Access Delay Analysis in String Multi-hop Wireless Network Under Jamming Attack

Built upon a shared wireless medium, wireless network is particularly vulnerable to jamming attacks. The ability to recover from attacks and maintain an acceptable level of service degradation is a crucial aspect in the design of a wireless network. To address this issue, this paper investigates the network restoration solutions via the joint design of traffic rerouting, channel re-assignment, and scheduling. Efficient routing and channel assignment schemes can relieve the interference caused by both the normal network nodes and the jamming nodes. Therefore, based on the necessary conditions of schedulability, we first formulate the optimal network restoration problem as linear programming problem, which gives an upper bound on the achievable network throughput. After we solve the LP problems, we have a set of flows assigned to edges that have been assigned to different channels. And based on the LP solutions, we provide a greedy scheduling algorithm using dynamic channel assignment, which schedules both the network traffic and the jamming traffic. In particular, we consider two strategies, namely global restoration and local restoration, which can support a range of tradeoffs between the restoration latency and network throughput after restoration. To quantitatively evaluate the impact of jamming attacks during and after restoration, we define two performance degradation indices, transient disruption index (TDI) and throughput degradation index (THI). Finally, extensive performance evaluations are performed to study the impact of various jamming scenarios in a multi-hop multi-channel wireless network.

Due to the shared nature of wireless mediums, jamming attacks have long been a great hazard to the security of wireless networks. A plethora of efforts have been spent to mitigate the impact of jamming attacks, and especially the localization technique of malicious jammer emerges in the last decade and enables us to remove the interfering devices from the physical layer. Since it is impossible to directly measure the interfering signal in a jamming scenario, many existing methods rely on inaccurate ranging estimation to locate the jammers. In this paper, we propose an improved least-square jammer localization method leveraging the network distribution properties. Specifically, we exploit the stochastic geometry theory to analyze the coverage changes of wireless devices around the jammer, which are then used to improve the accuracy of ranging estimation. Extensive numerical results demonstrate the effectiveness and robustness of the proposed jammer localization methods under various scenarios. Notably, the improved leastsquares method has a decreasing of 35 % on the mean localization error comparing to the traditional least-square method.

Wireless networks are built upon a shared medium that makes it easy for adversaries to launch jamming-style attacks. These attacks can be easily accomplished by an adversary emitting radio frequency signals that do not follow an underlying MAC protocol. Jamming attacks can severely interfere with the normal operation of wireless networks and, consequently, mechanisms are needed that can cope with jamming attacks. In this paper, we examine radio interference attacks from both sides of the issue: first, we study the problem of conducting radio interference attacks on wireless networks, and second we examine the critical issue of diagnosing the presence of jamming attacks. Specifically, we propose four different jamming attack models that can be used by an adversary to disable the operation of a wireless network, and evaluate their effectiveness in terms of how each method affects the ability of a wireless node to send and receive packets. We then discuss different measurements that serve as the basis for detecting a jamming attack, and explore scenarios where each measurement by itself is not enough to reliably classify the presence of a jamming attack. In particular, we observe that signal strength and carrier sensing time are unable to conclusively detect the presence of a jammer. Further, we observe that although by using packet delivery ratio we may differentiate between congested and jammed scenarios, we are nonetheless unable to conclude whether poor link utility is due to jamming or the mobility of nodes. The fact that no single measurement is sufficient for reliably classifying the presence of a jammer is an important observation, and necessitates the development of enhanced detection schemes that can remove ambiguity when detecting a jammer. To address this need, we propose two enhanced detection protocols that employ consistency checking. The first scheme employs signal strength measurements as a reactive consistency check for poor packet delivery ratios, while the second scheme employs location information to serve as the consistency check. Throughout our discussions, we examine the feasibility and effectiveness of jamming attacks and detection schemes using the MICA2 Mote platform.

While the millimeter-wave (mmWave) communication is less susceptible against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an attacker can opportunistically conduct wiretapping or jamming to initiate a more hazardous attack based on the instantaneous costs of wiretapping and jamming. We also provide three realizations of the OWJ attack, which are mainly determined by the cost models relevant to distance, path loss and received power, respectively. To understand the impact of the new attack on mmWave network security, we first develop novel approximation techniques to characterize the irregular distributions of wiretappers, jammers and interferers under three OWJ realizations. With the help of the results of node distributions, we then derive analytical expressions for the secrecy transmission capacity to depict the network security performance under OWJ. Finally, we provide extensive numerical results to illustrate the effect of OWJ and to demonstrate that the new attack can more significantly degrade the network security performance than the pure wiretapping or jamming attack.

