Data mining trends and applications in criminal science and investigations:
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| Sprache: | English |
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Information Science Reference, an imprint of IGI Global
[2016]
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| Schriftenreihe: | Advances in data mining and database management (ADMDM) book series
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| 245 | 1 | 0 | |a Data mining trends and applications in criminal science and investigations |c Omowunmi E. Isafiade (University of Cape Town, South Africa), Antoine B. Bagula (University of the Western Cape, South Africa) |
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Datensatz im Suchindex
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TABLE OF CONTENTS
FOREWORD XV
PREFACE XVII
ACKNOWLEDGMENT XXIV
SECTION 1
CHALLENGES AND EXISTING STRATEGIES IN PUBLIC SAFETY AND CRIME
MINING
CHAPTER 1
ON THE ADVANCEMENT OF USING DATA MINING FOR CRIME SITUATION RECOGNITION:
A COMPARATIVE REVIEW 1
OMOWUNMI E. ISAFIADE, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
ANTOINE BAGULA, UNIVERSITY OF WESTERN CAPE, SOUTH AFRICA
SONIA BERMAN, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
CHAPTER 2
A CLASSIFICATION FRAMEWORK FOR DATA MINING APPLICATIONS IN CRIMINAL
SCIENCE AND INVESTIGATIONS 32
MAHIMA GOYAL, AMBEDKAR INSTITUTE OF ADVANCED COMMUNICATION
TECHNOLOGIES AND RESEARCH, INDIA
VISHAL BHATNAGAR, AMBEDKAR INSTITUTE OF ADVANCED COMMUNICATION
TECHNOLOGIES AND RESEARCH, INDIA
ARUSHI JAIN, AMBEDKAR INSTITUTE OF ADVANCED COMMUNICATION
TECHNOLOGIES AND RESEARCH, INDIA
SECTION 2
HOTSPOT, SPATIAL, AND VISUAL ANALYTICS
CHAPTER 3
VISUAL ANALYTICS FOR CRIME ANALYSIS AND DECISION SUPPORT 53
CHIH-HAO KU, LAWRENCE TECHNOLOGICAL UNIVERSITY, USA
ALICIA IRIBERRI, CALIFORNIA STATE UNIVERSITY, FRESNO, USA
GOUTAM JENA, LAWRENCE TECHNOLOGICAL UNIVERSITY, USA
CHAPTER 4
CRIME HOTSPOT DETECTION: A COMPUTATIONAL PERSPECTIVE 82
EMRE EFTELIOGLU, UNIVERSITY OF MINNESOTA, USA
SHASHI SHEKHAR, UNIVERSITY OF MINNESOTA, USA
XUN TANG, UNIVERSITY OF MINNESOTA, USA
CHAPTER 5
VISUAL DATA MINING: A GREAT OPPORTUNITY FOR CRIMINAL INVESTIGATION 112
MEHRDAD GHAZIASGAR, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
NATHAN DE LA CRUZ, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
ANTOINE BAGULA, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
JAMES CONNAN, RHODES UNIVERSITY, SOUTH AFRICA
SECTION 3
FORENSICS, SUSPECT MODELING, AND INTELLIGENCE GATHERING
CHAPTER 6
ON THE USE OF BAYESIAN NETWORK IN CRIME SUSPECT MODELLING AND LEGAL
DECISION SUPPORT 143
O. E. ISAFIADE, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
A. B. BAGULA, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
S. BERMAN, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
CHAPTER 7
FORENSIC INVESTIGATION OF DIGITAL CRIMES IN HEALTHCARE APPLICATIONS 169
NOURHENE ELLOUZE, UNIVERSITY OF CARTHAGE, TUNISIA
SLIM REKHIS, UNIVERSITY OF CARTHAGE, TUNISIA
NOUREDDINE BOUDRIGA, UNIVERSITY OF CARTHAGE, TUNISIA
