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In this article, we investigate a model‐free adaptive funnel control framework for nonlinear multiagent systems under jamming attacks. An equivalent time‐varying linear data model is built for agents by utilizing the dynamic linearization approach. Then, a predefined funnel function is presented such that the tracking errors are expected to evolve within a predetermined range. The transient and steady‐state behaviors of the tracking error can be improved by adjusting the parameter values of the funnel function. Moreover, the Stackelberg game is employed to determine the optimal transmission power between the transmitters and jammers considering the state of the transmission channel, which influences the jamming attack rate. Based on funnel control, a model‐free adaptive funnel control scheme is presented to guarantee that the tracking error remains within a funnel boundary (even in the presence of jamming attacks) and the transient and steady‐state performances are improved. The effectiveness of the proposed algorithm is further demonstrated through simulations. [ABSTRACT FROM AUTHOR]

Cybersecurity challenges pose a significant threat to Healthcare Cyber Physical Systems (CPS) because they heavily rely on wireless communication. Particularly, jamming attacks can severely disrupt the integrity of these CPS networks. This research introduces a decentralized system to address this issue. Therefore, this paper suggested a system that leverages trust and blockchain technology to detect jamming attacks in healthcare CPS effectively. It proposes a layered model to improve CPS networks’ lifetime and performance. In smart healthcare environments, it ensures secure and reliable communication between sensor nodes, wearable sensors, medical devices, and monitoring systems. Results show that the suggested approach outperforms the baseline model in identifying and minimizing jamming assaults, with an average percentage difference of 15.71% more detection rate, 20.21% less packet loss rates, 16.65% less node-level energy consumption, reduced network latency of 8.29%, and 9.63% more network throughput.

In contemporary networked control systems (NCSs), ensuring robust and adaptive security measures against dynamic threats like jamming attacks is crucial. These attacks can disrupt the control signals, leading to degraded performance or even catastrophic failures. This paper introduces a novel approach to enhance NCS security by applying stochastic game theory to model and resolve interactions between a defender and a jammer. We develop a two-player zero-sum game where the defender employs mixed strategies to minimize the expected cost of maintaining system stability and control effectiveness in the face of potential jamming. Our model discretizes the state space and employs backward induction to dynamically update the value functions associated with various system states, reflecting the ongoing adjustment of strategies in response to the adversary’s actions. Utilizing linear programming in MATLAB, we optimize the defender’s mixed strategies to systematically mitigate the impact of jamming. The results from extensive simulations demonstrate the efficacy of our proposed strategies in attack scenarios, indicating a substantial enhancement in the resilience and performance of NCSs against jamming attacks. Specifically, the proposed method improved network state stability by 75%, reducing the fluctuation range by over 50% compared with systems without defense mechanisms. This study not only advances the theoretical framework for security in NCSs but also provides practical insights for the design of resilient control systems under uncertainty.

This paper considers the adaptive event-triggered strategy and controller design of vehicle platooning for stochastic attacks and interferences in communication channels. Bernoulli distribution and Markovian distribution Denial of Service models are introduced in this paper. In designing the controller, Aiming at the stochastic jamming attacks, the stability criterion is presented to guide the controller for almost sure string stability, and meanwhile aiming at the special safety requirements and the reduction of system interferences, the asymmetry event-triggered strategy framework is presented to adapt the transmission environment and the different safety requirements, which is designed to balance the principal concern in different situations. Finally, an example is introduced to demonstrate the controller performances of the vehicle platooning with the Bernoulli distribution and Markovian distribution DoS models, which implies that the presented methods are effective. • Considering the different safety requirements of the vehicle platooning and the influence of the SINR, the DoS attack probabilistic model is built by the analysis of the wireless communication channel under stochastic jamming attacks and interference among vehicles. • Considering the stability of the system and the jamming attacks, the controller design method can be refreshed in different communication environments and safety requirements to reduce the shock to the mechanical system of the vehicle and avoid the collision. • Considering the safety and focusing on the characteristic of the platooning system itself, we present the adaptive event-triggered method, which can further reduce the communication frequency, which is another different from previous results. [ABSTRACT FROM AUTHOR]