The aims of this paper are to analyze the performance of a one-dimensional ALOHA ad hoc network and to investigate the impact of the access probability of the ALOHA protocol on the network performance. As a performance metric we consider the average number of nodes that successfully receive a packet from an arbitrary node. To mathematically model the random locations of nodes and the interference in the ad hoc network, we use stochastic geometry theory. With the help of stochastic geometry theory, we model the ad hoc network, derive an analytic form of the performance metric, and finally obtain the optimal access probability that maximizes the performance metric. Numerical examples are provided to validate our analysis and to investigate the performance behavior.

Jamming attack detection in a pair of RF communicating vehicles using unsupervised machine learning

Wireless networks are built upon a shared medium that makes it easy for adversaries to conduct radio interference, or jamming attacks, which effectively cause a denial of service (DoS) of either transmission or reception functionalities. These attacks can be easily accomplished by an adversary by either bypassing MAC-layer protocols, or emitting a radio signal targeted at jamming a particular channel. In this thesis, we examine the issue of jamming wireless networks, and sensor networks in particular, by studying both the attack and defense side of the problem. On the attack side, we present four different jamming attack models that can be used by an adversary to disable the operation of a wireless network, and evaluate their effectiveness in terms of how each method affects the ability of a wireless node to send and receive packets. In order to cope with the problem of jamming, we discuss a two-phase strategy involving the diagnosis of the attack, followed by a suitable defense strategy. For detection, we show that single measurement statistics are not enough to reliably classify the presence of a jamming attack, and propose multimodal detection methods. To cope with jamming, we propose a technique, channel surfing, which involves evading the interferer in the spectral domain. Several different channel surfing models are presented, and we evaluate their effectiveness using a testbed of MICA2 motes. Beyond channel surfing, we overview a second defense strategy whereby it is possible to establish a low data rate jamming resistant communication channel by modulating the interarrival times between jammed packets.

Physical layer radio jamming is a serious security threat to a wireless sensor network since the network relies on open wireless radio channels. A radio jammer is typically strategic and chooses its jamming strategy in response to the possible defense strategy taken by the sensor network. In this paper we model the interaction between the sensor network and the attacker as a noncooperative nonzero-sum static game. In such a game, the sensor network has a set of strategies of controlling its probability of wireless channel access and the attacker manipulates its jamming by controlling its jamming probability after sensing a transmission activity. We propose an algorithm for computing the optimal strategies for jamming attack and network defense. A critical issue is that there may exist a number of possible strategy profiles of Nash equilibria. To address this issue, we further propose to choose realistic Nash equilibria by applying the Pareto dominance and risk dominance. Our numerical results demonstrate that the strategies chosen by the Pareto dominance and risk dominance achieve the expected performance. Our results presented in the paper provide valuable defense guidance for wireless sensor networks against jamming attacks.

We study the following questions related to wireless network security: Which jammer placement configuration during a jamming attack results in the largest degradation of network throughput? and Which network design strategies are most effective in mitigating a jamming attack? Although others have studied similar jammer placement problems, this article is the first to optimize network throughput subject to radio wave interference. We formulate this problem as a bi-level mixed-integer program, and solve it using a cutting plane approach that is able to solve networks with up to 81 transmitters, which is a typical size for studies in wireless network optimization. Experiments with the algorithm also yielded the following insights into wireless network jamming: (1) increasing the number of channels is the best strategy for designing a network that is robust against jamming attacks, and (2) increasing the range of the jammer is the best strategy for the attacker. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 67(2), 111–125 2016

For various wireless networks in adversarial environment, jamming attacks against radio channels can severely interfere with the normal network operations or even completely disrupt the network services. In this paper, we propose a new detection and defense method against hostile jamming by using dynamic radio channel allocation (RCA) technique at real-time and without relying on a large amount of data as in the existing methods. Each node independently estimates the normal value of the network throughput. By comparing the operational throughput to the normal value, an abnormal usage of the channel can be found. In this way, the jamming attacks can be detected by monitoring and analyzing the throughput. After detecting the jamming, the defense of the attack is a self-healing approach: switch the jammed channel to one of the available channels by the RCA techniques automatically. The effectiveness of the proposed method has been demonstrated by extensive simulation results.

