Jammer Node Research Articles

The pupil outdoes the master: Imperfect demonstration-assisted trust region jamming policy optimization against frequency-hopping spread spectrum

Jamming decision-making is a pivotal component of modern electromagnetic warfare, wherein recent years have witnessed the extensive application of deep reinforcement learning techniques to enhance the autonomy and intelligence of wireless communication jamming decisions. However, existing researches heavily rely on manually designed customized jamming reward functions, leading to significant consumption of human and computational resources. To this end, under the premise of obviating designing task-customized reward functions, we propose a jamming policy optimization method that learns from imperfect demonstrations to effectively address the complex and high-dimensional jamming resource allocation problem against frequency hopping spread spectrum (FHSS) communication systems. To achieve this, a policy network is meticulously architected to consecutively ascertain jamming schemes for each jamming node, facilitating the construction of the dynamic transition within the Markov decision process. Subsequently, anchored in the dual-trust region concept, we design policy improvement and policy adversarial imitation phases. During the policy improvement phase, the trust region policy optimization method is utilized to refine the policy, while the policy adversarial imitation phase employs adversarial training to guide policy exploration using information embedded in demonstrations. Extensive simulation results indicate that our proposed method can approximate the optimal jamming performance trained under customized reward functions, even with rough binary reward settings, and also significantly surpass demonstration performance.

Resource allocation algorithm for downlink secure transmission in wireless EH cooperative networks with idle relay-assisted jamming

In wireless Energy Harvesting (EH) cooperative networks, we investigate the problem of secure energy-saving resource allocation for downlink physical layer security transmission. Initially, we establish a model for a multi-relay cooperative network incorporating wireless energy harvesting, spectrum sharing, and system power constraints, focusing on physical layer security transmission in the presence of eavesdropping nodes. In this model, the source node transmits signals while injecting Artificial Noise (AN) to mitigate eavesdropping risks, and an idle relay can act as a jamming node to assist in this process. Based on this model, we formulate an optimization problem for maximizing system secure harvesting energy efficiency, this problem integrates constraints on total power, bandwidth, and AN allocation. We proceed by conducting a mathematical analysis of the optimization problem, deriving optimal solutions for secure energy-saving resource allocation, this includes strategies for power allocation at the source and relay nodes, bandwidth allocation among relays, and power splitting for the energy harvesting node. Thus, we propose a secure resource allocation algorithm designed to maximize secure harvesting energy efficiency. Finally, We validate the correctness of the theoretical derivation through Monte Carlo simulations, discussing the impact of parameters such as legitimate channel gain, power splitting factor, and the number of relays on secure harvesting energy efficiency of the system. The simulation results show that the proposed secure energy-saving resource allocation algorithm effectively enhances the security performance of the system.

Investigation on jamming detection in WSN using optimal decision rule

A jamming attack is a special case of a Denial of Service (DoS) attack that completely blocks the data transmission in Wireless Sensor Networks (WSNs). When sensor nodes are distributed in the field, numerous attacks, such as collision, black hole, selective forwarding, jamming, etc., caused by the presence of malicious nodes have the potential to cause network damage. Jamming is a highly risky attack that completely blocks data transmission within the wireless network. The existing technique for detecting jamming attacks are based on predetermined hopping-sequence, cryptographic, or random frequency hopping techniques. However, these mechanisms are more complex and frequently have energy constraints and high overhead. A novel jamming detection method based on a statistical approach that provides high network performance measures is proposed. It is a technique that uses energy-based clustering with a Received Signal Strength Indicator (RSSI). The selection of thresholds used for the detection of jamming is analyzed. The proposed approach employs three detection performance metrics for investigating the jamming attack, namely, Packet to Delivery Ratio (PDR), ENERGY, and RSSI. The jamming node is identified using the Optimal Decision Rule (ODR), which is determined by the hypothesis rule. If the hypothesis is not satisfied, then jamming exists; otherwise, there is no jamming. The novel technique is implemented using a Network Simulator, and various performance metrics such as PDR, Energy consumption, Network throughput, Routing overhead, network, and node lifetime are evaluated to conclude that the statistical approach outperforms the timestamp and IEWMA approaches.

