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Adversarial Attack Detection in Federated Learning Using Quantum Recurrent Neural Network
Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.Adversarial attacks in network systems manipulate data to deceive networks, impacting domains like image recognition and natural language processing. Attackers exploit algorithm weaknesses, creating misleading inputs that lead to inaccurate outcomes.
Venkat R. +7 more
wiley +1 more source
Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source
Hybrid Botnet Detection Mechanism
International Journal of Computer Applications, 2014 Botnets have emerged as one of the biggest threats to internet security in the recent years. They have confounded security researchers because of their mobile and secretive behavior. A Botnet is a network of zombie machines remotely controlled by a command server or a Botmaster.
openaire +1 more source
, 2014 In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide
Cova, Marco +2 more
core
Metaheuristic Optimization Algorithm for Vulnerability Detection in Web of Things Environment
Journal of Engineering, Volume 2026, Issue 1, 2026.The integration of the Web of Things with cloud computing platforms has significantly improved data sharing, analytics, and automation across smart environments. However, this interconnection also exposes devices and cloud infrastructures to severe security threats, including Trojans, ransomware, worms, and advanced malware.
Romil Rawat +2 more
wiley +1 more source
BotCatcher:botnet detection system based on deep learning
Tongxin xuebao, 2018 Machine learning technology has wide application in botnet detection.However,with the changes of the forms and command and control mechanisms of botnets,selecting features manually becomes increasingly difficult.To solve this problem,a botnet detection ...
Di WU, Binxing FANG, Xiang CUI, Qixu LIU
doaj +2 more sources
Pragmatic Study of Botnet Attack Detection In An IoT Environment [PDF]
E3S Web of ConferencesA comprehensive search for primary research published between 2014 and 2023 was carried across several databases. Studies that describe the application of machine learning (ML) and deep learning techniques for if they was carried out across several ...
Vennapureddy Rajasree, Srinivasulu T.
doaj +1 more source
Method of botnet network nodes detection base on communication similarity
网络与信息安全学报, 2018 At present,the botnet detection method mostly relies on the analysis of the network communication activity or the communication content.The former carries on the statistical analysis to the characteristic of the data flow,does not involve the content in ...
Yuquan JIN, Bin XIE, Yi ZHU
doaj +3 more sources
Multi-phase IRC Botnet and Botnet Behavior Detection Model
, 2015 Botnets are considered one of the most dangerous and serious security threats facing the networks and the Internet. Comparing with the other security threats, botnet members have the ability to be directed and controlled via C&C messages from the botmaster over common protocols such as IRC and HTTP, or even over covert and unknown applications.
Awadi, Aymen Hasan Rashid Al +1 more
openaire +2 more sources
Nepenthes Honeypots based Botnet Detection
, 2013 The numbers of the botnet attacks are increasing day by day and the detection of botnet spreading in the network has become very challenging. Bots are having specific characteristics in comparison of normal malware as they are controlled by the remote master server and usually dont show their behavior like normal malware until they dont receive any ...
Kumar, S. +3 more
openaire +2 more sources