Overcoming Adversaries in Sensor Networks: A Survey of Theoretical Models and Algorithmic Approaches for Tolerating Malicious Interference <s> Gilbert et al. [55] <s> Sensor networks hold the promise of facilitating large-scale, real-time data processing in complex environments, helping to protect and monitor military, environmental, safety-critical, or domestic infrastructures and resources, Denial-of-service attacks against such networks, however, may permit real world damage to public health and safety. Without proper security mechanisms, networks will be confined to limited, controlled environments, negating much of the promise they hold. The limited ability of individual sensor nodes to thwart failure or attack makes ensuring network availability more difficult. To identify denial-of-service vulnerabilities, the authors analyzed two effective sensor network protocols that did not initially consider security. These examples demonstrate that consideration of security at design time is the best way to ensure successful network deployment. <s> BIB001 </s> Overcoming Adversaries in Sensor Networks: A Survey of Theoretical Models and Algorithmic Approaches for Tolerating Malicious Interference <s> Gilbert et al. [55] <s> How efficiently can a malicious device disrupt communication in a wireless network? Imagine a basic game involving two honest players, Alice and Bob, who want to exchange information, and an adversary, Collin, who can disrupt communication using a limited budget of β broadcasts. How long can Collin delay Alice and Bob from communicating? In fact, the trials and tribulations of Alice and Bob capture the fundamental difficulty shared by several n–player problems, including reliable broadcast, leader election, static k–selection, and t–resilient consensus. We provide round complexity lower bounds—and (nearly) tight upper bounds—for each of those problems. These results imply bounds on adversarial efficiency, which we analyze in terms of jamming gain and disruption–free complexity. <s> BIB002 </s> Overcoming Adversaries in Sensor Networks: A Survey of Theoretical Models and Algorithmic Approaches for Tolerating Malicious Interference <s> Gilbert et al. [55] <s> This paper considers the problem of an attacker disrupting an encrypted victim wireless ad hoc network through jamming. Jamming is broken down into layers and this paper focuses on jamming at the Transport/Network layer. Jamming at this layer exploits AODV and TCP protocols and is shown to be very effective in simulated and real networks when it can sense victim packet types, but the encryption is assumed to mask the entire header and contents of the packet so that only packet size, timing, and sequence is available to the attacker for sensing. A sensor is developed that consists of four components. The first is a probabilistic model of the sizes and inter-packet timing of different packet types. The second is a historical method for detecting known protocol sequences that is used to develop the probabilistic models, the third is an active jamming mechanism to force the victim network to produce known sequences for the historical analyzer, and the fourth is the online classifier that makes packet type classification decisions. The method is tested on live data and found that for many packet types the classification is highly reliable. The relative roles of size, timing, and sequence are discussed along with the implications for making networks more secure. <s> BIB003
Consider two players, Alice and Bob, who wish to communicate in the presence of an adversary who can interfere with a bounded, but unknown, number of communications. What is the communication delay introduced by such an adversary? How efficiently can the adversary use its limited budget? These are the questions that motivate the work by Gilbert et al. BIB002 . In a single-hop setting where nodes can detect collisions, the authors derive bounds on (1) the jamming gain, which is defined as the amount of energy used to prevent communication relative to the amount of energy used by continuous jamming BIB003 , and (2) disruption-free complexity, which measures how long the adversary may disrupt a protocol without broadcasting. The adversary is assumed to be reactive and has the ability to spoof both the sender and the receiver; there is no message or identity authentication. A finite budget corresponds to the extent to which the adversary can cause disruption without being discovered. Once discovered, faulty nodes are subject to a variety of remedies BIB001 .