Function Call Graphs Versus Machine Learning for Malware Detection

Abstract

Includes index. Intro; Preface; Organisation; Target Audience; Suggested Instructor Use; Acknowledgements; Contents; Part I Introduction and State-of-the-art; Review into State of the Art of Vulnerability Assessment using Artificial Intelligence; 1 Introduction; 1.1 Importance of Vulnerability Assessment; 1.2 Motivation; 2 Manual Vulnerability Assessment; 2.1 Example; 2.2 Drawbacks and Challenges of Manual Techniques; 2.3 Tools and Frameworks; 2.4 Patent Literature; 2.5 Drawbacks and Challenges of Assistive Techniques; 3 Research in Artificial Intelligence for Vulnerability Assessment; 3.1 Literature Review 3.2 Knowledge Gaps and Recommendations4 Conclusion; 5 Questions; References; A Survey of Machine Learning Algorithms and Their Application in Information Security; 1 Introduction; 2 Hidden Markov Models; 2.1 Overview of Hidden Markov Models; 2.2 Security Applications of HMMs; 3 Profile Hidden Markov Models; 3.1 Overview of Profile Hidden Markov Models; 3.2 Security Applications of PHMMs; 4 Principal Component Analysis; 4.1 Overview of Principal Component Analysis; 4.2 Security Applications of PCA; 5 Support Vector Machines; 5.1 Overview of Support Vector Machines 5.2 Security Applications of SVMs6 Clustering; 6.1 Overview of Clustering; 6.2 Security Applications of Clustering; 7 Vector Quantization; 7.1 Security Applications of VQ; 8 Linear Discriminant Analysis; 8.1 Security Applications of LDA; 9 k Nearest Neighbour; 9.1 Security Applications of k`3́9`42`""̇613A``45`47`""603A-NN; 10 Random Forests; 10.1 Security Applications of RFs; 11 Boosting; 11.1 Security Applications of Boosting; 12 Conclusion; 13 Questions; References; Part II Vulnerability Assessment Frameworks; Vulnerability Assessment of Cyber Security for SCADA Systems; 1 Introduction 2 SCADA Systems3 Detecting Assets; 3.1 Existing Tools; 4 Vulnerabilities and Threats; 4.1 Vulnerabilities of SCADA Systems; 4.2 Threats of SCADA Systems; 5 Mitigation; 5.1 Cyber Security Risk Assessment Methods for SCADA Systems; 5.2 Countermeasures; 6 Privacy Issues in SCADA Systems; 7 Conclusions; 8 Questions; References; A Predictive Model for Risk and Trust Assessment in Cloud Computing: Taxonomy and Analysis for Attack Pattern Detection; 1 Introduction; 2 Vulnerability: An Overview; 2.1 Definition of Vulnerability; 2.2 Vulnerabilities in Cloud Computing 3 Trust Assessment Models in Cloud Computing3.1 Decision Models; 3.2 Evaluation Models; 4 Trust Assessment Information Sources in Cloud Computing; 4.1 Direct Interaction; 4.2 Indirect Interaction; 4.3 Cloud Service Provider Declarations; 4.4 Third-Party Assessment; 5 Trust Dimensions in Cloud Computing; 5.1 Multi-criteria; 5.2 Context; 5.3 Personalisation; 5.4 (De)Centralised Trust Assessment; 5.5 Adaptability; 5.6 Credibility; 5.7 Trust Dynamics; 6 Analysis of Trust Assessment Frameworks in Cloud Computing; 7 Related Detection Approaches; 7.1 Intrusion Detection System