4.2 More Fine-Grain Classification by ThreatZoom -- 5 Conclusion and Future Work -- References -- Detecting Dictionary Based AGDs Based on Community Detection -- 1 Introduction -- 2 Methodology -- 2.1 Word Graph -- 2.2 Community Detection on Word Graph -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Experiments -- References -- On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 BLE-based Contact Tracing -- 2.2 Proximity Measurement in BLE-based Contact Tracing -- 3 Analysis of BLE Software Configurations -- 4 Analysis of Proximity Measurement Approaches -- 4.1 Data Collected for Proximity Measurement -- 4.2 Data Used in Distance Calculation -- 5 Discussion 6 Related Work -- 7 Conclusion -- References -- A Formal Verification of Configuration-Based Mutation Techniques for Moving Target Defense -- 1 Introduction -- 2 Preliminaries -- 2.1 System Modeling Language -- 2.2 Duration Calculus -- 3 RHM Protocol -- 4 Verification Methodology -- 5 RHM Components Modeling -- 5.1 Moving Target Gateway -- 5.2 Moving Target Controller -- 6 MTD Verification -- 6.1 Evaluation Methodology -- 6.2 Properties Verification -- 6.3 Evaluation -- 7 Related Work -- 8 Conclusions -- References -- Coronavirus Contact Tracing App Privacy: What Data Is Shared by the Singapore OpenTrace App? -- 1 Introduction -- 2 Threat Model: What Do We Mean by Privacy? -- 3 Measurement Setup -- 3.1 Viewing Content of Encrypted Web Connections -- 3.2 Hardware and Software Used -- 3.3 Test Design -- 3.4 Finding Identifiers in Network Connections -- 4 Google Firebase -- 5 Cryptography -- 6 Measurements of Data Transmitted by OpenTrace App -- 6.1 Data Sent on Initial Startup -- 6.2 Data Sent upon Phone Number Entry -- 6.3 Data Sent When Permissions Are Granted -- 6.4 Data Sent When Sitting Idle at Main Screen -- 6.5 Data Sent by TraceTogether (v1.0.33) -- 7 Summary and Conclusions -- References -- The Maestro Attack: Orchestrating Malicious Flows with BGP -- 1 Introduction -- 2 Background -- 2.1 Border Gateway Protocol -- 2.2 BGP Poisoning -- 2.3 Link Flooding Attacks -- 3 Can Botnets Target Any Link? -- 3.1 Simulation Methodology -- 3.2 Vulnerability Experiments -- 4 The Maestro Attack -- 4.1 Poison Selection Algorithm -- 4.2 Evaluation -- 5 Internet Experiments -- 6 Attack Scope and Vulnerability -- 7 Towards Defenses -- 8 Related Work -- 9 Conclusion -- References -- pyDNetTopic: A Framework for Uncovering What Darknet Market Users Talking About -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 LDA -- 3.2 BTM -- 3.3 GSDMM. 4 Filtered Bi-Term Topic Model -- 4.1 Motivation -- 4.2 Methodology -- 5 Framework Architecture -- 5.1 Data Extraction and Preprocessing -- 5.2 Topic Models -- 5.3 Relevance Metric -- 6 Experiment -- 6.1 Evaluation Metrics -- 6.2 Performance Comparison -- 6.3 Result Analysis -- 7 Conclusion -- A List of Additional Stop Words -- B Full Topic Results of Agora Forums in 2014 -- References -- MisMesh: Security Issues and Challenges in Service Meshes -- 1 Introduction -- 2 Background -- 3 Threat Model and Experimental Design -- 4 Evaluation of Modern Service Meshes -- 5 Related Work -- 6 Conclusions -- References -- The Bitcoin Hunter: Detecting Bitcoin Traffic over Encrypted Channels -- 1 Introduction -- 2 Background on Bitcoin Traffic and Its Network Traffic -- 3 Characterizing Bitcoin Traffic -- 3.1 Proportion and Distribution of Messages -- 3.2 Shape of Traffic -- 4 Designing Bitcoin Classifiers -- 4.1 Size-Based Classifier -- 4.2 Shape-Based Classifier -- 4.3 Neural Network-Based Classifier (NN-Based) -- 4.4 Combined Classifier -- 5 Experimental Setup -- 5.1 Datasets -- 5.2 Metrics -- 5.3 Modeling Normal Users -- 6 Results -- 6.1 User Profiles and False Data -- 6.2 Size-Based Classifiers -- 6.3 Shape-Based Classifier -- 6.4 Neural Network-Based Classifier -- 6.5 Combined Classifier -- 6.6 Summary and Comparison of the Results -- 7 Countermeasures -- 7.1 Bitcoin over Tor -- 7.2 Evaluating Bitcoin