The SIC botnet lifecycle model: A step beyond traditional epidemiological models

Khosroshahy, Masood; Ali, M. K.; Qiu, Dongyu

doi:10.1016/j.comnet.2012.07.020

Cited by 19 publications

(7 citation statements)

References 18 publications

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“…There are various methods for the enumeration of botnet members [14, 15]. The enumeration of centralised botnets, in which members can be detected by spying on C&C servers, is easier than that of decentralised botnets.…”

Section: P2p Botnetmentioning

confidence: 99%

See 1 more Smart Citation

Reconstruction of C&C channel for P2P botnet

Dehkordi

Sadeghiyan

2020

IET Communications

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Section: P2p Botnetmentioning

confidence: 99%

“…Also in P2P botnets in which each bot constantly listens to a certain port for connecting other members, the number of botnet members can be obtained by counting the addresses on the Internet with these characteristics. There are also some methods that estimate the number of botnet's nodes, using a local measurement [15].…”

Section: P2p Botnetmentioning

confidence: 99%

Reconstruction of C&C channel for P2P botnet

Dehkordi

Sadeghiyan

2020

IET Communications

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“…In terms of stochastic propagation models in diffusion provenance locating, existing works simulate the spreading by using infection models such as the Susceptible-Infected-Recovered (SIR) [8] model, the Susceptible-Infected SI [7] model, and others [11,12]. On the other hand, recent works [13,14,15] claimed that modeling propagation cascades and information diffusion using continuous-time diffusion networks can provide accurate models.…”

Section: Related Workmentioning

confidence: 99%

Towards large-scale social networks with online diffusion provenance detection

Wang

Pan

et al. 2017

Computer Networks

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In this paper we study a new problem of online discovering diffusion provenances in large networks. Existing work on network diffusion provenance identification focuses on offline learning where data collected from network detectors are static and a snapshot of network is available before learning. However, an offline learning model does not meet the needs of early warning, real-time awareness, and real-time response of malicious information spreading in networks. To this end, we propose an online regression model for real-time diffusion provenance identification. Specifically, we first use offline collected network cascades to infer the edge transmission weights, and then use an online l 1 non-convex regression model as the identification model. The proposed methods are empirically evaluated on both synthetic and real-world networks. Experimental results demonstrate the effectiveness of the proposed model.

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“…Therefore, threats of P2P botnets to Internet security have drawn widespread attention [6][7][8][9][10][11][12]. Yan et al [6] mathematically analyzed the performance of Antbot-a new type of P2P botnets-from the perfectives of resilience, reachability, and scalability, and the authors developed a distributed P2P botnet simulator to evaluate the effectiveness of Antbot against pollution-based mitigation in practice.…”

Section: Introductionmentioning

confidence: 99%

Modeling Peer-to-Peer Botnet on Scale-Free Network

Feng

Wang

Han

et al. 2014

Abstract and Applied Analysis

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Peer-to-peer (P2P) botnets have emerged as one of the serious threats to Internet security. To prevent effectively P2P botnet, in this paper, a mathematical model which combines the scale-free trait of Internet with the formation of P2P botnet is presented. Explicit mathematical analysis demonstrates that the model has a globally stable endemic equilibrium when infection rate is greater than a critical value. Meanwhile, we find that, in scale-free network, the critical value is very little. Hence, it is unrealistic to completely dispel the P2P botnet. Numerical simulations show that one can take effective countermeasures to reduce the scale of P2P botnet or delay its outbreak. Our findings can provide meaningful instruction to network security management.

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The SIC botnet lifecycle model: A step beyond traditional epidemiological models

Cited by 19 publications

References 18 publications

Reconstruction of C&C channel for P2P botnet

Reconstruction of C&C channel for P2P botnet

Towards large-scale social networks with online diffusion provenance detection

Modeling Peer-to-Peer Botnet on Scale-Free Network

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