Data analysis for network cyber-security:
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London, UK
Imperial College Press
[2014]
|
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 Volltext |
| Beschreibung: | Description based on print version record |
| Beschreibung: | 1 online resource |
| ISBN: | 1783263741 178326375X 9781783263745 9781783263752 |
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| 505 | 8 | |a Ch. 1. Inference for graphs and networks: Adapting classical tools to modern data / Benjamin P. Olding and Patrick J. Wolfe -- ch. 2. Rapid detection of attacks in computer networks by quickest changepoint detection methods / Alexander G. Tartakovsky -- ch. 3. Statistical detection of intruders within computer networks using scan statistics / Joshua Neil ... [et al.] -- ch. 4. Characterizing dynamic group behavior in social networks for cybernetics / Sumeet Dua and Pradeep Chowriappa -- ch. 5. Several approaches for detecting anomalies in network traffic data / Celine Levy-Leduc -- ch. 6. Monitoring a device in a communication network / Nick A. Heard and Melissa J. Turcotte | |
| 505 | 8 | |a There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity. Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches. This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research | |
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| 700 | 1 | |a Heard, Nicholas |4 edt | |
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Datensatz im Suchindex
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| contents | Ch. 1. Inference for graphs and networks: Adapting classical tools to modern data / Benjamin P. Olding and Patrick J. Wolfe -- ch. 2. Rapid detection of attacks in computer networks by quickest changepoint detection methods / Alexander G. Tartakovsky -- ch. 3. Statistical detection of intruders within computer networks using scan statistics / Joshua Neil ... [et al.] -- ch. 4. Characterizing dynamic group behavior in social networks for cybernetics / Sumeet Dua and Pradeep Chowriappa -- ch. 5. Several approaches for detecting anomalies in network traffic data / Celine Levy-Leduc -- ch. 6. Monitoring a device in a communication network / Nick A. Heard and Melissa J. Turcotte There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity. Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches. This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research |
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| dewey-full | 005.8 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
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| discipline | Informatik |
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| spelling | Data analysis for network cyber-security Niall Adams & Nicholas Heard, editors London, UK Imperial College Press [2014] © 2014 1 online resource txt rdacontent c rdamedia cr rdacarrier Description based on print version record Ch. 1. Inference for graphs and networks: Adapting classical tools to modern data / Benjamin P. Olding and Patrick J. Wolfe -- ch. 2. Rapid detection of attacks in computer networks by quickest changepoint detection methods / Alexander G. Tartakovsky -- ch. 3. Statistical detection of intruders within computer networks using scan statistics / Joshua Neil ... [et al.] -- ch. 4. Characterizing dynamic group behavior in social networks for cybernetics / Sumeet Dua and Pradeep Chowriappa -- ch. 5. Several approaches for detecting anomalies in network traffic data / Celine Levy-Leduc -- ch. 6. Monitoring a device in a communication network / Nick A. Heard and Melissa J. Turcotte There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity. Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches. This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research COMPUTERS / Internet / Security bisacsh COMPUTERS / Networking / Security bisacsh COMPUTERS / Security / General bisacsh Computer networks / Security measures fast Computer networks Security measures Congresses (DE-588)1071861417 Konferenzschrift gnd-content Adams, Niall M. 1968- edt Heard, Nicholas edt Erscheint auch als Druck-Ausgabe Data analysis for network cyber-security http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=779681 Aggregator Volltext |
| spellingShingle | Data analysis for network cyber-security Ch. 1. Inference for graphs and networks: Adapting classical tools to modern data / Benjamin P. Olding and Patrick J. Wolfe -- ch. 2. Rapid detection of attacks in computer networks by quickest changepoint detection methods / Alexander G. Tartakovsky -- ch. 3. Statistical detection of intruders within computer networks using scan statistics / Joshua Neil ... [et al.] -- ch. 4. Characterizing dynamic group behavior in social networks for cybernetics / Sumeet Dua and Pradeep Chowriappa -- ch. 5. Several approaches for detecting anomalies in network traffic data / Celine Levy-Leduc -- ch. 6. Monitoring a device in a communication network / Nick A. Heard and Melissa J. Turcotte There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity. Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches. This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research COMPUTERS / Internet / Security bisacsh COMPUTERS / Networking / Security bisacsh COMPUTERS / Security / General bisacsh Computer networks / Security measures fast Computer networks Security measures Congresses |
| subject_GND | (DE-588)1071861417 |
| title | Data analysis for network cyber-security |
| title_auth | Data analysis for network cyber-security |
| title_exact_search | Data analysis for network cyber-security |
| title_full | Data analysis for network cyber-security Niall Adams & Nicholas Heard, editors |
| title_fullStr | Data analysis for network cyber-security Niall Adams & Nicholas Heard, editors |
| title_full_unstemmed | Data analysis for network cyber-security Niall Adams & Nicholas Heard, editors |
| title_short | Data analysis for network cyber-security |
| title_sort | data analysis for network cyber security |
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