Results 41 to 50 of about 1,396 (174)

A Comprehensive Systematic Review of Cyber‐Physical Systems Security: Threats, Challenges, and Defense in ICS/OT Environments

Engineering Reports, Volume 8, Issue 7, July 2026.
Overview of the paper organization, illustrating the hierarchical structure of cybersecurity domains in ICS and CPS, including attack analysis, security approaches, offensive tactics, career guidance, and concluding discussions. ABSTRACT The convergence of operational technology (OT) with IP‐based information systems has exposed industrial control ...
M. A. Khalifa, Ahmad Taher Azar, Walid El‐Shafai   +2 more
wiley   +1 more source

ELBA-IoT: An Ensemble Learning Model for Botnet Attack Detection in IoT Networks

Journal of Sensor and Actuator Networks, 2022
Due to the prompt expansion and development of intelligent systems and autonomous, energy-aware sensing devices, the Internet of Things (IoT) has remarkably grown and obstructed nearly all applications in our daily life.
Qasem Abu Al-Haija, Mu’awya Al-Dala’ien   +1 more
doaj   +1 more source

Graph–Time IoT IDS: Requirement‐Aligned Impact Evaluation

Engineering Reports, Volume 8, Issue 7, July 2026.
A multi‐view intrusion detection framework (IMPACT‐MVG) combines temporal behavior modeling and graph‐based interaction analysis to detect IoT network attacks. Impact‐centric evaluation using the ICSec score shows that the approach reduces operational damage from intrusions while maintaining efficient, explainable, and privacy‐aware security monitoring.
Kumkum Dubey, Isha Batra, Abhishek Bajpai, Arun Malik, Mohammed Ali Alshara, Tariqullah Jan, Naveed Ahmad, Ruhul Amin Khalil   +7 more
wiley   +1 more source

Design of Universal Botnet Experimental Platform [PDF]

Jisuanji gongcheng, 2018
Botnet research in open networks has many drawbacks,such as uncontrollable process,difficult to scale,and unable to repeat experiments.In order to solve this problem,the requirement and design principle of the universal botnet experimental platform with ...
LI Dawei
doaj   +1 more source

GA‐ANN: An Efficient Hybrid Deep Learning Scheme for Network Intrusion Detection in IoT

SECURITY AND PRIVACY, Volume 9, Issue 4, July/August 2026.
ABSTRACT Intrusion detection systems (IDS) are critical to the security of the dynamic internet of things (IoT) environment. The integration of Artificial Intelligence (AI) into IDS has substantially improved network security. Particularly, deep learning techniques have shown strong potential in addressing IoT security challenges.
Naveed Ahmed, M. Siraj Rathore, Azhar Mahmood, Muhammad Daniyal, Md Asri Ngadi   +4 more
wiley   +1 more source

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

A Systematic Literature Review: Classifying IoT Botnet Data Features Based on Its Lifecycle

IEEE Access
As the Internet of Things (IoT) becomes increasingly indispensable across various domains, the connectivity between humans, machines, and devices intensifies.
Shihao Liu, Fariza Fauzi, Ven Jyn Kok
doaj   +1 more source

OntoLogX: Ontology‐Guided Knowledge Graph Extraction From Cybersecurity Logs With Large Language Models

Advanced Intelligent Systems, Volume 8, Issue 6, June 2026.
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti, Idilio Drago, Anisa Rula, Devis Bianchini, Federico Cerutti   +4 more
wiley   +1 more source

Botnet Detection Using On-line Clustering with Pursuit Reinforcement Competitive Learning (PRCL)

Emitter: International Journal of Engineering Technology, 2018
Botnet is a malicious software that often occurs at this time, and can perform malicious activities, such as DDoS, spamming, phishing, keylogging, clickfraud, steal personal information and important data.
Yesta Medya Mahardhika, Amang Sudarsono, Ali Ridho Barakbah   +2 more
doaj   +1 more source

Semantic Evolution and Consistency Learning for Robust Malicious Network Traffic Detection

Engineering Reports, Volume 8, Issue 6, June 2026.
This paper proposes a semantic evolution and consistency network (SECN) for malicious traffic detection, modeling attack behaviors as temporally evolving semantics. By integrating dual‐level temporal representation and semantic consistency constraints, SECN achieves robust detection and strong generalization under encrypted, cross‐dataset, and unknown ...
Jing Yang, Wei Tan
wiley   +1 more source