Aug 2026· International Journal of Data Science and Analysis· Vol 22· 0 citations· 72 references
TL;DR
This comprehensive review delves into integration of the FL with the AI-based ZTA for the malware detection and Prevention and presents the comparative analysis between the AI, FL, ZTA, IAM approaches, and the trends, challenges, limitations, and the future directions.
The proposed framework introduces several innovative features, such as federated learning with momentum-based optimization, adaptive differential privacy, trust verification via blockchain, and Byzantine-resilient aggregation, to enhance the security, scalability, and robustness of the system compared with traditional...
The growing complexity and frequency of cyberattacks have demonstrated the weaknesses of conventional IDPS, which are highly dependent on fixed rules and signature-based approaches. Artificial Intelligence (AI) has become a transformative solution to overcome these difficulties, allowing intrusion detection to be more...
P. Ramya, H. R., S. Rajathi et al.· 2026 2nd International Confe...· 0 citations
This work proposes an intelligent, lightweight Tiny LSTM–GRU hybrid IDS on the edge to monitor device-generated behavioral patterns in real time, with minimal computational and energy overhead, and proposes an adaptive FedProx-based weighted federated learning framework.
Emmanuel Udok, B. Stephen, U. Luke et al.· E3S Web of Conferences· 0 citations
This research hopes to alleviate some of these challenges by enabling collaborative model training across remote devices while assuring that confidential user data remains uncompromised and undisclosed and inspires service providers, vendors of devices and researchers to the utility of elevating mobile security.
A conceptual framework is proposed that combines detection, explanation, and orchestrated response in a continuous feedback loop that is suitable for zero trust and IoT-enabled critical-infrastructure environments that will allow for continuous retraining of the model.
Jayesh Dalmet· Journal of Digital Security...· 0 citations
This survey critically examines significant research contributions highlighting AI applications across intrusion detection, malware analysis, phishing detection, ransomware mitigation, distributed denial-of-service prevention, and network security and outlines prospective directions to advance the development of intell...
Muhammad Zahid Mehmood, Dr.Irshad Ahmed Sumra, Sobia Yaqoob· International journal for el...· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