Over Tor -- 8 Related Work -- 8.1 Protocol Classification -- 8.2 Attacks on Bitcoin Cryptocurrency -- 9 Conclusions -- References -- MAAN: A Multiple Attribute Association Network for Mobile Encrypted Traffic Classification -- 1 Introduction -- 2 Background -- 2.1 SSL/TLS Basics -- 2.2 Related Work -- 3 Architecture of MAAN -- 3.1 Segment Preprocessor -- 3.2 Message Feature Extractor -- 3.3 Flow Feature Extractor -- 3.4 Dense Layer 3.5 Classification Layer -- 4 Experiment -- 4.1 Dataset -- 4.2 Experiment Setting -- 4.3 Comparisons with Existing Approaches -- 4.4 Analysis of MAAN -- 4.5 The Efficiency of MAAN -- 5 Discussion -- 6 Conclusion -- A Parameters Selection -- References -- Assessing Adaptive Attacks Against Trained JavaScript Classifiers -- 1 Introduction -- 2 Problem Overview -- 2.1 Existing Classification Approaches -- 2.2 Objectives and Challenges -- 3 Threat Models -- 4 Attacks -- 4.1 Subtree Editing Mimicry Attack -- 4.2 Script Stitching Mimicry Attack -- 4.3 Gadget Composition Mimicry Attack -- 4.4 Correctness -- 5 Implementation -- 6 Experimental Evaluation -- 6.1 Dataset and Infrastructure -- 6.2 Baseline Classifier Performance -- 6.3 Evaluation of Attacks -- 6.4 Per-domain Analysis -- 6.5 Knowledge of Dataset vs Model -- 6.6 Impact of Adversarial Training -- 6.7 Execution Times -- 6.8 Analysis of Results -- 7 Related Work -- 8 Conclusion -- References -- An Encryption System for Securing Physical Signals -- 1 Introduction -- 2 Related Work -- 3 Cryptographic Model -- 4 The Vernam Physical Signal Cipher -- 4.1 Noise Mitigation -- 4.2 Key Sharing -- 5 Cryptanalysis -- 6 Signal Synchronization -- 7 Complexity and Performance -- 8 Evaluation -- 8.1 Wireless - Simulation -- 8.2 Wired - Proof of Concept -- 9 Conclusion -- 10 Appendix - Additional Figures -- References -- A Cooperative Jamming Game in Wireless Networks Under Uncertainty -- 1 Introduction -- 1.1 Related Works -- 1.2 Summary of Contributions -- 2 System Model and Game Formulation -- 2.1 System Model -- 2.2 Formulation of the Game -- 3 Best Response Functions -- 4 Nonzero-Sum Game Under Uncertainty -- 5 Numerical Illustrations -- 6 Conclusions and Future Research -- References -- SmartSwitch: Efficient Traffic Obfuscation Against Stream Fingerprinting -- 1 Introduction -- 2 Background 3 Stream Fingerprinting Attack -- 4 SmartSwitch: Our Proposed Defense Mechanism -- 5 Which Packets Are More Significant? -- 5.1 Permutation Feature Importance -- 5.2 Mutual-Information-Based Algorithms -- 6 Evaluation of Feature Selection -- 7 Evaluation of SmartSwitch -- 7.1 Defense Performance of NDSS19 on YouTube Dataset -- 7.2 Defense Performance of SmartSwitch on YouTube Dataset -- 8 Related Work -- 9 Conclusion -- References -- Misreporting Attacks in Software-Defined Networking -- 1 Introduction -- 2 Background -- 3 Attacking the Load Balancer -- 3.1 Threat Model and Overview -- 3.2 Attack Model -- 3.3 Max-Flooding Attack -- 3.4 Stealthy Attack -- 3.5 Assessing the Impact -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Effects on Network Performance -- 4.4 Discussion -- 5 Conclusion -- References -- A Study of the Privacy of COVID-19 Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 Digital Contact Tracing -- 2.2 BLE in Proximity Tracing -- 2.3 Centralized vs. Decentralized Mobile Contact Tracing -- 3 Methodology -- 3.1 Scope and Overview -- 3.2 Contact Tracing Relevant API Recognition -- 3.3 Privacy Information Identification -- 3.4 Cross-Platform Comparison -- 4 Evaluation -- 4.1 COVID-19 Mobile App Collection -- 4.2 Evaluation Result -- 4.3 Evaluation Result of Cross-Platform Comparison -- 5 Discussion -- 5.1 Limitations -- 5.2 Mitigation on the Privacy Issues Identified -- 6 Related Work -- 7 Conclusion -- References -- Best-Effort Adversarial Approximation of Black-Box Malware Classifiers -- 1 Introduction -- 2 Background and Threat Model -- 2.1 Model Approximation Attacks -- 2.2 Threat Model and Problem