Randomized exponential backoff is a widely deployed technique for coordinating access to a shared resource. A good backoff protocol should, arguably, satisfy three natural properties: (1) it should provide constant throughput, wasting as little time as possible; (2) it should require few failed access attempts, minimizing the amount of wasted effort; and (3) it should be robust, continuing to work efficiently even if some of the access attempts fail for spurious reasons. Unfortunately, exponential backoff has some well-known limitations in two of these areas: it can suffer subconstant throughput under bursty traffic, and it is not robust to adversarial disruption. The goal of this article is to "fix" exponential backoff by making it scalable, particularly focusing on the case where processes arrive in an online, worst-case fashion. We present a relatively simple backoff protocol, Re-Backoff, that has, at its heart, a version of exponential backoff. It guarantees expected constant throughput with dynamic process arrivals and requires only an expected polylogarithmic number of access attempts per process. Re-Backoff is also robust to periods where the shared resource is unavailable for a period of time. If it is unavailable for D time slots, Re-Backoff provides the following guarantees. For n packets, the expected number of access attempts for successfully sending a packet is O(log2(n + D)). For the case of an infinite number of packets, we provide a similar result in terms of the maximum number of processes that are ever in the system concurrently. [ABSTRACT FROM AUTHOR]

In this paper, we present a machine-learning technique to counteract jamming attacks in underwater networks. Indeed, this is relevant in security applications where sensor devices are located in critical regions, for example, in the case of national border surveillance or for identifying any unauthorized intrusion. To this aim, a multi-hop routing protocol that relies on the exploitation of a Q-learning methodology is presented with a focus on increasing reliability in data communication and network lifetime. Performance results assess the effectiveness of the proposed solution as compared to other efficient state-of-the-art approaches.

Communication in the wireless sensor networks could be disturbed by the jammer and this jamming attacks could be identified as a distinctive type of Denial of Service attacks. This might result in the degradation of the network which could be recognized. Due to the jamming signals, the packet transmission might not be proper. These kinds of attacks are destructive in low power and lossy wireless network due to the attributes such as disruption in communication and rapid trench in the batteries. To detect the attack and to perform the secure data transmission, the illegitimate nodes have to be eradicated. Machine learning and deep learning methods are used for network analysis of intrusion detection and security. Hence, the deep learning model is proposed to identify the attacks which result in secured data transmission. Also, the logistic regression is applied to classify the behaviour of the node so that the deviation could be determined. Deep learning is applied so it can adaptively learn the attacks and classify with higher accuracy. It is efficient as it is adaptive in learning and has improved precision. The performance of the model could be proved with simulations by varying the nodes. The secured data transmission could be proved by analysing several metrics such as packet drop rate, normalized routing overhead, and jitter. The packet drop is decreased to 50%, jitter is decreased to 6% and throughput shows a significant increase by 6% when compared with the Dodge-Jam, a lightweight Mitigating Stealthy Jamming Attacks (MJSA) technique. [ABSTRACT FROM AUTHOR]

A wide range of cyber–physical systems can be modeled as Euler–Lagrange dynamics, whose inherent nonlinearities bring additional difficulties in the design and analysis of controllers for such systems. The objective of this article is to solve the jamming-resilient synchronization control problem of networked Lagrangian systems subject to unknown external disturbances, with the quantized sampling data. Under a jamming attack, a normal communication channel will be blocked with unknown frequencies and intervals. To achieve jamming attack resilience, a robust adaptive controller is proposed. Then a novel auxiliary system is designed for each subsystem over a directed network. By using the quantized sampling data from each subsystem and its neighbors, the jamming attack can be handled by an embedded single-integral subsystem. Sufficient conditions that are independent of the attack parameters are derived to guarantee the global stability of the closed-loop system. Compared with existing jamming-resilient methods, the proposed approach is concise and resilient to any jamming attacks with bounded frequencies and durations. [ABSTRACT FROM AUTHOR]