Analysis of Behavioral Characteristics of Jammers to Detect Malicious Nodes in Mobile ADHOC Networks

Wireless ADHOC Networks are used to establish a wireless connection between two computing devices without the need for a Wi-Fi access point or router. This network is decentralized and uses omnidirectional communication media, which makes it more vulnerable to certain types of attacks compared to wired networks. Jamming attacks, a subset of denial-of-service (DoS) attacks, involve malicious nodes that intentionally interfere with the network, blocking legitimate communication. To address this issue, the proposed method analyzes various characteristics of nodes, such as packets sent, received, and dropped, at each node. Using the packet delivery ratio and packet drop ratio, the method detects jamming nodes from normal nodes, improving network performance. The network is simulated in NS2 environment.

Distributed resource allocation model with presence of multiple jammer for underwater wireless sensor networks

Underwater-wireless sensor network (WSN) are prone to the jamming attacks; mainly in case of reactive jamming. Reactive jamming has emerged as one of the critical security threat for underwater-WSN; this occurs due to the reactive jammer capabilities of controlling and regulating jamming duration. Further reactive jammer possesses low detection probability and high vulnerability; moreover the existing model has been designed in consideration with terrestrial-WSN. Hence these models possesses limited capabilities of detecting the jamming and distinguish among uncorrupted and corrupted packets; also it fails to adapt with the dynamic environment. Furthermore co-operative mechanism of jamming model is presented for utilizing the resources in efficient way; however only few existing work has been carried out through the co-operative jamming detection; especially under presence of multiple jammer nodes. For overcoming research issues this paper presents distributed resource allocation (DRA) model adopting cross layer architecture under presence of multiple jammer. DRA algorithm is designed for allocating resource to jammer user in optimal manner. Experiment outcome shows the proposed DRA model achieves much better detection rate considering multi-jammer environment. Thus aid in achieving much better detection accuracy, packet drop, packet transmission and resource utilization performance.

Layering of edge node for jamming attack detection and elimination in wireless sensor network

SummaryWireless sensor network (WSN) is an environmental monitoring system exposing sensor nodes to various attacks. Jamming is an attack that disrupts the entire sensor network and affects the network's life span. The jammer broadcasts the signal at a frequency similar to the broadcast signal to jam the corresponding sensor node. There are many jamming detection schemes that only detect the jamming node, but they do not focus on eliminating the node that is not jamming. In this article, a novel strategy is used along with optimization to eliminate the disturbance in the sensor network and save the power consumed by nodes. The system uses the edge node, the sub‐edge node, and the cluster head for detection of jamming attack. Hyperbolic optimization is implemented in the cluster to eliminate data transmission failures. The proposed model considers the node's round trip time to detect jamming attacks. The optimization method considers the cluster head as the cluster member based on the probability of jamming in the network. The design is implemented and analyzed in MATLAB platform. As a result, the proposed method has improved the detection accuracy to 11.1% compared with extant techniques.

Robust Resource Allocation Design for Secure IRS-Aided WPCN

This paper studies the robust resource allocation design for secure intelligent reflecting surface (IRS)-aided wireless powered communication networks (WPCN). In particular, deploying an IRS can establish favorable end-to-end radio propagation environment for achieving the desired performance gain in secure wireless-powered systems. We aim to minimize the total hybrid base station (HBS) transmit power by jointly designing the active transmitting and receiving beamforming at the HBS, the passive beamforming at the IRS, and the transmit power of each wireless-powered device (WD) and jammer node (JN). We formulate a non-convex optimization problem for the robust resource allocation design taking into account the secrecy rate requirement of the WDs and the power budgets for both the WDs and the JNs. To handle this intractable problem, we propose a computationally efficient iterative suboptimal algorithm exploiting the block coordinate descent approach, the successive convex approximation, and the penalty method, which attains a Karush-Kuhn-Tucker (KKT) solution of the transformed problem. Also, we reveal that the optimal energy beamforming matrices are rank-one sharing the same spatial direction. Simulation results unveil that the proposed scheme is able to dramatically reduce the HBS transmit power over various baseline schemes adopting existing solutions. Besides, our results show the superiority of introducing IRS for secure communication in wireless-powered systems.

Optimal wireless rate and power control in the presence of jammers using reinforcement learning

Future wireless networks require high throughput and energy efficiency. This paper studies using Reinforcement Learning (RL) to do transmission rate and power control for maximizing a joint reward function consisting of both throughput and energy consumption. We design the system state to include factors that reflect packet queue length, interference from other nodes, quality of the wireless channel, battery status, etc. The reward function is normalized and does not involve unit conversion. It can be used to train three different types of agents: throughput-critical, energy-critical, and throughput and energy balanced. Using the NS-3 network simulation software, we implement and train these agents in an 802.11ac network with the presence of a jammer. We then test the agents with two jamming nodes interfering with the packets received at the receiver. We compare the performance of our RL optimal policies with the popular Minstrel rate adaptation algorithm: our approach can achieve (i) higher throughput when using the throughput-critical reward function; (ii) lower energy consumption when using the energy-critical reward function; and (iii) higher throughput and slightly higher energy when using the throughput and energy balanced reward function. Although our discussion is focused on 802.11ac networks, our method is readily applicable to other types of wireless networks.