Statement -- 3 Approach -- 3.1 Approximation Set Labeling -- 3.2 Representation Mapping -- 3.3 Progressive Approximation -- 3.4 Similarity Comparison -- 4 Evaluation -- 4.1 Datasets 4.2 Experimental Setup Computer networks-Security measures-Congresses Telecommunication systems-Security measures-Congresses Computer security Electronic books Sun, Kun Sonstige oth Foresti, Sara Sonstige oth Butler, Kevin Sonstige oth Saxena, Nitesh Sonstige oth Erscheint auch als Druck-Ausgabe Park, Noseong Security and Privacy in Communication Networks Cham : Springer International Publishing AG,c2020 9783030630850 |
| spellingShingle | Park, Noseong Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Email Address Mutation for Proactive Deterrence Against Lateral Spear-Phishing Attacks -- 1 Introduction -- 2 Related Work -- 3 Threat Model -- 3.1 Attack Taxonomy -- 3.2 Attack Model -- 4 Email Mutation System -- 4.1 Overview -- 4.2 Architecture -- 4.3 Algorithm -- 4.4 Protocol -- 4.5 Identifying Lateral Spear-Phishing Attack -- 5 Email Mutation - Challenges and Solutions -- 6 Scalable Implementation and Security Measurement -- 6.1 Email Mutation Agent -- 6.2 Email Mutation Gateway -- 7 Email Mutation Verification and Evaluation -- 7.1 System Verification -- 7.2 Performance Evaluation -- 8 Limitations and Future Work -- 9 Conclusion -- References -- ThreatZoom: Hierarchical Neural Network for CVEs to CWEs Classification -- 1 Introduction -- 1.1 Motivation Example -- 1.2 Related Works -- 1.3 Challenges -- 1.4 Contribution -- 2 Methodology -- 2.1 Preprocessing -- 2.2 Feature Extraction -- 2.3 Hierarchical Decision-Making -- 3 Results -- 3.1 Dataset Specification -- 3.2 Experiments -- 4 Discussion -- 4.1 ThreatZoom and Unlabeled CVEs -- 4.2 More Fine-Grain Classification by ThreatZoom -- 5 Conclusion and Future Work -- References -- Detecting Dictionary Based AGDs Based on Community Detection -- 1 Introduction -- 2 Methodology -- 2.1 Word Graph -- 2.2 Community Detection on Word Graph -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Experiments -- References -- On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 BLE-based Contact Tracing -- 2.2 Proximity Measurement in BLE-based Contact Tracing -- 3 Analysis of BLE Software Configurations -- 4 Analysis of Proximity Measurement Approaches -- 4.1 Data Collected for Proximity Measurement -- 4.2 Data Used in Distance Calculation -- 5 Discussion 6 Related Work -- 7 Conclusion -- References -- A Formal Verification of Configuration-Based Mutation Techniques for Moving Target Defense -- 1 Introduction -- 2 Preliminaries -- 2.1 System Modeling Language -- 2.2 Duration Calculus -- 3 RHM Protocol -- 4 Verification Methodology -- 5 RHM Components Modeling -- 5.1 Moving Target Gateway -- 5.2 Moving Target Controller -- 6 MTD Verification -- 6.1 Evaluation Methodology -- 6.2 Properties Verification -- 6.3 Evaluation -- 7 Related Work -- 8 Conclusions -- References -- Coronavirus Contact Tracing App Privacy: What Data Is Shared by the Singapore OpenTrace App? -- 1 Introduction -- 2 Threat Model: What Do We Mean by Privacy? -- 3 Measurement Setup -- 3.1 Viewing Content of Encrypted Web Connections -- 3.2 Hardware and Software Used -- 3.3 Test Design -- 3.4 Finding Identifiers in Network Connections -- 4 Google Firebase -- 5 Cryptography -- 6 Measurements of Data Transmitted by OpenTrace App -- 6.1 Data Sent on Initial Startup -- 6.2 Data Sent upon Phone Number Entry -- 6.3 Data Sent When Permissions Are Granted -- 6.4 Data Sent When Sitting Idle at Main Screen -- 6.5 Data Sent by TraceTogether (v1.0.33) -- 7 Summary and Conclusions -- References -- The Maestro Attack: Orchestrating Malicious Flows with BGP -- 1 Introduction -- 2 Background -- 2.1 Border Gateway Protocol -- 2.2 BGP Poisoning -- 2.3 Link Flooding Attacks -- 3 Can Botnets Target Any Link? -- 3.1 Simulation Methodology -- 3.2 Vulnerability Experiments -- 4 The Maestro Attack -- 4.1 Poison Selection Algorithm -- 4.2 Evaluation -- 5 Internet Experiments -- 6 Attack Scope and Vulnerability -- 7 Towards Defenses -- 8 Related Work -- 9 Conclusion -- References -- pyDNetTopic: A Framework for Uncovering What Darknet Market Users Talking About -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 LDA -- 3.2 BTM -- 3.3 GSDMM. 