In this paper, a jamming attack (a kind of Denial-of-Service attack) was investigated, which interfered with the normal operation of a Mobile Ad Hoc network, which is more vulnerable to various attacks because of its self-configuration, dynamic characteristics, therefore, jammers would affect the network QoS parameters by reducing the throughput and increasing the delay. This problem is solved in this study by enabling the Point Coordination Function, which is a media access mechanism specified by the IEEE standard in some selected MANET nodes (guard nodes) to improve the deficiency of MANET’s performance. The Riverbed modeler was utilized as a simulation tool. In this study, six jammers with two different transmission power values had been applied. In a number of different simulation scenarios with and without jammers, the estimated results showed that the jammers affected the network performance by increasing the delay to 3.0658 sec and decreasing the throughput to 120200.59 bits/sec. After enabling the PCF mechanism in a number of selected nodes, the results allowed the user to solve the problem by improving the network deficiency so that the throughput had been increased to 137478.32 bits/sec and the delay had been decreased to 0.7556 sec. It can be concluded that PCF is a good improvement for different levels of jammer transmission power such as 0.01 W and 0.001 W, and PCF also improved the network’s delay and throughput when the number of PCF enabled nodes had been increased to 10 nodes and 12 nodes, respectively. The improvement is also increased. This study can be used in practice for any ad hoc network when attacked by jammers. [ABSTRACT FROM AUTHOR]

Internet of Vehicles (IoV) is considered to be a backbone of smart transportation system where vehicles are expected to exchange traffic information and other data using vehicle-to-vehicle (V2V) communications. Furthermore, V2V communications is regarded as a medium to send upcoming traffic information to vehicles/drivers or passengers using wireless technology in a timely manner. This will help reduce traffic accidents, traffic jams, fuel consumption caused by traffic jams, loss of hours caused by delayed commuting and carbon emission caused by vehicles. Because of the critical nature of IoV for smart transportation systems, secure wireless communication is one of the critical and essential components to offer trustworthy services through IoV. Like in other wireless systems, wireless communication is open in air, which makes attackers’ job easy to launch the malicious actions in IoV. In this paper, we investigate the impact of mobility of vehicles for secure communications in IoV with joint jamming and eavesdropping attacks. We investigate different scenarios, when vehicles (legitimate ones and attackers) travel in same and opposite directions with low speed (school zone speed) limit to highway speed limit. Furthermore, we study the impact of association time and encryption time not only for establishing the connection between vehicles for V2V communications but also for exchanging messages for vehicles after successful association between vehicles and encryption of the message. In addition, we also study the joint impact of jamming and eavesdropping attacks in IoV for different speed limits, transmission ranges and wireless bandwidths. We investigate the extra cost in terms of transmit power and bandwidth incurred by jamming and eavesdropping attacks while maintaining the same secrecy rate as it could have been without those attacks. Numerical results are used to support the analysis. [ABSTRACT FROM AUTHOR]

This article proposes deep learning (DL) framework constructed using deep autoencoder (DAE) to detect the malicious nodes in an Internet of Things (IoT) network assisted by the cognitive radio (CR) technology. In the IoT era, a plethora of nodes are connected to the network for the purpose of collecting and exchanging data. CR technology finds its role in IoT applications because of its ability to efficiently exploit the available spectrum. In this article, we consider IoT nodes as secondary users that perform cooperative spectrum sensing (CSS). Specifically, these IoT nodes sense the spectrum and send their reports to the fusion center (FC) to determine whether the spectrum is occupied by the primary user or not. In such a scenario, the existence of malicious IoT nodes might mislead the FC. To determine which of these IoT nodes are benevolent and which are malicious is crucial. We adopt a DAE-based DL framework, called DAE-TRUST, to detect malicious nodes in CR-assisted IoT. The proposed DAE-TRUST is able to identify the malicious nodes, whose reports can be excluded from the spectrum detection process. Simulation results, in six different real-world environments, show that our DAE-TRUST enhances the performance of CSS in IoT applications. [ABSTRACT FROM AUTHOR]

Abstract In smart cities, the Internet-of-Thing (IoT) provides an enabling communication infrastructure to support tremendous amount of data exchange. Most IoT applications, e.g., wireless local area network, Bluetooth and so forth, utilize the channel-hopping scheme to suppress the transmission security threats. In this paper, to reduce the mutual interference and external jamming attacks, multiple novel channel-hopping patterns, i.e., traditional no-hit-zone (NHZ) hopping pattern and generalized NHZ hopping pattern, are introduced to suit to IoT networks. Particularly the design of probabilistic hopping pattern is first proposed, which has the various usage probabilities with regard to various channels. The properties of these hopping patterns are investigated by the step-to-step examples. Then, the error-rate performance of the multi-node IoT systems adopting these hopping patterns in the presence of jamming attacks is comprehensively analyzed. The extensive simulations show that the traditional/generalized NHZ hopping patterns are in favor of combating the mutual interference but with the limited capability of reducing jamming attacks, while the probabilistic hopping pattern possesses the opposite feature, that is, it has the predominant merit in suppressing jamming attacks. Thus, the novel channel-hopping pattern-based IoT could provide the secure transmission for communication applications in smart cities. Note that, as the physical-layer security technique, the channel-hopping patterns investigated in this paper are convenient to integrate with the security policies implemented in upper layers (e.g., encryption, authentication and so forth).