SECTION 4
DENIAL OF SERVICE, CYBER-CRIME, AND INTRUSION DETECTION
MANAGEMENT
CHAPTER 8
DATA MINING ANALYTICS FOR CRIME SECURITY INVESTIGATION AND INTRUSION
DETECTION 212
BOUTHEINA FESSI, CN&S, UNIVERSITY OF CARTHAGE, TUNISIA
YACINE DJEMAIEL, CN&S, UNIVERSITY OF CARTHAGE, TUNISIA
NOUREDDINE BOUDRIGA, CN&S, UNIVERSITY OF CARTHAGE, TUNISIA
CHAPTER 9
AUTOMATED IDENTIFICATION OF CHILD ABUSE IN CHAT ROOMS BY USING DATA
MINING 245
MOHAMMADREZA KEYVANPOUR, ALZAHRA UNIVERSITY, IRAN
MOHAMMADREZA EBRAHIMI, CONCORDIA UNIVERSITY, CANADA
NECMIYE GENE NAYEBI, ECOLE DE TECHNOLOGIE SUPERIEURE (ETS), CANADA
OLGA ORMANDJIEVA, CONCORDIA UNIVERSITY, CANADA
CHING Y. SUEN, CONCORDIA UNIVERSITY, CANADA
CHAPTER 10
DATA MINING TECHNIQUES FOR DISTRIBUTED DENIAL OF SERVICE ATTACKS
DETECTION
IN THE INTERNET OF THINGS: A RESEARCH SURVEY 275
PHEEHA MACHAKA, DECISION SCIENCES DEPARTMENT, UNIVERSITY OF SOUTH
AFRICA, SOUTH AFRICA
FULUFHELO NELWAMONDO, MODELLING AND DIGITAL SCIENCE, COUNCIL FOR
SCIENTIFIC AND INDUSTRIAL RESEARCH, SOUTH AFRICA
CONCLUSION 335
COMPILATION OF REFERENCES 339
ABOUT THE CONTRIBUTORS 376
INDEX 383
DETAILED TABLE OF CONTENTS
FOREWORD XV
PREFACE XVII
ACKNOWLEDGMENT XXIV
SECTION 1
CHALLENGES AND EXISTING STRATEGIES IN PUBLIC SAFETY AND CRIME
MINING
CHAPTER 1
ON THE ADVANCEMENT OF USING DATA MINING FOR CRIME SITUATION RECOGNITION:
A COMPARATIVE REVIEW 1
OMOWUNMI E. ISAFIADE, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
ANTOINE BAGULA, UNIVERSITY OF WESTERN CAPE, SOUTH AFRICA
SONIA BERMAN, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
THE PRIMARY ROLE OF INTELLIGENCE ORGANISATIONS AND PUBLIC SAFETY
AGENCIES ENCOMPASSES
PROTECTING THE LIVES AND PROPERTY OF CITIZENS. HOWEVER, THE URBAN
POPULATION GROWTH
RATE TENDS TO OVERSHADOW THE AVAILABLE SECURITY RESOURCES. THUS, THE
SECURITY
AGENCIES APPEAR TO BE MORE REACTIVE THAN PROACTIVE. PUBLIC SAFETY
AGENCIES USUALLY
HAVE A PLETHORA OF UNDER-UTILISED CRIME INCIDENT REPORTS AT THEIR
DISPOSAL, WHICH IF
EFFICIENTLY ANALYSED COULD REVEAL SOME PREVIOUSLY UNKNOWN USEFUL
INFORMATION.
SUCH INFORMATION REVEALS INSIGHTS INTO A RANGE OF FUNCTIONS IN A CRIME
INVESTIGATION,
WHICH CAN ASSIST IN DETERMINING CRIMINAL TRENDS AND IN KNOWLEDGE-DRIVEN
DECISION
SUPPORT. THIS CHAPTER PROVIDES AN OVERVIEW OF DATA MINING TECHNIQUES AND
EXISTING
APPLICATIONS USED IN THIS DOMAIN OF INTEREST. FEATURES OF EXISTING
APPLICATIONS AND
TECHNIQUES, SUCH AS EXPLORATORY BASIS, MODEL SELECTION, ALGORITHM
ADVANCEMENT AND
RESULT SUMMARY, ARE COMPARED. FUTURE POTENTIAL OF CRIME DATA MINING, AND
OPEN
RESEARCH ISSUES, ARE ALSO DISCUSSED.
CHAPTER 2
A CLASSIFICATION FRAMEWORK FOR DATA MINING APPLICATIONS IN CRIMINAL
SCIENCE AND INVESTIGATIONS 32
MAHIMA GOYAL, AMBEDKAR INSTITUTE OF ADVANCED COMMUNICATION
TECHNOLOGIES AND RESEARCH, INDIA
VISHAL BHATNAGAR, AMBEDKAR INSTITUTE OF ADVANCED COMMUNICATION
TECHNOLOGIES AND RESEARCH, INDIA
ARUSHI JAIN, AMBEDKAR INSTITUTE OF ADVANCED COMMUNICATION
TECHNOLOGIES AND RESEARCH, INDIA
THE IMPORTANCE OF DATA ANALYSIS ACROSS DIFFERENT DOMAINS IS GROWING DAY
BY DAY.
