Worm Epidemics in Wireless Adhoc Networks

arXiv:0707.2293v1 [cs.NI] 16 Jul 2007 Worm Epidemics in Wireless Adhoc Networks Maziar Nekovee BT Research, Polaris 134, Adastral Park, Martlesham, Suffolk IP5 3RE, UK and Centre for Computational Science, University College London, 20 Gordon Street, London WC1H 0AJ, UK A dramatic increase in the number of computing devices with wireless communication capability has resulted in the emergence of a new class of computer worms which specifically target such devices. The most striking feature of these worms is that they do not require Internet connectivity for their propagation but can spread directly from device to device using a short-range radio communication technology, such as WiFi or Bluetooth. In this paper we develop a new model for epidemic spreading of these worms and investigate their spreading in wireless adhoc networks via extensive Monte Carlo simulations. Our studies show that the threshold behaviour and dynamics of worm epidemics in these networks are greatly affected by a combination of spatial and temporal correlations which characterise these networks, and are significantly different from the previously studied epidemics in the Internet. PACS numbers: 89.75.Hc,05.70.Jk,87.19.Xx, 89.75.Fb I. INTRODUCTION Worms are self-replicating computer viruses which can propagate through computer networks without any hu- man intervention [1, 2, 3]. Cyber attacks by this type of viruses present one of the most dangerous threats to the security and integrity of computer and telecommu- nications networks. The Code Red [4, 5] and Nimda [4] worms, for example, infected hundreds of thousands of computers at alarming speeds and the resulting worm epidemics cost both the public and the private sector a great deal of money. The last few years have seen the emergence of a new type of worms which specifically tar- gets portable computing devices, such as smartphones and laptops. The novel feature of these worms is that they do not necessarily require Internet connectivity for their propagation. They can spread directly from de- vice to device using a short-range wireless communication technology, such as WiFi or Bluetooth [4, 6, 7, 8], creat- ing in their wake an adhoc contact network along which they propagate. The first computer worm written spe- cially for wireless devices was detected in 2003 and within three years the number of such viruses soared from one to more than 300 [8]. With wireless networks becoming increasingly popular, many security experts predict that these networks will soon be a main target of attacks by worms and other type of malware. [8]. Worm and virus attacks on the Internet have been the subject of extensive empirical, theoretical and simula- tion studies [1, 9, 10, 11, 12]. These studies have greatly contributed to our understanding of the impact of net- work topology on the properties of virus spreading [9, 10] and have inspired the design of more effective immunisa- tion strategies to prevent and combat Internet epidemics [11, 12]. Investigation of virus spreading in wireless net- works in general and worms in particular is, however, at its infancy, and there has been very limited studies which address this problem [7, 13]. In this paper we develop a new model for the spreading of worms in Wi-Fi-based wireless adhoc networks and in- vestigate the properties of worm epidemics in these net- works via extensive Monte Carlo simulations. Wireless adhoc networks [14, 15, 16, 16, 17, 18] are distributed net- works which can be formed on the fly by WiFi-equipped devices, such as laptops and smartphones. Nodes in these networks communicate directly with each other and can route data packets wirelessly, either among themselves or to the nearest Internet accesspoint. Adhoc technology has important applications in the provisioning of ubiq- uitous wireless Internet access, disaster relief operations and wireless sensor networks. From the perspective of complex network theory [20, 21, 22, 23] the study of these networks is important as their topology provides a clear-cut example of spatial networks [24]. Spatial net- works are embedded in a metric space where interactions between the nodes is a function of their spatial distance [24, 25]. Despite their relevance to many real-life phe- nomena the properties of these networks are much less studied than abstract graphs. Our Monte Carlo simulations show that epidemic spreading in wireless adhoc networks is significantly dif- ferent from the previously studied epidemics in the In- ternet. The initial growth of the epidemic is significantly slower than the exponential growth observed for worm spreading in the Internet, and the epidemic prevalence exhibits a density-dependent critical threshold which is higher than the value predicted by the mean-field theory. We show that these differences are due to strong spa- tial and temporal correlations which characterise these networks. Our study also reveals the presence of a self- throttling effect in the spreading of worms in

…(Full text truncated)…

This content is AI-processed based on ArXiv data.