Handbook of Big Data Analytics and Forensics

Handbook of Big Data Analytics and Forensics

Choo, Kim-Kwang Raymond; Dehghantanha, Ali

Springer Nature Switzerland AG

12/2021

287

Dura

Inglês

9783030747527

15 a 20 dias

612

Descrição não disponível.
1. Big data analytics and forensics: an overview.- 2. Lot privacy, security and forensics challenges: an unmanned aerial vehicle (uav) case study.- 3. Detection of enumeration attacks in cloud environments using infrastructure log data.- 4.- Cyber threat attribution with multi-view heuristic analysis.- 5. Security of industrial cyberspace: fair clustering with linear time approximation.- 6. Adaptive neural trees for attack detection in cyber physical systems.- 7. Evaluating performance of scalable fair clustering machine learning techniques in detecting cyber-attacks in industrial control systems.- 8. Fuzzy bayesian learning for cyber threat hunting in industrial control systems.- 9. Cyber-attack detection in cyber-physical systems using supervised machine learning.- 10. Evaluation of scalable fair clustering machine learning methods for threat hunting in cyber-physical systems.- 11. Evaluation of supervised and unsupervised machine learning classifiers for mac os malware detection.- 12. Evaluation of machine learning algorithms on internet of things (iot) malware opcodes.- 13. Mac os x malware detection with supervised machine learning algorithms.- 14. Machine learning for osx malware detection.- 15. Hybrid analysis on credit card fraud detection using machine learning techniques.- 16. Mapping ckc model through nlp modelling for apt groups reports.- 17. Ransomware threat detection: a deep learning approach.- 18. Scalable fair clustering algorithm for internet of things malware classification.
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cyber threat;cyber security;privacy;big data;threat intelligence;machine learning;cyber forensics;intrusion detection;incident response;cyber defense;malware campaign detection;indicators of compromise;evidence correlation;data security