THIS IS EVIDENT IN THE FACT THAT CRUCIAL INFORMATION IS RETRIEVED
THROUGH DATA ANALYSIS,
USING DIFFERENT AVAILABLE TOOLS. THE USAGE OF DATA MINING AS A TOOL TO
UNCOVER THE
NUGGETS OF CRITICAL AND CRUCIAL INFORMATION IS EVIDENT IN MODERN DAY
SCENARIOS. THIS
CHAPTER PRESENTS A DISCUSSION ON THE USAGE OF DATA MINING TOOLS AND
TECHNIQUES IN
THE AREA OF CRIMINAL SCIENCE AND INVESTIGATIONS. THE APPLICATION OF DATA
MINING
TECHNIQUES IN CRIMINAL SCIENCE HELP IN UNDERSTANDING THE CRIMINAL
PSYCHOLOGY AND
CONSEQUENTLY PROVIDES INSIGHT INTO EFFECTIVE MEASURES TO CURB CRIME.
THIS CHAPTER
PROVIDES A STATE-OF-THE-ART REPORT ON THE RESEARCH CONDUCTED IN THIS
DOMAIN OF INTEREST
BY USING A CLASSIFICATION SCHEME AND PROVIDING A ROAD MAP ON THE USAGE
OF VARIOUS
DATA MINING TOOLS AND TECHNIQUES. FURTHERMORE, THE CHALLENGES AND
OPPORTUNITIES
IN THE APPLICATION OF DATA MINING TECHNIQUES IN CRIMINAL INVESTIGATION
IS EXPLORED
AND DETAILED IN THIS CHAPTER.
SECTION 2
HOTSPOT, SPATIAL, AND VISUAL ANALYTICS
CHAPTER 3
VISUAL ANALYTICS FOR CRIME ANALYSIS AND DECISION SUPPORT 53
CHIH-HAO KU, LAWRENCE TECHNOLOGICAL UNIVERSITY, USA
ALICIA IRIBERRI, CALIFORNIA STATE UNIVERSITY, FRESNO, USA
GOUTAM JENA, LAWRENCE TECHNOLOGICAL UNIVERSITY, USA
TODAY, THE AMOUNT OF DIGITAL DATA INCREASES EXPONENTIALLY DUE TO THE
RAPID GROWTH
OF THE INTERNET, MOBILE, AND SENSORY DATA. CRIME DATA ARE ARRIVING FROM
MULTIPLE
SOURCES AND FORMATS. THE MAJOR CHALLENGE FOR CRIME ANALYSIS IS TO STORE,
MANIPULATE,
MANAGE, AND ANALYZE DATA EFFICIENTLY. TO GAIN USEFUL INSIGHT FROM A
GREAT AMOUNT OF
RAW DATA, VISUAL ANALYTICS TECHNIQUES HAVE BEEN DRAWN ATTENTION TO LAW
ENFORCEMENT
AGENCIES AND RESEARCHERS. THE VISUAL ANALYTICS APPLICATIONS DO NOT ERASE
THE NEED
FOR CRIME ANALYSTS' INSIGHT. TO MAKE BETTER PREDICTIONS AND SMARTER
DECISIONS,
DATA MINING, TEXT MINING, INFORMATION VISUALIZATION, HUMAN-COMPUTER
INTERACTION,
AND ANALYTICS TECHNIQUES ARE IMPORTANT TO EXPLORE. THIS BOOK CHAPTER
PROVIDES AN
OVERVIEW OF DIFFERENT TYPES OF CRIME DATA, DISCUSSES HOW TO ANALYZE AND
VISUALIZE
DIFFERENT TYPES OF DATA, AND EXPLORES POPULAR VISUALIZATION TOOLKITS
THAT HAVE BEEN
USED FOR CRIME ANALYSIS.
