Results 31 to 40 of about 306 (121)

Stochastic Modeling of IoT Botnet Spread: A Short Survey on Mobile Malware Spread Modeling

IEEE Access, 2020
The Internet of Things (IoT) devices are being widely deployed and have been targeted and victimized by malware attacks. The mathematical modelling for an accurate prediction of malicious spreads of botnets across IoT networks is of great importance ...
Arash Mahboubi, Seyit Camtepe, Keyvan Ansari   +2 more
doaj   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

Machine Learning-Based IoT-Botnet Attack Detection with Sequential Architecture

Sensors, 2020
With the rapid development and popularization of Internet of Things (IoT) devices, an increasing number of cyber-attacks are targeting such devices. It was said that most of the attacks in IoT environments are botnet-based attacks.
Yan Naung Soe, Yaokai Feng, Paulus Insap Santosa, Rudy Hartanto, Kouichi Sakurai   +4 more
doaj   +1 more source

Graph‐Based Generative Adversarial Network for Adaptive IoT Intrusion Detection

Engineering Reports, Volume 8, Issue 8, August 2026.
The study introduces a hybrid graph‐based generative adversarial network (G‐GAN) that integrates adversarial learning with graph attention mechanisms to enhance intrusion detection in IoT environments. G‐GAN significantly improves accuracy and adaptability by reducing false alarms and detecting emerging threats in dynamic, heterogeneous IoT networks ...
Meshari H. Alanazi, Aabid A. Mir, Asma A. Alhashmi, Faris Alanazi, Mohammad N. Alanazi, Majid Ali Nawaz, Yahia Said, Abdulbasit A. Darem   +7 more
wiley   +1 more source

IoT Botnet Detection Using Autoencoders and Decision Trees

Jurnal Sisfokom, 2023
The use of IoT devices has grown rapidly, leading to an increase in cyber attacks that pose greater security and privacy threats than ever before. One such threat is botnet attacks on IoT devices.
Susanto Susanto, M. Agus Syamsul Arifin, Harma Oktafia Lingga Wijaya   +2 more
doaj   +1 more source

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

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

Deep Learning-Based Intrusion Detection System for Detecting IoT Botnet Attacks: A Review

IEEE Access
The proliferation of Internet of Things (IoT) devices has brought about an increased threat of botnet attacks, necessitating robust security measures. In response to this evolving landscape, deep learning (DL)-based intrusion detection systems (IDS) have
Tamara Al-Shurbaji, Mohammed Anbar, Selvakumar Manickam, Iznan H Hasbullah, Nadia Alfriehat, Basim Ahmad Alabsi, Ahmad Reda Alzighaibi, Hasan Hashim   +7 more
doaj   +1 more source

Botnet Defense System: Concept, Design, and Basic Strategy

Information, 2020
This paper proposes a new kind of cyber-security system, named Botnet Defense System (BDS), which defends an Internet of Things (IoT) system against malicious botnets. The concept of BDS is “Fight fire with fire”.
Shingo Yamaguchi
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