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Keyword

botnet detection

Description: Botnet detection is the identification of compromised devices or malicious network activity associated with botnets, typically in cybersecurity monitoring.
OpenAlex ID: keywords/botnet-detection
Towards the development of realistic botnet dataset in the Internet of Things for network forensic analytics: Bot-IoT dataset
2019 · Nickolaos Koroniotis, Nour Moustafa, et al. · Future Generation Computer Systems · 1,968
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BotMiner: clustering analysis of network traffic for protocol- and structure-independent botnet detection
2008 · Guofei Gu, Roberto Perdisci, et al. · Journal of Bioresource Management · 1,033
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An empirical comparison of botnet detection methods
2014 · S. García, M. Grill, et al. · Computers & Security · 959
BotHunter: detecting malware infection through IDS-driven dialog correlation
2007 · Guofei Gu, Phillip Porras, et al. · 703
An Ensemble Intrusion Detection Technique Based on Proposed Statistical Flow Features for Protecting Network Traffic of Internet of Things
2018 · Nour Moustafa, Benjamin Turnbull, et al. · IEEE Internet of Things Journal · 584
An Overview of IP Flow-Based Intrusion Detection
2010 · Anna Sperotto, Gregor Schaffrath, et al. · IEEE Communications Surveys & Tutorials · 466
From throw-away traffic to bots: detecting the rise of DGA-based malware
2012 · Manos Antonakakis, Roberto Perdisci, et al. · 430
A Survey of Botnet and Botnet Detection
2009 · Maryam Feily, Alireza Shahrestani, et al. · International Conference on Emerging Security Information, Systems and Technologies · 395
Botnet Detection in the Internet of Things using Deep Learning Approaches
2018 · Christopher D. McDermott, Farzan Majdani, et al. · 376
Botnets: A survey
2012 · Sérgio S.C. Silva, Rodrigo M.P. Silva, et al. · Computer Networks · 358
Botnet detection based on traffic behavior analysis and flow intervals
2013 · David Zhao, Issa Traore, et al. · Computers & Security · 344
Spamming botnets
2008 · Yinglian Xie, Fang Yu, et al. · ACM SIGCOMM Computer Communication Review · 339
An Advanced Hybrid Peer-to-Peer Botnet
2009 · Ping Wang, Sherri Sparks, et al. · IEEE Transactions on Dependable and Secure Computing · 333
Detecting Internet of Things attacks using distributed deep learning
2020 · Gonzalo De La Torre Parra, Paul Rad, et al. · Journal of Network and Computer Applications · 328
Explainable Artificial Intelligence in CyberSecurity: A Survey
2022 · Nicola Capuano, Giuseppe Fenza, et al. · IEEE Access · 327
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A Visualized Botnet Detection System Based Deep Learning for the Internet of Things Networks of Smart Cities
2020 · R. Vinayakumar, Mamoun Alazab, et al. · IEEE Transactions on Industry Applications · 323
Wide-scale botnet detection and characterization
2007 · Anestis Karasaridis, Brian Rexroad, et al. · Conference on Workshop on Hot Topics in Understanding Botnets · 320
A Self-Adaptive Deep Learning-Based System for Anomaly Detection in 5G Networks
2018 · Lorenzo Fernandez Maimo, Angel Luis Perales Gomez, et al. · IEEE Access · 302
Usilng Machine Learning Technliques to Identify Botnet Traffic
2006 · Carl Livadas, Robert Walsh, et al. · Conference on Local Computer Networks · 302
Deep Cybersecurity: A Comprehensive Overview from Neural Network and Deep Learning Perspective
2021 · Iqbal H. Sarker · SN Computer Science · 292
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An algorithm for anomaly-based botnet detection
2006 · James R. Binkley, Suresh Singh · 292
Towards effective feature selection in machine learning-based botnet detection approaches
2014 · Elaheh Biglar Beigi, Hossein Hadian Jazi, et al. · IEEE Conference on Communications and Network Security · 286
Performance evaluation of Botnet DDoS attack detection using machine learning
2019 · Tong Anh Tuan, Hoang Viet Long, et al. · Evolutionary Intelligence · 272
Detecting P2P botnets through network behavior analysis and machine learning
2011 · Sherif Saad, Issa Traore, et al. · International Conference on Privacy, Security and Trust (PST) · 267
Disclosure
2012 · Leyla Bilge, Davide Balzarotti, et al. · Annual Computer Security Applications Conference · 251
Works count: 3,963
Citation count: 51,500
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