This work presents efficient connection provisioning techniques mitigating high-power jamming attacks in spectrally-spatially flexible optical networks (SS-FONs) utilizing multicore fibers. High-power jamming attacks are modeled based on their impact on the lightpaths' quality of transmission (QoT) through inter-core crosstalk. Based on a desired threshold on a lightpath's QoT, the modulation format used, the length of the path, as well as a set of physical layer characteristics, each lightpath can potentially tolerate a high-power jamming attack. In this paper, an integer linear program is thus formulated, as well as heuristic algorithms to solve the problem of attack-aware routing, spectrum, modulation format, and core allocation in SS-FONs, aiming to both efficiently provision the network in terms of network resources, as well as minimize the impact of high-power jamming attacks on the established lightpaths. Extensive simulation results are obtained for several algorithm variants with different objectives, demonstrating the validity and efficiency of the proposed techniques that can effectively mitigate high-power jamming attacks, by minimizing the number of inter-core interactions, while at the same time establishing connections with high spectral efficiency.

As the applications of deep reinforcement learning (DRL) in wireless communications grow, sensitivity of DRL-based wireless communication strategies against adversarial attacks has started to draw increasing attention. In order to address such sensitivity and alleviate the resulting security concerns, we in this paper consider a victim user that performs DRL-based dynamic channel access, and an attacker that executes DRL-based jamming attacks to disrupt the victim. Hence, both the victim and attacker are DRL agents and can interact with each other, retrain their models, and adapt to opponents’ policies. In this setting, we initially develop an adversarial jamming attack policy that aims at minimizing the accuracy of victim’s decision making on dynamic channel access. Subsequently, we devise defense strategies against such an attacker, and propose three defense strategies, namely diversified defense with proportional-integral-derivative (PID) control, diversified defense with an imitation attacker, and defense via orthogonal policies. We design these strategies to maximize the attacked victim’s accuracy and evaluate their performances.

With technological breakthroughs and increasing network technology reliability in daily life, it is vital to provide robust network-based system operations. According to the Comprehensive Error Rate Test Report, as network attacks become more common, the number of attacks nearly doubles or triples every year. The fifth-generation mobile communication is going to provide a connecting world with almost zero Latency. Network coding has emerged as a viable answer to the mostly efficiency, secure network needs for coming-generation networking technology. A small cell environment with network coding allows an effective system to communicate with the high rate of data. A significant countermeasure for several forms of network attacks is the Intrusion Detection Systems (IDS). Unique IDS solutions which are lightweight but also provide a high level of security are therefore demanded. The main security concerns in collaborative networks are Distributed -Denial-of-Service (DDOS) attacks, pollution attacks etc. While the network efficiency of non-DDOS attacks is also impaired, the impact of DDOS attacks is severe. In DDOS attacks, the specific node as a victim floods and mass traffic jams occurs, affecting the entire network performance. However, small, NC-enabled mobile cells, due to the essential NC vulnerabilities, are susceptible to pollution attacks. This article presents a brief survey on intrusion detection and mitigation schemes for Network Coding environment Mobile Small Cells. [ABSTRACT FROM AUTHOR]

