.png)
Integration of Machine Learning Models for Real-Time Detection of Advanced Persistent Threats and Network Intrusions
Dr. Vignesh Thangathurai, Dr. T. S. Karthik, Nisha Rathore, Dr. Sarangam Kodati
Indexed In: google scholar
Release Date: 10/03/2025 | Copyright:© 2025 | Pages: 446
DOI: 10.71443/9789349552388
ISBN10: 9349552388 | ISBN13: 9789349552388
This research explores the integration of machine learning (ML) models for real-time detection of Advanced Persistent Threats (APTs) and network intrusions. By leveraging supervised and unsupervised learning techniques, including anomaly detection, deep learning, and ensemble methods, the study aims to enhance cybersecurity defenses. The proposed framework incorporates feature selection, data preprocessing, and adaptive learning strategies to improve detection accuracy and reduce false positives. Real-time threat analysis is achieved through scalable ML pipelines, ensuring rapid response to evolving cyber threats. This approach enhances network security by providing proactive intrusion detection, mitigating risks, and strengthening overall cyber defense mechanisms against sophisticated attacks.
The integration of machine learning (ML) models for real-time detection of Advanced Persistent Threats (APTs) and network intrusions enhances cybersecurity by identifying sophisticated attack patterns. ML techniques, including anomaly detection, supervised classification, and deep learning, analyze network traffic, user behavior, and system logs to detect deviations indicative of cyber threats. Hybrid approaches, combining signature-based and behavior-based detection, improve accuracy and reduce false positives. Real-time processing through online learning and adaptive models ensures continuous monitoring and rapid response. Leveraging ML for APT and intrusion detection strengthens threat intelligence, mitigates risks, and enhances automated security defenses in dynamic network environments.
Vignesh Thangathurai received M. Tech (Computer and Information Technology Engineering) degree from Manonmaniam Sundaranar University, Tirunelveli, India in the year 2011. He also, obtained his doctoral degree (Computer and Information Technology Engineering) from Manonmaniam Sundaranar University, Tirunelveli, India in the year of 2019. He has more than 13 years of teaching experience in various prestigious universities such as SRM Institute of Science and Technology, Chennai, India, Chandigarh University, Mohali, Punjab., etc. and 3 years’ industry experience. Currently, He is working as a Professor in the Department of B.Tech (Computer Science and Business Systems), in Panimalar Engineering College, Chennai. He has published 53 research articles in reputed International journals and conferences. His research area includes Computer Vision, Satellite Image processing and Soft Computing Research and Machine Learning and Deep Learning Techniques. He is a lifetime member of ISTE, IAENG, and IACSIT.
T. S. KARTHIK is currently working as Associate Professor in the Department of Electronics and Communication Engineering, at SRMIST, Kattankulathur, TamilNadu. His research interests include Computer architecture with an emphasis on memory systems and the three-dimension architecture; Algorithmic modeling, process variations aware design; CAD tools Programming, Embedded systems, IOT/NLP and Nanotechnology. He received his Ph.D. in the Faculty of Information & Communication under the Department of Electronics & Communication Engineering from College of Engineering Guindy Campus, Anna University, Chennai in 2015. He made out outstanding contributions in the area of Three-Dimensional Integrated circuits (3D-IC’S) and Clocking which are applicable to the analytical gate area model it drives to transistor sizing and leads to very minimal gate area. The findings had immediate implications in studies that detect the defects faster, variation in their delay, sampling their limits, accuracy in estimating the vital parameters for fabrication. Recently, honored Post doctoral Fellowship from Unifacvest University, Brazil in the Digital Cognitive Computing in Industry 5.0. He contributed more than 75 International Journal, 11 National/International Conference, 9 Patents, and served as Chief editor for various Book chapter. He authored a book on Digital Electronics: Theory and Practice and Internet of Things-Case Study and its Applications published recently. Chaired a session & Resource person in various international conferences and served as expert member for External Academic Audit Inspection in various Autonomous bodies. He received awards from several organizations in recognition of her academic and research work in the products and their Innovation Ideas. Interacting with industries for Joint research activities in the technical chapters and society.
Nisha Rathore is an Assistant Professor at Amity School of Engineering and Technology, Amity University Chhattisgarh, Raipur. With a distinguished academic background in Computer Science and Engineering, including a B.Tech. from Pranveer Singh Institute of Technology, Kanpur, an M.Tech. from National Institute of Technology, Patna, and enrolled as Ph.D. scholar at IIT (ISM) Dhanbad, Nisha has established herself as a leading expert in her field. Her impressive credentials are complemented by a slew of achievements, including GATE and UGC-NET success, numerous research publications, a book, multiple book chapters, and three patents. Her research interests span brain-computer interface, soft computing, computer networks, fuzzy logic, and machine learning. As a member of IAENG and the Institutional Innovation Council, Nisha actively promotes computer science education and innovation. With her self-help book, 'The Paradise of Ultimate Happiness,' Nisha extends her expertise beyond academics, empowering students to prioritize their well-being and happiness.
Sarangam Kodati is currently working as Associate Professor in the Department of Information Technology at CVR College of Engineering, Mangalpally, Telangana, India. He received his B.Tech degree Computer Science and Engineering JNTU graduate from VNR VJIET, M.Tech (Computer Science) from JNTU – CEH (Autonomous) Hyderabad and Ph.D degree in Computer Science and Engineering from Sri Satya Sai University of Technology and Medical Science, Sehore, Bhopal, Madhya Pradesh. He has more than 10 years of teaching experience and more than 4 years of Research Experience. Published more than 50 papers in reputed Journals and Conferences. He has Published more than 10 Books and Book Chapters His fields of interest include Data Mining, Machine Learning, Internet of Things and Wireless Mobile Ad hoc Networks.