4 Filtered Bi-Term Topic Model -- 4.1 Motivation -- 4.2 Methodology -- 5 Framework Architecture -- 5.1 Data Extraction and Preprocessing -- 5.2 Topic Models -- 5.3 Relevance Metric -- 6 Experiment -- 6.1 Evaluation Metrics -- 6.2 Performance Comparison -- 6.3 Result Analysis -- 7 Conclusion -- A List of Additional Stop Words -- B Full Topic Results of Agora Forums in 2014 -- References -- MisMesh: Security Issues and Challenges in Service Meshes -- 1 Introduction -- 2 Background -- 3 Threat Model and Experimental Design -- 4 Evaluation of Modern Service Meshes -- 5 Related Work -- 6 Conclusions -- References -- The Bitcoin Hunter: Detecting Bitcoin Traffic over Encrypted Channels -- 1 Introduction -- 2 Background on Bitcoin Traffic and Its Network Traffic -- 3 Characterizing Bitcoin Traffic -- 3.1 Proportion and Distribution of Messages -- 3.2 Shape of Traffic -- 4 Designing Bitcoin Classifiers -- 4.1 Size-Based Classifier -- 4.2 Shape-Based Classifier -- 4.3 Neural Network-Based Classifier (NN-Based) -- 4.4 Combined Classifier -- 5 Experimental Setup -- 5.1 Datasets -- 5.2 Metrics -- 5.3 Modeling Normal Users -- 6 Results -- 6.1 User Profiles and False Data -- 6.2 Size-Based Classifiers -- 6.3 Shape-Based Classifier -- 6.4 Neural Network-Based Classifier -- 6.5 Combined Classifier -- 6.6 Summary and Comparison of the Results -- 7 Countermeasures -- 7.1 Bitcoin over Tor -- 7.2 Evaluating Bitcoin Over Tor -- 8 Related Work -- 8.1 Protocol Classification -- 8.2 Attacks on Bitcoin Cryptocurrency -- 9 Conclusions -- References -- MAAN: A Multiple Attribute Association Network for Mobile Encrypted Traffic Classification -- 1 Introduction -- 2 Background -- 2.1 SSL/TLS Basics -- 2.2 Related Work -- 3 Architecture of MAAN -- 3.1 Segment Preprocessor -- 3.2 Message Feature Extractor -- 3.3 Flow Feature Extractor -- 3.4 Dense Layer 3.5 Classification Layer -- 4 Experiment -- 4.1 Dataset -- 4.2 Experiment Setting -- 4.3 Comparisons with Existing Approaches -- 4.4 Analysis of MAAN -- 4.5 The Efficiency of MAAN -- 5 Discussion -- 6 Conclusion -- A Parameters Selection -- References -- Assessing Adaptive Attacks Against Trained JavaScript Classifiers -- 1 Introduction -- 2 Problem Overview -- 2.1 Existing Classification Approaches -- 2.2 Objectives and Challenges -- 3 Threat Models -- 4 Attacks -- 4.1 Subtree Editing Mimicry Attack -- 4.2 Script Stitching Mimicry Attack -- 4.3 Gadget Composition Mimicry Attack -- 4.4 Correctness -- 5 Implementation -- 6 Experimental Evaluation -- 6.1 Dataset and Infrastructure -- 6.2 Baseline Classifier Performance -- 6.3 Evaluation of Attacks -- 6.4 Per-domain Analysis -- 6.5 Knowledge of Dataset vs Model -- 6.6 Impact of Adversarial Training -- 6.7 Execution Times -- 6.8 Analysis of Results -- 7 Related Work -- 8 Conclusion -- References -- An Encryption System for Securing Physical Signals -- 1 Introduction -- 2 Related Work -- 3 Cryptographic Model -- 4 The Vernam Physical Signal Cipher -- 4.1 Noise Mitigation -- 4.2 Key Sharing -- 5 Cryptanalysis -- 6 Signal Synchronization -- 7 Complexity and Performance -- 8 Evaluation -- 8.1 Wireless - Simulation -- 8.2 Wired - Proof of Concept -- 9 Conclusion -- 10 Appendix - Additional Figures -- References -- A Cooperative Jamming Game in Wireless Networks Under Uncertainty -- 1 Introduction -- 1.1 Related Works -- 1.2 Summary of Contributions -- 2 System Model and Game Formulation -- 2.1 System Model -- 2.2 Formulation of the Game -- 3 Best Response Functions -- 4 Nonzero-Sum Game Under Uncertainty -- 5 Numerical Illustrations -- 6 Conclusions and Future Research -- References -- SmartSwitch: Efficient