This paper considers the $\mathscr{L}_{2}$ string stability analysis and controller synthesis for vehicle platooning under jamming attacks and interferences from other communication channels. Jamming attacks and interferences for vehicle platooning systems are modeled as periodic denial of service attacks. Further, the vehicle platooning with denial of service attacks is modeled as a distributed switching system where an average dwell time approach is adopted for the stability analysis. Under the distributed switching system framework, this paper presents a co-design paradigm for the vehicle platooning. The distributed event-triggered method (ETM) and controllers are presented to guarantee $\mathscr{L}_{2}$ string stability, which can ensure that the output cannot be amplified along the vehicle platooning. Sufficient conditions for $\mathscr{L}_{2}$ string stability are then provided to guide the co-design of the ETM and controllers, which can be efficiently obtained by solving LMIs. Simulation results are presented to demonstrate the efficacy of the proposed co-design approach in addressing the denial of service attacks for vehicle platooning systems. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of authenticating the transmitter device in wirelessly powered communications networks (WPCNs). We proposed a physical-layer authentication scheme for a WPCN. In comparison with upper-layer authentication schemes, the proposed scheme has low complexity, low power consumption, low overhead, and high security. For comprehensively analyzing the performance of the proposed scheme by considering the requirements of transmission delay, security, and reliability together, we put forward an analytical framework by considering the probabilities of transmission, security outage, connection outage, and joint security-connection outage. Based on the proposed analytical framework, we further introduced a new systematic metric by calculating the achievable throughput of all users with considering the performance of transmission-delay, security, and reliability together. We defined this new systematic metric as the overall transmission efficiency (OTE) of a WPCN, which can effectively quantize the average efficiency of message transmission in the WPCN with physical layer authentication. We analyzed the events represented by these probability factors over random fading channels and explicitly derive their closed-form expressions. For defending against jamming attacks, we further proposed another metric to estimate which user has the high probability of suffering from jamming attacks. The new metric represents that the adversary has the largest attacking gain with the minimum cost. We implemented our scheme and conducted extensive performance comparisons through simulations. Our experimental results show that the proposed scheme accurately detects an impersonating attack and drops its contribution to the sum of long-term throughput. [ABSTRACT FROM AUTHOR]

In smart cities, the Internet-of-Thing (IoT) provides an enabling communication infrastructure to support tremendous amount of data exchange. Most IoT applications, e.g., wireless local area network, Bluetooth and so forth, utilize the channel-hopping scheme to suppress the transmission security threats. In this paper, to reduce the mutual interference and external jamming attacks, multiple novel channel-hopping patterns, i.e., traditional no-hit-zone (NHZ) hopping pattern and generalized NHZ hopping pattern, are introduced to suit to IoT networks. Particularly the design of probabilistic hopping pattern is first proposed, which has the various usage probabilities with regard to various channels. The properties of these hopping patterns are investigated by the step-to-step examples. Then, the error-rate performance of the multi-node IoT systems adopting these hopping patterns in the presence of jamming attacks is comprehensively analyzed. The extensive simulations show that the traditional/generalized NHZ hopping patterns are in favor of combating the mutual interference but with the limited capability of reducing jamming attacks, while the probabilistic hopping pattern possesses the opposite feature, that is, it has the predominant merit in suppressing jamming attacks. Thus, the novel channel-hopping pattern-based IoT could provide the secure transmission for communication applications in smart cities. Note that, as the physical-layer security technique, the channel-hopping patterns investigated in this paper are convenient to integrate with the security policies implemented in upper layers (e.g., encryption, authentication and so forth). [ABSTRACT FROM AUTHOR]

Smart home systems are developed to interconnect and automate household appliances and create ubiquitous home services. Such a system is mainly driven by the communications among Internet-of-Things (IoT) objects along with Radio Frequency IDentification (RFID) technologies, where the RFID techniques in the IoT network are commonly prone to malicious attacks due to the inherent weaknesses of underlying wireless radio communications. Thus, it causes the smart home systems vulnerable to some active attacks such as the jamming and cloning attacks, which in turn threaten to home breach and personal information disclosure. This paper therefore proposes a new trust-based authentication scheme to effectively address two typical attacks, jamming and cloning attacks, in smart home environment. The evaluation shows that our solution can significantly reduce the authentication failure in jamming attacks, increase the detection probability of cloning attacks, and improve the authentication efficiency to manage the authentication delay in a reasonable time. [ABSTRACT FROM AUTHOR]

Wireless body area networks (WBANs) have to address jamming attacks to support healthcare applications. In this paper, we present a reinforcement learning-based power control scheme for the communication between the in-body sensors and the WBAN coordinator to resist jamming attacks. This scheme applies Q-learning to guide the coordinator to achieve an optimal power control strategy without being aware of the in-body sensor's transmission parameters and the WBAN model of the other sensors in the dynamic anti-jamming transmission. In addition, a transfer learning method is adopted to accelerate the learning speed. Stackelberg equilibria and their existence conditions are deduced in a single time slot to upper bound the performance of the learning-based sensor power control scheme. Simulation results show that the proposed scheme can efficiently increase the utilities and decrease the transmission energy consumptions for the in-body sensors and the WBAN coordinator, and simultaneously reduce the attack possibility of the jammer compared with a standard Q-learning-based sensor power control scheme.