Interference and secrecy analysis based on randomly spacial model in clustered WSNs

Clustering and layering are widely employed in large-scale wireless sensor networks (WSNs) to alleviate data implosion, reduce transmission delay and improve energy efficiency. It is vital to conduct performance analysis in clustered WSNs for better defining and designing networks. Here, a general analytical framework based on a randomly spacial model is proposed to conduct inter-cluster interference analysis and physical-layer security analysis for clustered WSNs. It is assumed that two adjacent cluster heads exchange confidential massage with a passive eavesdropper and the non-head nodes in clusters could be selected as cooperative jamming (CJ) nodes to disturb the eavesdropper. All mentioned nodes are randomly located in their specific areas. Under the above settings, three scenarios, namely interference, eavesdropping and CJ are considered, and a stochastic geometry tool based on kinematic measure is employed for analysis. Comparing to existing stochastic geometry methods, the proposed analytical framework can handle arbitrarily shaped, disjoint and tiered networks. The results obtained from extensive simulations have verified the rationality of the framework and demonstrated the impact of different parameters on the performance metrics of interest. The comparison with PPP also shows the advantages of this proposed model.

Intelligent slime mold algorithm for proficient jamming attack detection in wireless sensor network

Wireless Sensor Networks (WSNs) depicts to the group of spatially distributed sensor nodes, each node is having individual battery for power consumption which senses the factors like Temperature, Pressure, Soil makeup, Vehicular movement, and checks the physical presence of objects, which are communicate through internet and passing messages between nearest neighbor nodes. WSN are extensively used in several applications like Environmental Monitoring, Area Monitoring, Engineering Monitoring, Health Care Monitoring, and Military Applications. Since WSN are highly susceptible for many attacks especially Jamming Attack. This causes high energy consumption, reduces the life time of nodes, affects the entire sensor networks and most significantly also the confidentiality and integrity of the data packets which are transmitted through dissimilar nodes in the network. In order to overcome these issues, a new bio-inspired algorithm called Intelligent Slime Mold (ISM) has been introduced for detection jamming node and to setting up of alternate optimal path form source node to destination node in WSN to avoid jammer affected nodes by applying Context Aware Decision Rule (CADR). This work ensures the confidentiality and integrity of both the network and data packets.

Modeling and simulation of defense game model for jamming attack in wireless sensor networks using evolutionary game theory

AbstractThe open and shared communication medium of wireless sensor networks creates vulnerability to various types of attacks. In particular, jamming is a kind of attack that is difficult to defend. When the jammer transmits the jamming signal, the nodes covered by the jamming signal will suffer for their transmission. The interactions between the jammer and the source nodes are complex. Thus this article models the interactions between the jammer and the source node as an evolutionary game‐theoretical model. The game model of jamming is formulated, and then the evolutionary analysis of the game model is done. The game model is solved using replicator dynamics, and also the solution is verified by conducting various simulations. It can also be verified by using a stability diagram of replicator dynamics. The equilibrium points are analyzed to check whether that is an evolutionarily stable strategy. Extensive numerical simulation experiments have been carried out to analyze the evolution of strategies for source nodes and jammer nodes.

Two Birds With One Stone: Simultaneous Jamming and Eavesdropping With the Bayesian-Stackelberg Game

In adversarial scenarios, it is crucial to timely monitor what tactical messages that opponent transmitters are sending to intended receiver(s), and disrupt the transmissions immediately if in need. The issue becomes more challenging in face of an intelligent transmitter. To address the above-stated issue, a full-duplex (FD) technique is utilized to enable simultaneous jamming and eavesdropping (SJE) at a friendly jammer node. In particular, the “Two Birds with One Stone” strategy is utilized at the jammer node to realize effective rate degradation and information eavesdropping. A confrontation game between an intelligence-empowered FD jammer and its opponent is investigated. Specifically, to capture their adversarial relationship in an environment with incomplete information, a power-domain Bayesian-Stackelberg game is proposed. The existence of a Stackelberg equilibrium (SE) power solution is proved. The semi-closed-form solutions of SE are derived, which are proved to be asymptotically optimal (have a gap of less than 1% with the exact utility), and improves the jammer node 10% utility compared with the Nash equilibrium. Additionally, the SJE strategy outperforms the half-duplex (HD) and other benchmark schemes.

