Handbook of AI-Driven Threat Detection and Prevention (eBook, PDF)

A Holistic Approach to Security
Redaktion: Bhambri, Pankaj; Anand, A. Jose

• Format: PDF

Produktbeschreibung

In today's digital age, companies need to adopt cutting-edge artificial intelligence solutions to effectively detect and counter potential threats. This handbook brings together a team of experts to discuss insights on proactive strategies, threat mitigation techniques, and comprehensive tactics for safeguarding sensitive data.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 388
• Erscheinungstermin: 12. Juni 2025
• Englisch
• ISBN-13: 9781040355558
• Artikelnr.: 73919686

Autorenporträt

Dr. Pankaj Bhambri is affiliated with the Department of Information Technology at Guru Nanak Dev Engineering College in Ludhiana. He fulfills the role of the Convener for his Departmental Board of Studies. He possesses nearly two decades of teaching experience. He is an active member of IE India, ISTE New Delhi, IIIE Navi Mumbai, IETE New Delhi, and CSI Mumbai. He has contributed to the various research activities while publishing articles in the renowned SCIE and Scopus journals and conference proceedings. He has also published several international patents. Dr. Bhambri has garnered extensive experience in the realm of academic publishing, having served as an editor/author for a multitude of books in collaboration with esteemed publishing houses. Dr. Bhambri has been honored with several prestigious accolades, including the ISTE Best Teacher Award in 2023 and 2022, the I2OR National Award in 2020, the Green ThinkerZ Top 100 International Distinguished Educators award in 2020, the I2OR Outstanding Educator Award in 2019, the SAA Distinguished Alumni Award in 2012, the CIPS Rashtriya Rattan Award in 2008, the LCHC Best Teacher Award in 2007, and numerous other commendations from various government and nonprofit organizations. He has provided guidance and oversight for numerous research projects and dissertations at the postgraduate and Ph.D. levels. He has successfully organized a diverse range of educational programs, securing financial backing from esteemed institutions such as the AICTE, the TEQIP, among others. Dr. Bhambri's areas of interest encompass machine learning, bioinformatics, wireless sensor networks, and network security. Dr. A. Jose Anand is currently associated with Halifax Regional Center for Education, Halifax, Nova Scotia, Canada. Earlier, he had worked as a professor at the Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, Tamil Nadu, India. He has one year of industrial experience, 24 years of teaching experience, and one year of experience as an assistant for Halifax Regional Center for Education at Saint Mary's Elementary School, Halifax, Nova Scotia, Canada. He has presented several papers at national and international conferences. He has published several papers in national and international journals and has published books for polytechnic and engineering subjects. He is a member of CSI, IEI, IET, IETE, ISTE, INS, QCFI, and EWB. His current research interests are wireless sensor networks, embedded systems, Internet of Things, machine learning, and image processing.

Inhaltsangabe

1. Understanding AI and Machine Learning in Security. 2. Data Collection
and Preprocessing for Security. 3. Feature Engineering for Threat
Detection. 4. Anomaly Detection with Artificial Intelligence. 5.
Signature-based Security in Wireless Communication. 6. Behavioral Analysis
for Threat Detection. 7. Network Security with Artificial Intelligence. 8.
Endpoint Security and Artificial Intelligence in the Financial Sector. 9.
Cloud Security and Artificial Intelligence. 10. Adversarial Attacks on AI
Security Systems. 11. Ethical Considerations and Privacy in Artificial
Intelligence Powered Security Systems. 12. Artificial Intelligence in
Financial Fraud Detection. 13. Graph-based Intelligent Cyber Threat
Detection System. 14. Future Trends in Artificial Intelligence Driven
Security. 15. Enhancing Cybersecurity with Distributed Models and Sparse
Mixture of Experts. 16. Anomaly Detection in SIEM Data: User Behavior
Analysis with Artificial Intelligence. 17. AI-Driven Security System for
Biometric Surveillance. 18. AI-Powered Predictive Analysis for Proactive
Cyber Defense. 19. Deep Learning Techniques for Intrusion Detection in
Critical Infrastructure. 20. Quantum Computing and AI Synergies:
Strengthening Cybersecurity Resilience. 21. Integrating AI with Blockchain
for Decentralized Security and Threat Prevention.