Worm Epidemics in Vehicular Networks

Abstract

Abstract-Connected vehicles promise to enable a wide range of new automotive services that will improve road safety, ease traffic management, and make the overall travel experience more enjoyable. However, they also open significant new surfaces for attacks on the electronics that control most of modern vehicle operations. In particular, the emergence of vehicle-to-vehicle (V2V) communication risks to lay fertile ground for self-propagating mobile malware that targets automobile environments. In this work, we perform a first study on the the dynamics of vehicular malware epidemics in a large-scale road network, and unveil how a reasonably fast worm can easily infect thousands of vehicles in minutes. We determine how such dynamics are affected by a number of parameters, including the diffusion of the vulnerability, the penetration ratio and range of the V2V communication technology, or the worm selfpropagation mechanism. We also propose a simple yet very effective numerical model of the worm spreading process, and prove it to be able to mimic the results of computationally expensive network simulations. Finally, we leverage the model to characterize the dangerousness of the geographical location where the worm is first injected, as well as for efficient containment of the epidemics through the cellular network.Index Terms-Vehicular networks, V2V, mobile malware.

CC2: Defending Hybrid Worm on Mobile Networks with Two‐Dimensional Circulation Control

“…Gao and Liu [18] focused on the impacts of human behaviors on worm propagation and proposed a two-layer network model to protect large-scale dynamic mobile networks. e short-range worm relies on the direct connections between hardware interfaces and currently tends to attack wireless sensor networks [19][20][21] and vehicular networks [22][23][24].…”

“…In equation 23, when a i, j or b i, j dominates, the value of uc i, j declines, which indicates that the security of the next communication will be more predictable. Based on equations (22) and (23), the revised communication security rs ij can be defined as…”

An agent-based modeling framework for cybersecurity in mobile tactical networks

“…Many examples of malware have been observed which take advantage of security gaps in hardware, software, or communication protocols to infiltrate and spread through mobile ad-hoc networks (MANETs), giving attackers the ability to sabotage, control, or gain access to targeted assets. [6][7][8][9][10][11] It is therefore critical to develop effective defensive mechanisms to protect cyber networks at the tactical edge. Although low-level techniques such as those proposed in Kidston et al 12 can be highly effective in preventing and detecting intrusions, the threat of zero-day attacks and a continuously evolving attack surface make high-level cybersecurity analysis and risk mitigation another important component of a robust cyber defense solution.…”

The Impact of Hierarchy on Bluetooth-Based Malware Spread in Mobile Tactical Networks

“…Cyber attacks are a growing threat to mobile network security. Many examples of malware have been observed which take advantage of security gaps in wireless networking protocols to gain control of critical services by propagating an attack from a single point of entry to targeted assets [31,29,10,11,21]. Worms such as Cabir and CommWarrier, introduced in 2004 and 2005, respectively, demonstrated the ability of self-propagating malware to target popular mobile operating systems such as Android and Windows Mobile by spreading over Bluetooth.…”