Networks of randomly distributed nodes appear in various fields, including forestry and wireless communications, and can often be modeled, using stochastic geometry theory, as Poisson point processs (PPPs). In these contexts, estimation of nodes density is important for monitoring and optimizing the network. Originally, this problem has been addressed in forestry where the trees are the nodes and, assuming these are distributed according to an infinite two-dimensional homogeneous PPP, the spatial density can be estimated by measuring the distances from one reference tree to its neighbors. However, in many other scenarios, nodes could result invisible with some probability, for example depending on distance. In this paper, we derive the Cramér-Rao bounds and new estimators for the node spatial density, taking into account a limited capability in sensing neighbors. As an example, we provide estimators of the spatial density of transmitting devices in wireless networks with links affected by thermal noise, path loss, and shadowing.

Caching on the edge has been recognized as an effective solution to tackle the backhaul constraint of network densification. However, most related works ignored user mobility in wireless networks, which is unreasonable under the background of network densification. For a more flexible and context-aware caching decision, the concept of caching on the edge can be extended to mobile edge computing (MEC) that enables computation and storage resources at mobile edge networks. With MEC servers deployed on base stations, a huge amount of collected radio access network context data can be analyzed and utilized to render a caching scheme adaptive to user’s context-aware information. In this regard, a novel mobility-aware coded probabilistic caching scheme is proposed for MEC-enabled small cell networks (SCNs). Different from previous mobility-aware caching schemes, user mobility and distributed storage are incorporated into a conventional probabilistic caching scheme, with the aim of throughput maximization. Based on stochastic geometry theory and a modified mobility model of discrete random jumps, the explicit expression of throughput is derived. Due to the complexity of the expression, two light-weight heuristic algorithms are provided to numerically obtain the optimal solutions. Moreover, a significant trade-off among the gains of mobility diversity, content diversity, and channel selection diversity is discussed, and we further numerically analyze how such a trade-off is influenced by user mobility, content popularity, and backhaul capacity, with some fundamental insights into the application of the proposed scheme in MEC-enabled SCNs. The superiority of our proposed scheme is demonstrated by the comparisons with the classical M most popular caching scheme and the conventional probabilistic caching scheme. Numerical results show that our proposed caching scheme achieves higher throughput than those of the other two, especially when users of intense mobility request contents, of which the popularity profile is not skewed, in MEC-enabled SCNs with poor backhaul capacity, indicating that the proposed caching scheme is a promising solution for network densification.

Jamming attacks on wireless networked control systems are investigated for the scenarios where the system dynamics face exogenous disturbance. In particular, the control input packets are assumed to be transmitted from a controller to a remotely located linear plant over an insecure wireless communication channel that is subject to jamming attacks. The time-varying likelihood of transmission failures on this channel depends on the power of the jamming interference signal emitted by an attacker. We show that jamming attacks can prevent stability when the system faces disturbance, even if the attacked system without disturbance is stable. We also show that stability under jamming and disturbance can be achieved if the average jamming interference power is restricted in a certain way that we characterize in this article. We illustrate our results on an example networked control system with a fading wireless channel, where the outage probability is affected by jamming attacks.

There is an increasing deployment of Internet-of-Things (IoT) networks, from smart meters and smart lighting to humidity soil sensors and medical wearable devices. Long Range (LoRa) is one such over-the-air (OTA) transmission IoT standard, having a wide range of applications in smart cities, agriculture and health. It facilitates the inter-connection of services and smooth exchange of information. However, owing to its wireless interface, it is susceptible, as all wireless networks are, to OTA attacks. In this paper, we initially obtain the Bit Error Rate (BER) and Packet Error Rate (PER) of LoRa, in order to investigate the impact of continuous and reactive jamming attacks on it. We show that overall, LoRa can achieve a good performance even under a jamming attack, subject to parameters such as the transmit power, the Spreading Factor (SF) and the Coding Rate (CR). Moreover, it is proven that the impact on BER and PER is similar irrespective of whether the attack occurs with total frame synchronization or is synchronized to after the preamble transmission. Lastly, we apply a detection scheme, based on previous values of Received Signal Strength Indicator (RSSI) and PER to successfully identify malicious attacks.

Service continuity is a critical issue in wireless networks. Unfortunately, jamming attacks seriously threatens the continuity of wireless networks. The open nature of wireless mediums makes it vulnerable to any wireless capable devices. There are only few researches address the issue of how the service providers should deploy its topology or allocate its resources to minimize the impact of jamming attacks launched by malicious attackers. In this paper, a mathematical model formulating an attack-defense scenario of the problem is proposed. The results show when deploying defense resources, considering hops from core node is more useful than link degree. With the advantage of simulations, the concept of incomplete information can be taken into account which though raises the difficulty of the problem, but makes the problem closer to reality.