Results 11 to 20 of about 14,194 (229)
Botnet detection using social graph analysis [PDF]
2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2014 Signature-based botnet detection methods identify botnets by recognizing Command and Control (C\&C) traffic and can be ineffective for botnets that use new and sophisticate mechanisms for such communications. To address these limitations, we propose a novel botnet detection method that analyzes the social relationships among nodes.
Wang, Jing, Paschalidis, Ioannis Ch.
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Sonification of Network Traffic for Detecting and Learning About Botnet Behavior [PDF]
IEEE Access, 2018 Today's computer networks are under increasing threat from malicious activity. Botnets (networks of remotely controlled computers, or “bots”) operate in such a way that their activity superficially resembles normal network traffic which ...
Mohamed Debashi, Paul Vickers
doaj +3 more sources
Analyzing IDS botnets detection
, 2018 In a world increasingly connected with equipment permanently attached, the risk of cybersecurity had rise. Among the various vulnerabilities and forms of exploitation, the Botnets are those being addressed in this work. The number of botnets related infections has grown critically and, due to botnets’ increased capacity and potential use for future ...
Kahe Henrique Binda
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Measurement: Sensors, 2023 With various malware, botnets are the legitimate risk increasing against cybersecurity providing criminal operations like malware dispersal, distributed denial of service attacks, fraud clicking, phishing, and identification of theft. Existing techniques
Sathiyandrakumar Srinivasan +1 more
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International Journal of Advanced Research in Science, Communication and Technology, 2022 Android, being the most widespread mobile operating systems is increasingly becoming a target for malware. Malicious apps designed to turn mobile devices into bots that may form part of a larger botnet have become quite common, thus posing a serious threat. This calls for more effective methods to detect botnets on the Android platform.
null Prof. (Mrs) Mayuri Khade +4 more
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Adaptive secure malware efficient machine learning algorithm for healthcare data
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed +8 more
wiley +1 more source
Large-scale Malicious P2P Botnet Node Detection Technology Based on Challenge Strategy [PDF]
Jisuanji gongcheng, 2016 Traditional botnet detection technologies mainly detect botnet nodes in specified area network on the hosts or the border of gateway export,which have small scale and low detection efficiency.To efficiently execute Peer-to-Peer(P2P) network botnet node ...
LI Jing,YAO Yiyang,LU Xindai,QIAO Yong
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IEEE Access, 2023 Botnet detection in a cloud-aided Internet of Things (IoT) environment is a tedious process, meanwhile, IoT gadgets are extremely vulnerable to attacks due to poor security practices and limited computing resources.
Latifah Almuqren +5 more
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Botnet Detection Approach Using Graph-Based Machine Learning
IEEE Access, 2021 Detecting botnet threats has been an ongoing research endeavor. Machine Learning (ML) techniques have been widely used for botnet detection with flow-based features.
Afnan Alharbi, Khalid Alsubhi
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International Journal for Research in Applied Science and Engineering Technology, 2023 Abstract: Android, being the most widespread mobile operating systems is in- creasingly becoming a target for malware. Malicious apps designed to turn mobile devices into bots that may form part of a larger botnet have become quite common, thus posing a serious threat.
Pranay Jadhav +4 more
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