Secrecy performance of multi-user multi-hop cluster-based network with joint relay and jammer selection under imperfect channel state information

In this paper, we propose and analyze two important secure performance metrics of cluster-based multi-hop relay networks with friendly jamming nodes under the presence of multi-eavesdroppers in condition of imperfect channel estimation. At each hop, partial relay and jammer selection are used to improve the network security. The close-form expressions of secrecy outage probability and the probability of non-zero secrecy capacity of the considered system are derived as criteria to evaluate system security performance. The system performance is analyzed for Rayleigh fading channels with imperfect channel state information. Monte Carlo simulations are also performed to verify the correctness of the analytical results.

Energy Efficient Secure Communication Model against Cooperative Eavesdropper

In a wiretap channel system model, the jammer node adopts the energy-harvesting signal as artificial noise (jamming signal) against the cooperative eavesdroppers. There are two eavesdroppers in the wiretap channel: eavesdropper E1 is located near the transmitter and eavesdropper E2 is located near the jammer. The eavesdroppers are equipped with multiple antennas and employ the iterative block decision feedback equalization decoder to estimate the received signal, i.e., information signal at E1 and jamming signal at E2. It is assumed that E1 has the channel state information (CSI) of the channel between transmitter and E1, and similarly, E2 has the CSI of channel between jammer and E2. The eavesdroppers establish communication link between them and cooperate with each other to reduce the information signal interference at E2 and jamming signal interference at E1. The performance of decoders depends on the signal to interference plus noise ratio (SINR) of the received signal. The power of information signal is fixed and the power of the jamming signal is adjusted to improve the SINR of the received signal. This research work is solely focused on optimizing the jamming signal power to degrade the performance of cooperative eavesdroppers. The jamming signal power is optimized for the given operating SINR with the support of simulated results. The jamming signal power optimization leads to better energy conservation and degrades the performance of eavesdroppers.

Eavesdropper and Jammer Selection in Wireless Source Localization Networks

We consider a wireless source localization network in which a target node emits localization signals that are used by anchor nodes to estimate the target node position. In addition to target and anchor nodes, there can also exist eavesdropper nodes and jammer nodes which aim to estimate the position of the target node and to degrade the accuracy of localization, respectively. We first propose the problem of eavesdropper selection with the goal of optimally placing a given number of eavesdropper nodes to a subset of possible positions in the network to estimate the target node position as accurately as possible. As the performance metric, the Cramer-Rao lower bound (CRLB) related to the estimation of the target node position by eavesdropper nodes is derived, and its convexity and monotonicity properties are investigated. By relaxing the integer constraints, the eavesdropper selection problem is approximated by a convex optimization problem and algorithms are proposed for eavesdropper selection. Moreover, in the presence of parameter uncertainty, a robust version of the eavesdropper selection problem is developed. Then, the problem of jammer selection is proposed where the aim is to optimally place a given number of jammer nodes to a subset of possible positions for degrading the localization accuracy of the network as much as possible. A CRLB expression from the literature is used as the performance metric, and its concavity and monotonicity properties are derived. Also, a convex optimization problem and its robust version are derived after relaxation. Moreover, the joint eavesdropper and jammer selection problem is proposed with the goal of placing certain numbers of eavesdropper and jammer nodes to a subset of possible positions. Simulation results are presented to illustrate performance of the proposed algorithms.

Security-Reliability Trade-Off Analysis for Rateless Codes-Based Relaying Protocols Using NOMA, Cooperative Jamming and Partial Relay Selection

In this paper, we propose secure relaying transmission protocols using rateless codes, where a source sends encoded packets to two intended destinations via help of intermediate relays. Employing non-orthogonal multiple access, two encoded packets can be sent to the destinations at the same time. In addition, two partial relay selection methods are studied to enhance reliability of the data transmission at the first and second hops. For protecting the source-relay and relay-destination transmission against an eavesdropper, cooperative jamming technique is employed. Particularly, in the first phase of each data transmission cycle, the remaining relays (except the selected relay) are used to transmit artificial noise on the eavesdropper, and cooperate with the selected relay to cancel interference components. In the second phase, trusted nodes that are near the destinations are employed to play a role as the cooperative jammers. For a fair performance comparison, we design a simple transmit power allocation for the transmitter and jammer nodes at the first and second phases. We also propose an adaptive power allocation method, where fractions of the transmit power are appropriately allocated to the signals, relying on instantaneous channel gains between the selected relay and the destinations. This paper also derives exact closed-form formulas of outage probability and intercept probability over Rayleigh fading channel. All the performance analysis is then validated by Monte-Carlo simulations. The obtained results clearly show a trade-off between security and reliability that can be enhanced by optimally designing the system parameters.

