Results 31 to 40 of about 958 (168)

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

Survey on Visualization of Information Diffusion over Networks

Computer Graphics Forum, EarlyView.
Abstract Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision‐making as well as ...
T. Baumgartl, M. Sondag, V. Filipov, M. Tuscher, S. Rajendran, S. Miksch, D. Archambault, A. Arleo, T. von Landesberger   +8 more
wiley   +1 more source

Safeguarding Online Research in Eating Disorders Against Fraud: Increasing Risks and Practical Recommendations

International Journal of Eating Disorders, Volume 59, Issue 7, Page 1451-1468, July 2026.
ABSTRACT Objective Recent growth of online research has been accompanied by an increase in reports of fraudulent participants, which can significantly comprise research validity. Drawing from our experience using Qualtrics with open recruitment, existing literature, and emerging studies in eating disorders (ED), we outline the risk and provide simple ...
Jamie‐Lee Pennesi, Mia L. Pellizzer, Tracey D. Wade   +2 more
wiley   +1 more source

Enhancing Botnet Detection in Network Security Using Profile Hidden Markov Models

Applied Sciences
A botnet is a network of compromised computer systems, or bots, remotely controlled by an attacker through bot controllers. This covert network poses a threat through large-scale cyber attacks, including phishing, distributed denial of service (DDoS ...
Rucha Mannikar, Fabio Di Troia
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

Peer-to-peer botnets: exploring behavioural characteristics and machine/deep learning-based detection

EURASIP Journal on Information Security
The orientation of emerging technologies on the Internet is moving toward decentralisation. Botnets have always been one of the biggest threats to Internet security, and botmasters have adopted the robust concept of decentralisation to develop and ...
Arkan Hammoodi Hasan Kabla, Achmad Husni Thamrin, Mohammed Anbar, Selvakumar Manickam, Shankar Karuppayah   +4 more
doaj   +1 more source

Analysis and Characterization of IoT Malware Command and Control Communication

Telfor Journal, 2020
The emergence of Mirai botnet in 2016 took worldwide research teams by surprise, proving that a large number of low-performance IoT devices could be hacked and used for illegal purposes, causing extremely voluminous DDoS attacks.
Đ. D. Jovanović, P. V. Vuletić
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

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

Improving spam botnet detection through convolutional model and geolocation feature enhancement in a novel three-class classification task

International Journal of Intelligent Networks
Botnet detection remains a critical and challenging area in the field of information security, primarily due to the intricate architectures and sophisticated attack mechanisms employed by botnets.
Florentino Benedictus, Muhammad Aidiel Rachman Putra, Tohari Ahmad, Choiru Za’in, Tony de Souza-Daw   +4 more
doaj   +1 more source