Modeling of Wireless Sensor Networks Jamming Attack Strategies

Jamming attacks like constant jamming, deceptive jamming, random jamming and reactive jamming disrupt the normal operation of nodes in wireless sensor networks thereby drastically affecting the network throughput, delay and energy consumption by sending random signals in the network without following the underlying Media Access Control rules. These signals collide with the legitimate signals causing undue traffic in the network leading to Denial of Service Attack. This work provides a model for the different jamming attacks experienced in wireless sensor networks using Unified Modeling Language. Modeling the different jamming attacks would help in better description of their behavior and strategy. Established models can be employed in the design of jamming detection and mitigation framework for DoS attacks mitigation in wireless sensor networks that involve sensors which are known to have limited and constrained resources

H2B: Heartbeat-based Secret Key Generation Using Piezo Vibration Sensors

We present Heartbeats-2-Bits (H2B), which is a system for securely pairing wearable devices by generating a shared secret key from the skin vibrations caused by heartbeat. This work is motivated by potential power saving opportunity arising from the fact that heartbeat intervals can be detected energy-efficiently using inexpensive and power-efficient piezo sensors, which obviates the need to employ complex heartbeat monitors such as Electrocardiogram or Photoplethysmogram. Indeed, our experiments show that piezo sensors can measure heartbeat intervals on many different body locations including chest, wrist, waist, neck and ankle. Unfortunately, we also discover that the heartbeat interval signal captured by piezo vibration sensors has low Signal-to-Noise Ratio (SNR) because they are not designed as precision heartbeat monitors, which becomes the key challenge for H2B. To overcome this problem, we first apply a quantile function-based quantization method to fully extract the useful entropy from the noisy piezo measurements. We then propose a novel Compressive Sensing-based reconciliation method to correct the high bit mismatch rates between the two independently generated keys caused by low SNR. We prototype H2B using off-the-shelf piezo sensors and evaluate its performance on a dataset collected from different body positions of 23 participants. Our results show that H2B has an overwhelming pairing success rate of 95.6%. We also analyze and demonstrate H2B's robustness against three types of attacks. Finally, our power measurements show that H2B is very power-efficient

Energy and Distance evaluation for Jamming Attacks in wireless networks

International audienceWireless networks are prone to jamming-type attacks due to their shared medium. An attacker node can send a radio frequency signal and if this signal interferes with the "normal" signals of two communicating nodes, the communication can be severely impacted. In this paper, we examine radio interference attacks from the jamming node perspective. In particular, we assume a "greedy" jamming node, whose main twofold objectives are to attack and interfere the communication of a transmitter and a receiver node, by minimizing its energy consumption and maximizing the detection time. The two communication nodes are static during the attack window time, while the attacker node can adapt its distance from the transmitter in order to select the most suitable range for a successful interference. In order to take into account the distance factor for the effectiveness of the attack, we derive an optimization model for representing the attack and we will study the key factors that allow effective and efficient implementation of a jamming attack, namely a) the energy b) the detection time and c) the impact on the transmission in terms of lowering the PDR. Three different types of attacks will be analyzed, 1) Constant Jamming, 2) Random Jamming and 3) Reactive Jamming. Simulation results show that the effectiveness of a jamming attack in respect to the others not only depends on the position of the jamming node but also on the distance between the transmitter and receiver nodes

On jamming detection methods for satellite Internet of Things networks

Despite the fast growth of machine-type communications via satellite, the vulnerability of such networks to intentional interference and malicious jamming attacks is a raising concern. Specifically, in this paper, we address a class of jamming attacks in which the adversary uses the underlying knowledge of the satellite physical and access protocol to increase the jamming impact. In particular, we focused on a type of camouflage jamming attack (using publicly known preamble) to deceive the receiver, which rapidly leads to poor performance. Compared to conventional constant jamming attacks, these jamming strategies are known to be more effective and potentially more harmful to the targeted communication network. We analyze methods to detect such jamming attacks and provide examples of jamming detection techniques for the satellite Internet of Things (IoT) networks. Results indicate the effective performance of the jamming detection techniques for a variety of representative system parameters. More specifically, we introduce a simple (counting) jamming detection method along with numerical results for realistic system parameters, which confirms system design vulnerability as well as how the jammer may improve her strategy

