Results 11 to 20 of about 7,753,315 (190)
Real-Time Bot Detection from Twitter Using the Twitterbot+ Framework [PDF]
Journal of Universal Computer Science, 2020 Nowadays, bot detection from Twitter attracts the attention of several researchers around the world. Different bot detection approaches have been proposed as a result of these research efforts.
Kheir Daouadi, Rim Rebaï, Ikram Amous
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CB-MTE: Social Bot Detection via Multi-Source Heterogeneous Feature Fusion [PDF]
SensorsSocial bots increasingly mimic real users and collaborate in large-scale influence campaigns, distorting public perception and making their detection both critical and challenging. Traditional bot detection methods, constrained by single-source features,
Meng Cheng +4 more
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BotBuster: Multi-platform Bot Detection Using A Mixture of Experts [PDF]
International Conference on Web and Social Media, 2022 Despite rapid development, current bot detection models still face challenges in dealing with incomplete data and cross-platform applications. In this paper, we propose BotBuster, a social bot detector built with the concept of a mixture of experts ...
L. Ng, Kathleen M. Carley
semanticscholar +2 more sources
Journal of King Saud University: Computer and Information Sciences, 2022 In this cyber era, botnets have been a serious threat to computer network security in that they can infect computers connected to a network through malicious applications known as malware.
Dandy Pramana Hostiadi, Tohari Ahmad
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Detection of randomized bot command and control traffic on an end-point host [PDF]
Alexandria Engineering Journal, 2016 Bots are malicious software entities that unobtrusively infect machines and silently engage in activities ranging from data stealing to cyber warfare. Most recent bot detection methods rely on regularity of bot command and control (C&C) traffic for bot ...
B. Soniya, M. Wilscy
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Intention embedding method based social bot detection [PDF]
Tongxin xuebaoArtificial intelligence generated content technology has significantly enhanced the disguise capabilities of social bots, presenting new challenges to existing bot detection methods.
NIU Hongfeng +3 more
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Identifying and Analyzing Bot-Generated Responses in Online Health Care Surveys: Methodological Study [PDF]
JMIR Medical InformaticsBackgroundThe increasing reliance on online surveys for collecting patient-reported feedback for health care research has led to growing concerns over fraudulent responses generated by bots.
Emily Hamovitch +2 more
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BotRGCN: Twitter bot detection with relational graph convolutional networks [PDF]
International Conference on Advances in Social Networks Analysis and Mining, 2021 Twitter bot detection is an important and challenging task. Existing bot detection measures fail to address the challenge of community and disguise, falling short of detecting bots that disguise as genuine users and attack collectively.
Shangbin Feng +3 more
semanticscholar +1 more source
TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark [PDF]
International Conference on Information and Knowledge Management, 2021 Twitter has become a vital social media platform while an ample amount of malicious Twitter bots exist and induce undesirable social effects. Successful Twitter bot detection proposals are generally supervised, which rely heavily on large-scale datasets.
Shangbin Feng +4 more
semanticscholar +1 more source
Applied Sciences, 2022 Twitter, as a popular social network, has been targeted by different bot attacks. Detecting social bots is a challenging task, due to their evolving capacity to avoid detection. Extensive research efforts have proposed different techniques and approaches
Eiman Alothali +3 more
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