Modeling and analyzing of botnet interactions

Song, Lipeng; Jin, Zhen; Sun, Gui‐Quan

doi:10.1016/j.physa.2010.10.001

Cited by 39 publications

(26 citation statements)

References 14 publications

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“…For instance, similarities in the underlying C&C communication protocols exist, which includes Internet Relay Chat, Hypertext Transfer Protocol (HTTP) [18], and Peer-to-Peer (P2P) networks [24]. In addition to these, mechanisms based on Short Messaging System (SMS) [6][25] [26], Bluetooth [27], or Multimedia Messaging System (MMS) [28] have also emerged to disseminate and control botnet traffic. Fig.…”

Section: Architecturementioning

confidence: 99%

Mobile Botnet Attacks – an Emerging Threat: Classification, Review and Open Issues

2015

KSII TIIS

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The rapid development of smartphone technologies have resulted in the evolution of mobile botnets. The implications of botnets have inspired attention from the academia and the industry alike, which includes vendors, investors, hackers, and researcher community. Above all, the capability of botnets is uncovered through a wide range of malicious activities, such as distributed denial of service (DDoS), theft of business information, remote access, online or click fraud, phishing, malware distribution, spam emails, and building mobile devices for the illegitimate exchange of information and materials. In this study, we investigate mobile botnet attacks by exploring attack vectors and subsequently present a well-defined thematic taxonomy. By identifying the significant parameters from the taxonomy, we compared the effects of existing mobile botnets on commercial platforms as well as open source mobile operating system platforms. The parameters for review include mobile botnet architecture, platform, target audience, vulnerabilities or loopholes, operational impact, and detection approaches. In relation to our findings, research challenges are then presented in this domain. This technological shift has motivated cyber criminals to exploit the vulnerabilities of smartphone devices through off-the-shelf malware creation tools [3]. Similarly, the spread of mobile applications have enabled the dissemination of malicious code to a wide range of potential audience. Through the Internet, the majority of current mobile threats replicate the behavior of attacks on desktop machines. Therefore, many of the existing solutions can also be considered applicable to the malicious mobile attacks. Nevertheless, mobile devices have their own constraints, such as limited processing, less data storage capabilities, and heterogeneity of OS (e.g., Android, iOS, and Windows), that restricts the security solutions to be efficiently programmed.

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Section: Architecturementioning

confidence: 99%

Mobile Botnet Attacks – an Emerging Threat: Classification, Review and Open Issues

2015

KSII TIIS

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“…The second compound matrix [2] of the Jacobin matrix can be calculated as follows (see [10,11]): [2]…”

Section: Theorem 4 * Is Uniquely Globally Asymptotically Stable Ifmentioning

confidence: 99%

“…And they are residing by erasing data, damaging files, or modifying the normal operation. Due to the high similarity between computer virus and biological virus [1], various computer virus propagation models are proposed [2][3][4]. This dynamical modeling of the spread process of computer virus is an effective approach to the understanding of the behavior of computer viruses because on this basis, some effective measures can be posed to prevent infection.…”

Section: Introductionmentioning

confidence: 99%

Modeling Computer Virus and Its Dynamics

Mei

Huang

et al. 2013

Mathematical Problems in Engineering

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Based on that the computer will be infected by infected computer and exposed computer, and some of the computers which are in suscepitible status and exposed status can get immunity by antivirus ability, a novel coumputer virus model is established. The dynamic behaviors of this model are investigated. First, the basic reproduction numberR0, which is a threshold of the computer virus spreading in internet, is determined. Second, this model has a virus-free equilibriumP0, which means that the infected part of the computer disappears, and the virus dies out, andP0is a globally asymptotically stable equilibrium ifR0<1. Third, ifR0>1then this model has only one viral equilibriumP*, which means that the computer persists at a constant endemic level, andP*is also globally asymptotically stable. Finally, some numerical examples are given to demonstrate the analytical results.

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“…By now, current botnet detection research is mainly based on network behaviors [5,6,7,8,9,10,11,12]. Few people have studied how to detect botnets based on host behaviors [13].…”

Section: Related Workmentioning

confidence: 99%