This paper considers the resilient tracking control problem for nonlinear unknown cyber-physical systems (CPSs) subject to jamming attacks in the wireless transmission channel. First, a novel model-free adaptive control (MFAC) framework against jamming attacks is established. A Bernoulli distribution process is used to describe the happen behavior of jamming attacks. Second, a n -steps predictive compensation algorithm is designed in the controller side to reduce the effect of jamming attacks. Then, the model-free adaptive controller is designed such that the tracking error of the nonlinear system is stochastic stable, and all the analysis are based on input/output data. Simulation results demonstrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Underwater sensor networks (UWSNs) are vulnerable to jamming attacks due to the narrow frequency bandwidth and the fast fading channels. In this paper, we propose a reinforcement learning (RL)-based antijamming relay scheme for UWSNs that enables an underwater relay to decide whether to leave the heavily jammed location and choose the relay power based on the state that consists of the bit error rate of the previous transmission, the previous relay power, the current transmit power of the sensor, and the jamming power measured by the relay node. We also propose a deep-RL-based relay scheme to further improve the relay performance for the node that supports deep learning computation. We discuss the computational complexity of the deep-RL-based relay scheme and provide the relay performance bound regarding the bit error rate, energy consumption, and utility of the relay node. Experiments taken in a nonanechoic pool with underwater transducers against smart jamming attacks verify the analysis results. According to the experimental results, the proposed relay scheme can improve the relay performance compared with the benchmark underwater relay schemes. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of event-triggered attack-tolerant tracking control for a networked nonlinear system under spasmodic denial-of-service (DoS) attacks. Compared with some existing results, the exact duration of DoS attacks is not required while only assuming attainable bounds of attack frequency and duration. First, a new event-triggered attack-tolerant fuzzy tracking controller is proposed, to reduce the amount of sensor data transmissions over the sensor-to-controller (S-C) channel while counteracting unknown DoS attacks. Second, for the purpose of performance analysis and synthesis, a unified event-triggered Takagi-Sugeno (T-S) fuzzy switched model is established, which accounts for a suitable attackresilient event-triggered communication scheme and unknown DoS jamming signals. Third, using piecewise Lyapunov-Krasovskii functional (PLKF) analysis technique, a new criterion is derived to ensure exponential stability of the resulting switched tracking error system while achieving a weighted H1 performance level. Additionally, the relationship among the parameters of a DoS attack signal, the triggering parameters, the fuzzy controller gains, the sampling period, and the decay rate can be quantitatively characterized. Moreover, the triggering matrix parameter and fuzzy controller gains are obtained by finding a feasible solution to a set of linear matrix inequalities (LMIs). Finally, numerical verification is performed to demonstrate the effectiveness of the proposed control design method. [ABSTRACT FROM AUTHOR]

Lightweight session key agreement schemes are expected to play a central role in building Internet of things (IoT) security in sixth-generation (6G) networks. A well-established approach deriving from the physical layer is a secret key generation (SKG) from shared randomness (in the form of wireless fading coefficients). However, although practical, SKG schemes have been shown to be vulnerable to active attacks over the initial “advantage distillation” phase, throughout which estimates of the fading coefficients are obtained at the legitimate users. In fact, by injecting carefully designed signals during this phase, a man-in-the-middle (MiM) attack could manipulate and control part of the reconciled bits and thus render SKG vulnerable to brute force attacks. Alternatively, a denial of service attack can be mounted by a reactive jammer. In this paper, we investigate the impact of injection and jamming attacks during the advantage distillation in a multiple-input–multiple-output (MIMO) system. First, we show that a MiM attack can be mounted as long as the attacker has one extra antenna with respect to the legitimate users, and we propose a pilot randomization scheme that allows the legitimate users to successfully reduce the injection attack to a less harmful jamming attack. Secondly, by taking a game-theoretic approach we evaluate the optimal strategies available to the legitimate users in the presence of reactive jammers.