CHAPTER 4
CRIME HOTSPOT DETECTION: A COMPUTATIONAL PERSPECTIVE 82
EMRE EFTELIOGLU, UNIVERSITY OF MINNESOTA, USA
SHASHI SHEKHAR, UNIVERSITY OF MINNESOTA, USA
XUN TANG, UNIVERSITY OF MINNESOTA, USA
GIVEN A SET OF CRIME LOCATIONS, A STATISTICALLY SIGNIFICANT CRIME
HOTSPOT IS AN AREA
WHERE THE CONCENTRATION OF CRIMES INSIDE IS SIGNIFICANTLY HIGHER THAN
OUTSIDE. THE
MOTIVATION OF CRIME HOTSPOT DETECTION IS TWOFOLD: DETECTING CRIME
HOTSPOTS TO FOCUS
THE DEPLOYMENT OF POLICE ENFORCEMENT AND PREDICTING THE POTENTIAL
RESIDENCE OF A
SERIAL CRIMINAL. CRIME HOTSPOT DETECTION IS COMPUTATIONALLY CHALLENGING
DUE TO THE
DIFFICULTY OF ENUMERATING ALL POTENTIAL HOTSPOT AREAS, SELECTING AN
INTEREST MEASURE TO
COMPARE THESE WITH THE OVERALL CRIME INTENSITY, AND TESTING FOR
STATISTICAL SIGNIFICANCE TO
REDUCE CHANCE PATTERNS. THIS CHAPTER FOCUSES ON STATISTICAL SIGNIFICANT
CRIME HOTSPOTS.
FIRST, THE FOUNDATIONS OF SPATIAL SCAN STATISTICS AND ITS APPLICATIONS
(I.E. SATSCAN)
TO CIRCULAR HOTSPOT DETECTION ARE REVIEWED. NEXT, RING-SHAPED HOTSPOT
DETECTION IS
INTRODUCED. THIRD, LINEAR HOTSPOT DETECTION IS DESCRIBED SINCE MOST
CRIMES OCCUR
ALONG A ROAD NETWORK. THE CHAPTER CONCLUDES WITH FUTURE RESEARCH
DIRECTIONS IN
CRIME HOTSPOT DETECTION.
CHAPTER 5
VISUAL DATA MINING: A GREAT OPPORTUNITY FOR CRIMINAL INVESTIGATION 112
MEHRDAD GHAZXASGAR, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
NATHAN DE LA CRUZ, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
ANTOINE BAGULA, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
JAMES CONNAN, RHODES UNIVERSITY, SOUTH AFRICA
CURRENT GENERATION CRIMINAL JUSTICE RELIES MOSTLY ON MANUAL PROCEDURES
AND PROCESSES
WHICH ARE TIME-CONSUMING AND ERROR-PRONE. A POLYGRAPH TEST CONSISTS OF
ONLY "YES"
OR "NO" QUESTIONS AND DEPENDS SEVERAL PHYSIOLOGICAL RESPONSES IN
SUBJECTS. IT'S
EFFECTIVENESS AND ACCURACY HAVE BEEN QUESTIONED DUE TO THE POSSIBILITY
OF SWAYING
THE EXAMINER BY INDIVIDUALS THAT ARE CAPABLE OF CONTROLLING THEIR
PHYSICAL REACTIONS
IN ORDER TO DEFEAT THE LIE DETECTION EXERCISE. THE CRIMINAL JUSTICE OF
THE FUTURE IS
EXPECTED TO BE EMPOWERED BY THE MOST MODERN INFORMATION AND
COMMUNICATION
TECHNOLOGIES TO PROVIDE VARIOUS PARTICIPANTS IN THE JUSTICE SYSTEM WITH
A RICH SET
OF SERVICES SUCH AS VIRTUAL COURT PRESENCE AND HEARING PARTICIPATION
THROUGH VISUAL
SENSOR NETWORKS. THIS CHAPTER REVISITS THE ISSUE OF DECEPTION DETECTION
BY PROPOSING
VISUAL DATA MINING AS A NON-INVASIVE ALTERNATIVE TO DECEPTION DETECTION
IN NEXT
GENERATION CRIMINAL JUSTICE. IMAGE PROCESSING AND MACHINE LEARNING
TECHNIQUES ARE
USED TO ACCURATELY DETECT FACIAL MICRO-EXPRESSIONS WHICH HAVE BEEN SHOWN
TO BE
STRONG INDICATORS OF DECEPTION.
