Malware-Propagative Mobile Ad Hoc Networks: Asymptotic Behavior Analysis

Karyotis, Vasileios; Kakalis, Anastasios; Papavassiliou, Symeon

doi:10.1007/s11390-008-9141-z

Cited by 27 publications

(15 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Virus spreading models [10][11][12] and control strategies in mobile environments attract much attention. So far, many efforts have been recently made to model virus spreading among computer network.…”

Section: Related Workmentioning

confidence: 99%

Influence of node mobility on virus spreading behaviors in multi-hop network

Liu

Jin

Wang

2016

J Wireless Com Network

View full text Add to dashboard Cite

Multi-hop network has received growing attention recently with the widely use of wireless network communication technology. At the same time, the security of multi-hop network is facing more serve challenges. Unfortunately, classic techniques for computer virus spreading model cannot be applied to multi-hop network because of ignoring dynamic topology of network. In this paper, classic susceptible-infected (SI) model, susceptible-infectedsusceptible (SIS) model and susceptible-infected-removed (SIR) model are applied to multi-hop network based on random way-point (RWP) model, and contact duration of virus is introduced. Virus spreading behaviors are examined through contact duration of virus, communication radius of node, distribution density of node, and the number of initial infected nodes. Simulation results show that node mobility has significant effect on virus spreading behaviors. In particular, a special node speed that can lead network to appear the fastest-spreading virus phenomenon is found. The special speed is approximately equal to the ratio of communication radius of node to contact duration of virus. Distribution density of node and the number of initial infected nodes almost do not affect the special speed.

show abstract

Section: Related Workmentioning

confidence: 99%

Influence of node mobility on virus spreading behaviors in multi-hop network

Liu

Jin

Wang

2016

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…The security issue regarding malware propagation that exploits geographic proximity of wireless-enabled devices has received significant attention in recent years. Many efforts have been made to model the propagation behavior of malware in wireless networks, such as wireless sensor networks [70]- [73] and wireless ad-hoc networks [74]- [78].…”

Section: Comparison Of Epidemic Modelsmentioning

confidence: 99%

Smartphone Malware and Its Propagation Modeling: A Survey

Peng

Yang

2014

IEEE Commun. Surv. Tutorials

157

View full text Add to dashboard Cite

Smartphones are pervasively used in society, and have been both the target and victim of malware writers. Motivated by the significant threat that presents to legitimate users, we survey the current smartphone malware status and their propagation models. The content of this paper is presented in two parts. In the first part, we review the short history of mobile malware evolution since 2004, and then list the classes of mobile malware and their infection vectors. At the end of the first part, we enumerate the possible damage caused by smartphone malware. In the second part, we focus on smartphone malware propagation modeling. In order to understand the propagation behavior of smartphone malware, we recall generic epidemic models as a foundation for further exploration. We then extensively survey the smartphone malware propagation models. At the end of this paper, we highlight issues of the current smartphone malware propagation models and discuss possible future trends based on our understanding of this topic.

show abstract

“…For example, V. Karyotis et-el [18] have study the propagation of malware over a wireless ad hoc network. They proposed a probabilistic model that is able to model and capture the aggregated behavior of a large ad hoc network attacked by a malicious node, where legitimate network nodes are prone to propagate infections they receive to their neighbors.…”

Section: B Infrastructure-based Detection Typologymentioning

confidence: 99%

Handsets Malware Threats and Facing Techniques

Elfattah¹,

Youssif²,

Ahmed³

2011

IJACSA

View full text Add to dashboard Cite

Abstract-Nowadays, mobile handsets combine the functionality of mobile phones and PDAs. Unfortunately, mobile handsets development process has been driven by market demand, focusing on new features and neglecting security. So, it is imperative to study the existing challenges that facing the mobile handsets threat containment process, and the different techniques and methodologies that used to face those challenges and contain the mobile handsets malwares. This paper also presents a new approach to group the different malware containment systems according to their typologies.

show abstract

Malware-Propagative Mobile Ad Hoc Networks: Asymptotic Behavior Analysis

Cited by 27 publications

References 12 publications

Influence of node mobility on virus spreading behaviors in multi-hop network

Influence of node mobility on virus spreading behaviors in multi-hop network

Smartphone Malware and Its Propagation Modeling: A Survey

Handsets Malware Threats and Facing Techniques

Contact Info

Product

Resources

About