Opportunistic Relaying and Jamming Based on Secrecy-Rate Maximization for Multiuser Buffer-Aided Relay Systems

In this paper, we investigate opportunistic relaying and jamming techniques and develop relay selection algorithms that maximize the secrecy rate for multiuser buffer-aided relay networks. We develop an approach to maximize the secrecy rate of relay systems that does not require the channel state information (CSI) of the eavesdroppers. We also devise relaying and jamming function selection (RJFS) algorithms to select multiple relay nodes as well as multiple jamming nodes to assist the transmission. In the proposed RJFS algorithms inter-relay interference cancellation (IC) is taken into account. IC is first performed to improve the transmission rate to legitimate users and then inter-relay IC is applied to amplify the jamming signal to the eavesdroppers and enhance the secrecy rate. With the buffer-aided relays the jamming signal can be stored at the relay nodes and a buffer-aided RJFS (BF-RJFS) algorithm is proposed. Greedy RJFS and BF-RJFS algorithms are then developed for relay selection with reduced complexity. Simulation results show that the proposed RJFS and BF-RJFS algorithms can achieve a higher secrecy rate performance than previously reported techniques even in the absence of CSI of the eavesdroppers.

Cooperative Jamming Secure Scheme for IWNs Random Mobile Users Aided by Edge Computing Intelligent Node Selection

The cooperative physical layer security scheme can enhance the communication security of industrial wireless nodes that are computing and energy limitation, which provides the lightweight security for future industrial wireless networks (IWNs). By aiding an edge computing device, the optimal cooperative jamming (CJ) node can be selected, and employed to collaboratively transmit jamming signals to maximumly weaken the quality of the wiretap channel. For overcoming the drawback of the existing work that only studies the physical layer security in static scenes, a practical scenario where legitimate user and eavesdropper move randomly is considered in this article. The ergodic secrecy capacity with CJ in random mobile scenes is derived. An edge computing device is employed to make intelligent selection of an optimal cooperative node. Test and verification are carried out in the industrial factory. The test results show that the novel scheme can improve the secrecy of random mobile users in the IWNs.

Deadline Constrained Packet Scheduling in the Presence of an Energy Harvesting Jammer

Maintaining data communication in the presence of jammer nodes is an important feature required in several modern wireless networks. In this article, we analyze a three node system, where a legitimate link between the transmitter and the receiver is adversarially affected by independent Gaussian noise injected by a jammer. The transmitter is battery powered, and has data arriving as packets. All the data need to be delivered to the receiver before a common deadline. The transmitter's goal is to accomplish this task using as minimum an energy as possible, while the jammer's objective is the opposite, viz. increase the transmitter's energy as much as possible by strategically injecting noise. We consider a jammer node which relies on dynamic energy harvesting sources to power its hardware. The adversarial interactions are modeled by posing a min-max game between the transmitter and the jammer. Solving this, we derive the equilibrium scheduling policies of the transmitter and the jammer for the offline model, and present an iterative algorithm to compute these policies. Competitive online scheduling policies are then proposed, whose competitive ratio is bounded using ideas from the offline policies derived earlier. A constant competitive ratio is shown when the last data packet does not arrive too early, and a significant fraction of the jamming energy is harvested before this arrival.

Detecting the Structural Hole for Social Communities Based on Conductance–Degree

It has been shown that identifying the structural holes in social networks may help people analyze complex networks, which is crucial in community detection, diffusion control, viral marketing, and academic activities. Structural holes bridge different communities and gain access to multiple sources of information flow. In this paper, we devised a structural hole detection algorithm, known as the Conductance–Degree structural hole detection algorithm (CD-SHA), which computes the conductance and degree score of a vertex to identify the structural hole spanners in social networks. Next, we proposed an improved label propagation algorithm based on conductance (C-LPA) to filter the jamming nodes, which have a high conductance and degree score but are not structural holes. Finally, we evaluated the performance of the algorithm on different real-world networks, and we calculated several metrics for both structural holes and communities. The experimental results show that the algorithm can detect the structural holes and communities accurately and efficiently.