SECTION 3
FORENSICS, SUSPECT MODELING, AND INTELLIGENCE GATHERING
CHAPTER 6
ON THE USE OF BAYESIAN NETWORK IN CRIME SUSPECT MODELLING AND LEGAL
DECISION SUPPORT 143
O. E. LSAFIADE, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
A. B. BAGULA, UNIVERSITY OF THE WESTERN CAPE, SOUTH AFRICA
S. BERMAN, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA
PREDICTIVE POLICING (PP) RELATES TO IDENTIFYING POTENTIALLY RELATED
OFFENCES, SIMILAR
CRIMINAL ATTRIBUTES AND POTENTIAL CRIMINAL ACTIVITY, IN ORDER TO TAKE
ACTIONABLE
MEASURES IN DETERRING CRIME. SIMILARLY, LEGAL DECISION MAKING PROCESS
(LDMP)
CONSIDERS SOME LEVEL OF PROBABILISTIC REASONING IN DERIVING LOGICAL
EVIDENCE FROM
CRIME INCIDENTS. BAYESIAN NETWORKS (BN) HAVE GREAT POTENTIAL IN
CONTRIBUTING TO
THE AREA OF PP AND LDMP. BEING BASED ON PROBABILISTIC REASONING, THEY
CAN ASSESS
UNCERTAINTY IN CRIME RELATED ATTRIBUTES AND DERIVE USEFUL EVIDENCE BASED
ON CRIME
INCIDENT OBSERVATIONS OR EVIDENTIAL DATA. FOR EXAMPLE, IN A PARTICULAR
CONTEXT OF
CRIME INVESTIGATION, BN BASED INFERENCE COULD HELP COLLECT USEFUL
EVIDENCE ABOUT A
CRIME SCENARIO OR INCIDENT. SUCH EVIDENCE PROMOTES EFFECTIVE LEGAL
DECISION MAKING
PROCESS AND CAN ASSIST PUBLIC SAFETY AND SECURITY AGENCIES IN ALLOCATING
RESOURCES IN
AN OPTIMAL FASHION. THIS CHAPTER REPORTS ON VARIOUS APPLICATION AREAS OF
BN IN THE
CRIME DOMAIN, HIGHLIGHTS THE POTENTIAL OF BN AND PRESENTS "THOUGHT
EXPERIMENTS"
ON HOW OFFENDER CHARACTERISTICS COULD BE MODELLED FOR DECISION SUPPORT
IN LEGAL
MATTERS. THE CHAPTER FURTHER REPORTS ON THE PERFORMANCE OF EMPIRICAL
ANALYSIS IN
THE LEGAL DECISION SUPPORT PROCESS, IN ORDER TO ELUCIDATE THE PRACTICAL
RELEVANCE AND
CHALLENGES OF USING BN IN THE CRIME DOMAIN.
CHAPTER 7
FORENSIC INVESTIGATION OF DIGITAL CRIMES IN HEALTHCARE APPLICATIONS 169
NOURHENE ELLOUZE, UNIVERSITY OF CARTHAGE, TUNISIA
SLIM REKHIS, UNIVERSITY OF CARTHAGE, TUNISIA
NOUREDDINE BOUDRIGA, UNIVERSITY OF CARTHAGE, TUNISIA
HEALTHCARE APPLICATIONS ARE INCREASINGLY BEING USED DUE TO THE SAFETY
AND CONVENIENCE
BROUGHT TO PATIENTS' LIFE AND HEALTHCARE PROFESSIONALS, RESPECTIVELY.
NEVERTHELESS, THE
USE OF WEAK AUTHENTICATION TECHNIQUES AND VULNERABLE COMMUNICATION
PROTOCOLS MAKES
THESE APPLICATIONS THREATENED BY SPECIFIC CLASSES OF SECURITY ATTACKS
AND E-CRIMES.
THE LATTER THREATEN THE PRIVACY, THE SAFETY AND EVEN THE LIFE OF THE
PERSONS USING THESE
APPLICATIONS, DUE TO THE FACT THAT THEY HANDLE SENSITIVE INFORMATION AND
IMPLEMENT
COMPLEX AND CRITICAL FEATURES. THIS CHAPTER FOCUSES ON POSTMORTEM
INVESTIGATION
OF CRIMES ON HEALTHCARE APPLICATIONS. AFTER CLASSIFYING CRIMES TARGETING
HEALTHCARE
APPLICATIONS, THE REQUIREMENTS FOR THE DESIGN OF APPROPRIATE POSTMORTEM
INVESTIGATION
SYSTEM, ARE DISCUSSED. A LITERATURE REVIEW OF PROPOSALS RELATED TO THE
INVESTIGATION OF
CRIMES IN HEALTHCARE APPLICATIONS TOGETHER WITH A DISCUSSION OF THE
ADVANCED ISSUES
ARE ALSO PROVIDED IN THIS CHAPTER.