Traffic Obfuscation Against Stream Fingerprinting -- 1 Introduction -- 2 Background 3 Stream Fingerprinting Attack -- 4 SmartSwitch: Our Proposed Defense Mechanism -- 5 Which Packets Are More Significant? -- 5.1 Permutation Feature Importance -- 5.2 Mutual-Information-Based Algorithms -- 6 Evaluation of Feature Selection -- 7 Evaluation of SmartSwitch -- 7.1 Defense Performance of NDSS19 on YouTube Dataset -- 7.2 Defense Performance of SmartSwitch on YouTube Dataset -- 8 Related Work -- 9 Conclusion -- References -- Misreporting Attacks in Software-Defined Networking -- 1 Introduction -- 2 Background -- 3 Attacking the Load Balancer -- 3.1 Threat Model and Overview -- 3.2 Attack Model -- 3.3 Max-Flooding Attack -- 3.4 Stealthy Attack -- 3.5 Assessing the Impact -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Effects on Network Performance -- 4.4 Discussion -- 5 Conclusion -- References -- A Study of the Privacy of COVID-19 Contact Tracing Apps -- 1 Introduction -- 2 Background -- 2.1 Digital Contact Tracing -- 2.2 BLE in Proximity Tracing -- 2.3 Centralized vs. Decentralized Mobile Contact Tracing -- 3 Methodology -- 3.1 Scope and Overview -- 3.2 Contact Tracing Relevant API Recognition -- 3.3 Privacy Information Identification -- 3.4 Cross-Platform Comparison -- 4 Evaluation -- 4.1 COVID-19 Mobile App Collection -- 4.2 Evaluation Result -- 4.3 Evaluation Result of Cross-Platform Comparison -- 5 Discussion -- 5.1 Limitations -- 5.2 Mitigation on the Privacy Issues Identified -- 6 Related Work -- 7 Conclusion -- References -- Best-Effort Adversarial Approximation of Black-Box Malware Classifiers -- 1 Introduction -- 2 Background and Threat Model -- 2.1 Model Approximation Attacks -- 2.2 Threat Model and Problem Statement -- 3 Approach -- 3.1 Approximation Set Labeling -- 3.2 Representation Mapping -- 3.3 Progressive Approximation -- 3.4 Similarity Comparison -- 4 Evaluation -- 4.1 Datasets 4.2 Experimental Setup Computer networks-Security measures-Congresses Telecommunication systems-Security measures-Congresses Computer security |
| title | Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| title_auth | Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| title_exact_search | Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| title_exact_search_txtP | Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| title_full | Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| title_fullStr | Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| title_full_unstemmed | Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| title_short | Security and Privacy in Communication Networks |
| title_sort | security and privacy in communication networks 16th eai international conference securecomm 2020 washington dc usa october 21 23 2020 proceedings part i |
| title_sub | 16th EAI International Conference, SecureComm 2020, Washington, DC, USA, October 21-23, 2020, Proceedings, Part I. |
| topic | Computer networks-Security measures-Congresses Telecommunication systems-Security measures-Congresses Computer security |
| topic_facet | Computer networks-Security measures-Congresses Telecommunication systems-Security measures-Congresses Computer security |
| work_keys_str_mv | AT parknoseong securityandprivacyincommunicationnetworks16theaiinternationalconferencesecurecomm2020washingtondcusaoctober21232020proceedingsparti AT sunkun securityandprivacyincommunicationnetworks16theaiinternationalconferencesecurecomm2020washingtondcusaoctober21232020proceedingsparti AT forestisara securityandprivacyincommunicationnetworks16theaiinternationalconferencesecurecomm2020washingtondcusaoctober21232020proceedingsparti AT butlerkevin securityandprivacyincommunicationnetworks16theaiinternationalconferencesecurecomm2020washingtondcusaoctober21232020proceedingsparti AT saxenanitesh securityandprivacyincommunicationnetworks16theaiinternationalconferencesecurecomm2020washingtondcusaoctober21232020proceedingsparti |