A Concept of Clustering-Based Method for Botnet Detection

Ostap, Hubert; Antkiewicz, Ryszard

doi:10.1007/978-3-319-65127-9_18

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…In other words, the majority of DNS research is detrimental to this field. The DNS-based anomaly detection methods are described and assessed in this study [32]. This study suggested Botnet Group Activity Detector, an online unsupervised botnet detection method (BoTGAD) [33].…”

Section: Dns-based Detectionmentioning

confidence: 99%

Detection Mechanisms for Peer-to-Peer Botnets

Manickam¹,

Al-Shareeda²

2022

Preprint

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Cybercrimes are becoming a bigger menace to both people and corporations. It poses a serious challenge to the modern digital world. According to a press release from 2019 Cisco and Cybersecurity Ventures, Cisco stopped seven trillion threats in 2018, or 20 billion threats every day, on behalf of its clients. According to Cybersecurity Ventures, the global cost of cybercrime will reach $6 trillion annually by 2021, which is significantly more than the annual damage caused by all natural disasters and more profitable than the global trade in all major illegal narcotics put together. Botnets are the most common and have a significant negative impact on any civilization among malware programmes. As a result, this study will explore various P2P botnet detection algorithms by outlining their essential characteristics, advantages and disadvantages, obstacles, and future research.

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Section: Dns-based Detectionmentioning

confidence: 99%

Detection Mechanisms for Peer-to-Peer Botnets

Manickam¹,

Al-Shareeda²

2022

Preprint

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“…This approach is also problematic especially for an organization that possesses a huge number of devices that should be secured. This paper presents an improved and developed method for botnet detection which is based on previous research (Ostap et. al 2017).…”

Section: Introductionmentioning

confidence: 99%

“…• thr -threshold of similarity between following clusters, where analysed source IPs were connecting to the same destination IP. From research presented by Ostap et al (2017) results that KhL could take value not less than 0.5. • we consider the hypotheses:…”

mentioning

confidence: 99%