SECTION 4
DENIAL OF SERVICE, CYBER-CRIME, AND INTRUSION DETECTION
MANAGEMENT
CHAPTER 8
DATA MINING ANALYTICS FOR CRIME SECURITY INVESTIGATION AND INTRUSION
DETECTION 212
BOUTHEINA FESSI, CN&S, UNIVERSITY OF CARTHAGE, TUNISIA
YACINE DJEMAIEL, CN&S, UNIVERSITY OF CARTHAGE, TUNISIA
NOUREDDINE BOUDRIGA, CN&S, UNIVERSITY OF CARTHAGE, TUNISIA
THIS CHAPTER PROVIDES A REVIEW ABOUT THE USEFULNESS OF APPLYING DATA
MINING TECHNIQUES
TO DETECT INTRUSION WITHIN DYNAMIC ENVIRONMENTS AND ITS CONTRIBUTION IN
DIGITAL
INVESTIGATION. NUMEROUS APPLICATIONS AND MODELS ARE DESCRIBED BASED ON
DATA MINING
ANALYTICS. THE CHAPTER ADDRESSES ALSO DIFFERENT REQUIREMENTS THAT SHOULD
BE FULFILLED
TO EFFICIENTLY PERFORM CYBER-CRIME INVESTIGATION BASED ON DATA MINING
ANALYTICS. IT
STATES, AT THE END, FUTURE RESEARCH DIRECTIONS RELATED TO CYBER-CRIME
INVESTIGATION THAT
COULD BE INVESTIGATED AND PRESENTS NEW TRENDS OF DATA MINING TECHNIQUES
THAT DEAL
WITH BIG DATA TO DETECT ATTACKS.
CHAPTER 9
AUTOMATED IDENTIFICATION OF CHILD ABUSE IN CHAT ROOMS BY USING DATA
MINING 245
MOHAMMADREZA KEYVANPOUR, ALZAHRA UNIVERSITY, IRAN
MOHAMMADREZA EBRAHIMI, CONCORDIA UNIVERSITY, CANADA
NECMIYE GENE NAYEBI, ECOLE DE TECHNOLOGIE SUPERIEURE (ETS), CANADA
OLGA ORMANDJIEVA, CONCORDIA UNIVERSITY, CANADA
CHING Y. SUEN, CONCORDIA UNIVERSITY, CANADA
PROVIDING A SAFE ENVIRONMENT FOR JUVENILES AND CHILDREN IN ONLINE SOCIAL
NETWORKS
IS CONSIDERED AS ONE OF THE MAJOR FACTORS OF IMPROVING PUBLIC SAFETY.
DUE TO THE
PREVALENCE OF THE ONLINE CONVERSATIONS, MITIGATING THE UNDESIRABLE
EFFECTS OF CHILD
ABUSE IN CYBER SPACE HAS BECOME INEVITABLE. USING AUTOMATIC WAYS TO
COMBAT
THIS KIND OF CRIME IS CHALLENGING AND DEMANDS EFFICIENT AND SCALABLE
DATA MINING
TECHNIQUES. THE PROBLEM CAN BE CASTED AS A COMBINATION OF TEXTUAL
PREPROCESSING IN
DATA/TEXT MINING AND PATTERN CLASSIFICATION IN MACHINE LEARNING. THIS
CHAPTER COVERS
DIFFERENT DATA MINING METHODS INCLUDING PREPROCESSING, FEATURE
EXTRACTION AND THE
POPULAR WAYS OF FEATURE ENRICHMENT THROUGH EXTRACTING SENTIMENTS AND
EMOTIONAL
FEATURES. A BRIEF TUTORIAL ON CLASSIFICATION ALGORITHMS IN THE DOMAIN OF
AUTOMATED
PREDATOR IDENTIFICATION IS ALSO PRESENTED THROUGH THE CHAPTER. FINALLY,
THE DISCUSSION
IS SUMMARIZED AND THE CHALLENGES AND OPEN ISSUES IN THIS APPLICATION
DOMAIN ARE
DISCUSSED.