Wireless networks are vulnerable to jamming attacks. Jamming in wireless communication becomes a major research problem due to ease in Unmanned Aerial Vehicle (UAV) launching and blocking of communication channels. Jamming is a subset of Denial of Service Attack (DoS) and an intentional interference where the malicious node disrupts the wireless communication by increasing the noise at the receiver node through transmission interference signal towards the target channel. In this work, the considered jammer is a UAV hovering around the target area to block the communication channel between two transceivers. We proposed a three-dimensional (3-D) UAV jamming localization scheme to track and detect the jammer position at each time step by employing a single boundary node observer. For this purpose, we developed two distributed Extended Kalman Filter (EKF) based schemes: (1) the Distributed EKF (DEKF) scheme using the information of the received power from the jammer at a single nearby boundary node only and (2) Distance Ratio aided Distributed EKF (DEKF-DR) based scheme utilizing an edge node in addition to a single boundary node. Extensive simulations are conducted in order to evaluate the performance of the proposed distributed algorithms for a 3-D trajectory and compared with that of the conventional Centralized EKF (EKF-Centr) based method (which is also modified for the 3-D scenario). The results show the clear supremacy of the proposed distributed algorithms with much lesser complexity in contrast to the conventional EKF-Centr technique.

Wireless Sensor Networks (WSNs) are vulnerable to various security threats. One of the most common types of vulnerability threat is the jamming attack, where the attacker uses the same frequency signals to jam the network transmission. In this paper, an edge node scheme is proposed to address the issue of jamming attack in WSNs. Three edge nodes are used in the deployed area of WSN, which have different transmission frequencies in the same bandwidth. The different transmission frequencies and Round Trip Time (RTT) of transmitting signal makes it possible to identify the jamming attack channel in WSNs transmission media. If an attacker jams one of the transmission channels, then the other two edge nodes verify the media serviceability by means of transmitting information from the same deployed WSNs. Furthermore, the RTT of the adjacent channel is also disturbed from its defined interval of time, due to high frequency interference in the adjacent channels, which is the indication of a jamming attack in the network. The simulation result was found to be quite consistent during analysis by jamming the frequency channel of each edge node in a step-wise process. The detection rate of jamming attacks was about 94% for our proposed model, which was far better than existing schemes. Moreover, statistical analyses were undertaken for field-proven schemes, and were found to be quite convincing compared with the existing schemes, with an average of 6% improvement.

Cognitive radio networks (CRNs) have a shortcoming in that attackers can increase their ability to disturb secondary users (SUs). This paper focuses on jamming attacks in the physical layer, in which several attackers try to interrupt SUs by injecting the interference into their communications. Once a jammer transmits interfering signals on the channel during the defined time, all ongoing transmissions on this channel will be corrupted. It is quite difficult for SUs to protect a single-hop data transmission from jammers. So, obtaining a solution for secure multi-hop data transmission in the presence of jammers becomes a more challenging task in CRNs. This paper investigates a strategy to find the optimal route and channels for transmission between cognitive transmitters and receivers in the presence of jammers in CRNs. In this scenario, the jammers are located randomly and their jamming behavior is assumed to follow a Gaussian distribution. We provide an optimal link-channel pair allocation scheme in which the secondary transmitter (the source) selects the best relay and a suitable channel for each hop in the source-to-destination route to protect the information intended to the secondary receiver (the destination) from the jammers. Simulation results prove the efficiency of the proposed scheme in a CR network. [ABSTRACT FROM AUTHOR]

Consider a scenario where Alice wishes to send a message m to Bob in a time-slotted wireless network. However, there exists an adversary, Carol, who aims to prevent the transmission of m by jamming the communication channel. There is a per-slot cost of 1 to send, receive or jam m on the channel, and we are interested in how much Alice and Bob need to spend relative to Carol in order to guarantee communication. Our approach is to design an algorithm in the framework of resource-competitive analysis where the cost incurred by correct network devices (i.e., Alice and Bob) is parameterized by the cost incurred by faulty devices (i.e., Carol). We present an algorithm that guarantees the successful transmission of m and has the following property: if Carol incurs a cost of T to jam, then both Alice and Bob have a cost of O(Tφ-1+1)=O(T.62+1) in expectation, where φ=(1+5)/2 is the golden ratio. In other words, it possible for Alice and Bob to communicate while incurring asymptotically less cost than Carol. We generalize to the case where Alice wishes to send m to n receivers, and we achieve a similar result. Our findings hold even if (1) T is unknown to either party; (2) Carol knows the algorithms of both parties, but not their random bits; (3) Carol can jam using knowledge of past actions of both parties; and (4) Carol can jam reactively, so long as there is sufficient network traffic in addition to m. [ABSTRACT FROM AUTHOR]

