Results 61 to 70 of about 21,088 (211)

Analysis of Encrypted Malicious Traffic

, 2019
In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation and communication. Due to the volume of legitimate encrypted data, encrypted malicious traffic resembles benign traffic.
openaire   +2 more sources

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, Volume 14, Issue 3, Page 1431-1455, March 2026.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Federated Learning and 5G/6G‐Based Internet of Medical Things (IoMT): Applications, Key Enabling Technologies, Open Issues and Future Research Directions

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.
This review examines the integration of federated learning (FL) in the Internet of Medical Things (IoMT), enhanced by 5G/6G technologies, to improve healthcare systems with decentralized data processing, enhanced privacy, reduced latency, and efficient resource utilization, while addressing emerging challenges and future research directions.
Abdul Ahad, Kazi Istiaque Ahmed, Farhan Ullah, Muhammad Aman Sheikh, Mohammad Tahir, Mohammad Hayajneh, Ivan Miguel Pires   +6 more
wiley   +1 more source

The application and research of machine learning in malicious encrypted traffic detection

Dianzi Jishu Yingyong
With the widespread use of encrypted communication, malicious attackers increasingly exploit encrypted traffic to conceal their activities, posing challenges to traditional signature-based and rule-based detection methods.
Tian Rui, Zhang Yaqin, Dong Wei, Li Zhicheng, Feng Zhi   +4 more
doaj   +1 more source

A new dynamic security defense system based on TCP_REPAIR and deep learning

Journal of Cloud Computing: Advances, Systems and Applications, 2023
Honeypot is an active defense mechanism, which attracts attackers to interact with virtual resources in the honeypot mainly by simulating real working scenarios and deploying decoy targets, so as to prevent real resources from being damaged and collect ...
Jianxun Tang, Mingsong Chen, Haoyu Chen, Shenqi Zhao, Yu Huang   +4 more
doaj   +1 more source

A cybersecurity risk analysis framework for systems with artificial intelligence components

International Transactions in Operational Research, Volume 33, Issue 2, Page 798-825, March 2026.
Abstract The introduction of the European Union Artificial Intelligence (AI) Act, the NIST AI Risk Management Framework, and related international norms and policy documents demand a better understanding and implementation of novel risk analysis issues when facing systems with AI components: dealing with new AI‐related impacts; incorporating AI‐based ...
J.M. Camacho, A. Couce‐Vieira, D. Arroyo, D.R. Insua   +3 more
wiley   +1 more source

A Machine Learning Framework for Detecting and Preventing Cyber‐Attacks in Industrial Cyber‐Physical Systems

Engineering Reports, Volume 8, Issue 1, January 2026.
Proposed cyber physical system security framework. ABSTRACT The increasing adoption of cyber‐physical systems (CPS) in Industry 4.0 has heightened vulnerability to cyber threats. This study proposes a machine learning–based intrusion detection framework, DBID‐Net, to effectively identify and prevent attacks in CPS environments. The framework integrates
Anurag Sinha, Rejuwan Shamim, Mihika Mahendra, Trupti Mohota, G. Madhukar Rao, Mohammad Nadeem Ahmed, Mohammad Rashid Hussain, Satyam Solanki, Tanish Ranjan, Bhaskar, Mini Kumari, Karan Dixit, Vyom Modi, Syed Immamul Ansarullah, Mohd Asif Shah   +14 more
wiley   +1 more source

Efficacy Improvement of Anomaly Detection by Using Intelligence Sharing Scheme

Applied Sciences, 2019
Computer networks are facing threats of ever-increasing frequency and sophistication. Encryption is becoming the norm in both legitimate and malicious network traffic.
Muhammad Tahir, Mingchu Li, Naeem Ayoub, Muhammad Aamir   +3 more
doaj   +1 more source

Exploiting Vision Transformer and Ensemble Learning for Advanced Malware Classification

Engineering Reports, Volume 8, Issue 1, January 2026.
Overview of the proposed RF–ViT ensemble for multi‐class malware classification. Textual (BoW/byte‐frequency) and visual representations are combined via a product rule, achieving improved accuracy and robustness over individual models. ABSTRACT Malware remains a significant concern for modern digital systems, increasing the need for reliable and ...
Fadi Makarem, Rida El Chall, Abed Ellatif Samhat, Khouloud Samrouth, Nader Bakir   +4 more
wiley   +1 more source

RRF‐IPS: A Real‐Time Reputation‐Based Intrusion Prevention System

Engineering Reports, Volume 8, Issue 1, January 2026.
RRF‐IPS: A Real‐Time Reputation‐Based Intrusion Prevention System. ABSTRACT With the rapid development of technologies such as cloud computing and the Internet of Things, organizations face the thorny reality that network attacks are becoming increasingly diverse, covert, and intelligent.
Zhenghao Qian, Fengzheng Liu, Mingdong He, Bo Li, Xuewu Li, Chuangye Zhao, Gehua Fu, Yifan Hu   +7 more
wiley   +1 more source