CHAPTER 10
DATA MINING TECHNIQUES FOR DISTRIBUTED DENIAL OF SERVICE ATTACKS
DETECTION
IN THE INTERNET OF THINGS: A RESEARCH SURVEY 275
PHEEHA MACHAKA, DECISION SCIENCES DEPARTMENT, UNIVERSITY OF SOUTH
AFRICA, SOUTH AFRICA
FULUFHELO NELWAMONDO, MODELLING AND DIGITAL SCIENCE, COUNCIL FOR
SCIENTIFIC AND INDUSTRIAL RESEARCH, SOUTH AFRICA
THIS CHAPTER REVIEWS THE EVOLUTION OF THE TRADITIONAL INTERNET INTO THE
INTERNET OF
THINGS (IOT). THE CHARACTERISTICS AND APPLICATION OF THE IOT ARE ALSO
REVIEWED,
TOGETHER WITH ITS SECURITY CONCERNS IN TERMS OF DISTRIBUTED DENIAL OF
SERVICE ATTACKS.
THE CHAPTER FURTHER INVESTIGATES THE STATE-OF-THE-ART IN DATA MINING
TECHNIQUES FOR
DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACKS TARGETING THE VARIOUS
INFRASTRUCTURES.
THE CHAPTER EXPLORES THE CHARACTERISTICS AND PERVASIVENESS OF DDOS
ATTACKS. IT ALSO
EXPLORES THE MOTIVES, MECHANISMS AND TECHNIQUES USED TO EXECUTE A DDOS
ATTACK.
THE CHAPTER FURTHER INVESTIGATES THE CURRENT DATA MINING TECHNIQUES THAT
ARE USED TO
COMBAT AND DETECT THESE ATTACKS, THEIR ADVANTAGES AND DISADVANTAGES ARE
EXPLORED.
FUTURE DIRECTION OF THE RESEARCH IS ALSO PROVIDED.
CONCLUSION 335
COMPILATION OF REFERENCES 339
ABOUT THE CONTRIBUTORS 376
INDEX 383 |
| any_adam_object | 1 |
| author2 | Isafiade, Omowunmi E. 1982- Bagula, Antoine B. |
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| id | DE-604.BV044252892 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-20T06:37:54Z |
| institution | BVB |
| isbn | 9781522504641 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029657949 |
| oclc_num | 986503218 |
| open_access_boolean | |
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| physical | 1 Online-Ressource (xxiv, 386 Seiten) |
| psigel | ZDB-98-IGB ZDB-1-IGE ZDB-98-IGB FHD01_IGB_Kauf ZDB-98-IGB TUB_EBS_IGB |
| publishDate | 2016 |
| publishDateSearch | 2016 |
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| publisher | Information Science Reference, an imprint of IGI Global |
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| series2 | Advances in data mining and database management (ADMDM) book series Premier reference source |
| spelling | Data mining trends and applications in criminal science and investigations Omowunmi E. Isafiade (University of Cape Town, South Africa), Antoine B. Bagula (University of the Western Cape, South Africa) Hershey PA Information Science Reference, an imprint of IGI Global [2016] © 2016 1 Online-Ressource (xxiv, 386 Seiten) txt rdacontent c rdamedia cr rdacarrier Advances in data mining and database management (ADMDM) book series Premier reference source Isafiade, Omowunmi E. 1982- (DE-588)1116290863 edt Bagula, Antoine B. edt Erscheint auch als Druck-Ausgabe 978-1-5225-0463-4 Erscheint auch als Druck-Ausgabe 1-5225-0463-X http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-0463-4 Verlag URL des Erstveröffentlichers Volltext SWB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029657949&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Data mining trends and applications in criminal science and investigations |
| title | Data mining trends and applications in criminal science and investigations |
| title_auth | Data mining trends and applications in criminal science and investigations |
| title_exact_search | Data mining trends and applications in criminal science and investigations |
| title_full | Data mining trends and applications in criminal science and investigations Omowunmi E. Isafiade (University of Cape Town, South Africa), Antoine B. Bagula (University of the Western Cape, South Africa) |
| title_fullStr | Data mining trends and applications in criminal science and investigations Omowunmi E. Isafiade (University of Cape Town, South Africa), Antoine B. Bagula (University of the Western Cape, South Africa) |
| title_full_unstemmed | Data mining trends and applications in criminal science and investigations Omowunmi E. Isafiade (University of Cape Town, South Africa), Antoine B. Bagula (University of the Western Cape, South Africa) |
| title_short | Data mining trends and applications in criminal science and investigations |
| title_sort | data mining trends and applications in criminal science and investigations |
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