EWMA STATISTICS AND FUZZY LOGIC IN FUNCTION OF NETWORK ANOMALY DETECTION

Anomaly detection is used to monitor and capture traffic anomalies in network systems. Many anomalies manifest in changes in the intensity of network events. Because of the ability of EWMA control chart to monitor the rate of occurrences of events based on their intensity, this statistic is appropriate for implementation in control limits based algorithms. The performance of standard EWMA algorithm can be made more effective combining the logic of adaptive threshold algorithm and adequate application of fuzzy theory. This paper analyzes the theoretical possibility of applying EWMA statistics and fuzzy logic to detect network anomalies. Different aspects of fuzzy rules are discussed as well as different membership functions, trying to find the most adequate choice. It is shown that the introduction of fuzzy logic in standard EWMA algorithm for anomaly detection opens the possibility of previous warning from a network attack. Besides, fuzzy logic enables precise determination of degree of the risk

A Study on Intrusion Detection System in Wireless Sensor Networks

The technology of Wireless Sensor Networks (WSNs) has become most significant in present day. WSNs are extensively used in applications like military, industry, health, smart homes and smart cities. All the applications of WSN require secure communication between the sensor nodes and the base station. Adversary compromises at the sensor nodes to introduce different attacks into WSN. Hence, suitable Intrusion Detection System (IDS) is essential in WSN to defend against the security attack. IDS approaches for WSN are classified based on the mechanism used to detect the attacks. In this paper, we present the taxonomy of security attacks, different IDS mechanisms for detecting attacks and performance metrics used to assess the IDS algorithm for WSNs. Future research directions on IDS in WSN are also discussed

CNA Tactics and Techniques: A Structure Proposal

[EN] Destructive and control operations are today a major threat for cyber physical systems. These operations, known as Computer Network Attack (CNA), and usually linked to state-sponsored actors, are much less analyzed than Computer Network Exploitation activities (CNE), those related to intelligence gathering. While in CNE operations the main tactics and techniques are defined and well structured, in CNA there is a lack of such consensuated approaches. This situation hinders the modeling of threat actors, which prevents an accurate definition of control to identify and to neutralize malicious activities. In this paper, we propose the first global approach for CNA operations that can be used to map real-world activities. The proposal significantly reduces the amount of effort need to identify, analyze, and neutralize advanced threat actors targeting cyber physical systems. It follows a logical structure that can be easy to expand and adapt.Villalón-Huerta, A.; Ripoll-Ripoll, I.; Marco-Gisbert, H. (2021). CNA Tactics and Techniques: A Structure Proposal. Journal of Sensor and Actuator Networks. 10(1):1-23. https://doi.org/10.3390/jsan10010014S12310

A Cluster-Based Energy-Efficient Secure Optimal Path-Routing Protocol for Wireless Body-Area Sensor Networks

Recently, research into Wireless Body-Area Sensor Networks (WBASN) or Wireless Body-Area Networks (WBAN) has gained much importance in medical applications, and now plays a significant role in patient monitoring. Among the various operations, routing is still recognized as a resource-intensive activity. As a result, designing an energy-efficient routing system for WBAN is critical. The existing routing algorithms focus more on energy efficiency than security. However, security attacks will lead to more energy consumption, which will reduce overall network performance. To handle the issues of reliability, energy efficiency, and security in WBAN, a new cluster-based secure routing protocol called the Secure Optimal Path-Routing (SOPR) protocol has been proposed in this paper. This proposed algorithm provides security by identifying and avoiding black-hole attacks on one side, and by sending data packets in encrypted form on the other side to strengthen communication security in WBANs. The main advantages of implementing the proposed protocol include improved overall network performance by increasing the packet-delivery ratio and reducing attack-detection overheads, detection time, energy consumption, and delay