Most of the researches on error rate analysis of direct sequence spread spectrum (DSSS-CDMA) systems assume that the synchronization is perfect. However, in practice, the synchronization is often imperfect due to various effects of channel parameters such as noise and fading. The degree of imperfection further increases due to jamming attacks. The present study, therefore, derives new expressions to compute the probability of error in DSSS-CDMA systems under imperfect synchronisation. It is assumed that the channel is wideband and is subjected to various jamming attacks. A new parameter, called as probability of successful synchronization, was introduced which includes the effects of both the probability of false alarm and detection under fast and slow jammers. Monte Carlo simulations were conducted in MATLAB to establish the validity of the derived mathematical expressions. [ABSTRACT FROM AUTHOR]

In this paper, we provide an overview of recent research efforts on networked control systems under denial-of-service attacks. Our goal is to discuss the utility of different attack modeling and analysis techniques proposed in the literature for addressing feedback control, state estimation, and multi-agent consensus problems in the face of jamming attacks in wireless channels and malicious packet drops in multi-hop networks. We discuss several modeling approaches that are employed for capturing the uncertainty in denial-of-service attack strategies. We give an outlook on deterministic constraint-based modeling ideas, game-theoretic and optimization-based techniques and probabilistic modeling approaches. A special emphasis is placed on tail-probability based failure models, which have been recently used for describing jamming attacks that affect signal to interference-plus-noise ratios of wireless channels as well as transmission failures on multi-hop networks due to packet-dropping attacks and non-malicious issues. We explain the use of attack models in the security analysis of networked systems. In addition to the modeling and analysis problems, a discussion is provided also on the recent developments concerning the design of attack-resilient control and communication protocols.

The delay-tolerant-network (DTN) model is becoming a viable communication alternative to the traditional infrastructure model for military, terrestrial and atypical networks, which are characterised by transmission delay and intermittent network connections. The possibility of limited connectivity and resource scarcity in DTNs make them vulnerable to various cyber-attacks, including interference attacks such as jamming. We study the defence against jamming attacks in a delay tolerant network with two adversarial players - the jammer, and the transmitterreceiver pair in a game theoretic environment. The transmitters seek to choose an optimal time to schedule the transmission securely to maximise the probability of successful delivery before the session expires, while signal interferences from the jammer attempts to minimise this probability. We design strategies for the transmitters that offset transmission period based inference of network traffic by the jammer. We deduce a solution for this game, using a probability distribution function over finite number of strategies for both the players to compute their expected payoff. Using a simulation test-bed, we create several scenarios in which the players are considered to have perfect/imperfect information and compute the expected payoff and resulting equilibrium values. The cases of perfect/imperfect information of the players are further studied using entropy based measures. These results are used to strategically evaluate the optimal time for the players, and assess the efficiency of the strategies used by the transmitters against jammer attacks. [ABSTRACT FROM AUTHOR]

5G wireless networks will support massive connectivity mainly due to device-to-device communications. An enabling technology for device-to-device links is the dynamical spectrum access. The devices, which are equipped with cognitive radios, are to be allowed to reuse spectrum occupied by cellular links. The dynamical spectrum availability makes cognitive users switch between channels. Switching leads to energy consumption, latency, and communication overhead in general. The performance degrades even more when the network is under jamming attack. This type of attack is one of the most detrimental attacks. Addressing jamming while maintaining a desired quality of service is a challenge. While existing anti-jamming mechanisms assume stationary users, in this paper, we propose and evaluate countermeasures for mobile cognitive users. We propose two time-based techniques, which, unlike other existing frequency-based techniques, do not assume accessibility to multiple channels and hence do not rely on switching to countermeasure jamming. We achieve analytical solutions of jamming, switching, and error probabilities. Based on our findings, the proposed techniques out perform other existing frequency-based techniques. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]