Security wireless sensor networks: prospects, challenges, and future

With the advancements of networking technologies and miniaturization of electronic devices, wireless sensor network (WSN) has become an emerging area of research in academic, industrial, and defense sectors. Different types of sensing technologies combined with processing power and wireless communication capability make sensor networks very lucrative for their abundant use in near future. However, many issues are yet to be solved before their full-scale practical implementations. Among all the research issues in WSN, security is one of the most challenging topics to deal with. The major hurdle of securing a WSN is imposed by the limited resources of the sensors participating in the network. Again, the reliance on wireless communication technology opens the door for various types of security threats and attacks. Considering the special features of this type of network, in this chapter we address the critical security issues in wireless sensor networks. We talk about cryptography, steganography, and other basics of network security and their applicability in WSN. We explore various types of threats and attacks against wireless sensor networks, possible countermeasures, mentionable works done so far, other research issues, etc. We also introduce the view of holistic security and future trends towards research in wireless sensor network security

A New Approach for Jamming Attacks using -Packet-Hiding Methods

The open nature of the wireless medium leaves it vulnerable to intentional interference attacks, typically referred to as jamming. This intentional interference with wireless transmissions can be used as a launch pad for mounting Denial - of - Service attacks on wireless networks. Typically, jamming has been addressed under an external threat model. In this work, we address the problem of selective jamming attacks in wireless networks. In these attacks, the adversary is active only for a short period of time, selectively targeting messages of high importance. We illustrate the advantages of selective jamming in terms of network performance degradation and adversary effort by presenting two case studies; a selective attack o n TCP and one on routing. We show tha t selective jamming attacks can be launched by performing real - time packet classification at the physical layer. To mitigate these attacks, we develop three schemes that prevent real - time packet classification by combining cryptographic primitives with physical - layer attributes. O ur methods and evaluate their computational and communication overhea

A Survey on Layer-Wise Security Attacks in IoT: Attacks, Countermeasures, and Open-Issues

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Security is a mandatory issue in any network, where sensitive data are transferred safely in the required direction. Wireless sensor networks (WSNs) are the networks formed in hostile areas for different applications. Whatever the application, the WSNs must gather a large amount of sensitive data and send them to an authorized body, generally a sink. WSN has integrated with Internet-of-Things (IoT) via internet access in sensor nodes along with internet-connected devices. The data gathered with IoT are enormous, which are eventually collected by WSN over the Internet. Due to several resource constraints, it is challenging to design a secure sensor network, and for a secure IoT it is essential to have a secure WSN. Most of the traditional security techniques do not work well for WSN. The merger of IoT and WSN has opened new challenges in designing a secure network. In this paper, we have discussed the challenges of creating a secure WSN. This research reviews the layer-wise security protocols for WSN and IoT in the literature. There are several issues and challenges for a secure WSN and IoT, which we have addressed in this research. This research pinpoints the new research opportunities in the security issues of both WSN and IoT. This survey climaxes in abstruse psychoanalysis of the network layer attacks. Finally, various attacks on the network using Cooja, a simulator of ContikiOS, are simulated.Peer reviewe

An Asynchronous Node Replication Attack in Wireless Sensor Networks

Abstract Applications of wireless sensor network (WSN) are growing significantly, and many security protocols meant for WSN have been proposed. One of the unique problems of WSN is that the sensor nodes are not tamper resistant as the main attraction of deploying WSN is its low cost. Node replication attack exploits this weakness to launch an attack, in which cryptographic secrets from the compromised sensor nodes are used to create duplicate sensor nodes in large number. Then these sensor nodes are placed in critical locations of the WSN to mount attacks. Several protocols were proposed to defend WSN against the replication attack, and one of the promising among them is distributed detection protocol presented by Parno et al. at IEEE S&P 2005. However, we show in this paper that their distributed detection protocol is vulnerable to an asynchronous node replication attack. Further, we modify the protocol to make it secure for dynamic WSN supporting node mobility

Cognitive Security Framework For Heterogeneous Sensor Network Using Swarm Intelligence

Rapid development of sensor technology has led to applications ranging from academic to military in a short time span. These tiny sensors are deployed in environments where security for data or hardware cannot be guaranteed. Due to resource constraints, traditional security schemes cannot be directly applied. Unfortunately, due to minimal or no communication security schemes, the data, link and the sensor node can be easily tampered by intruder attacks. This dissertation presents a security framework applied to a sensor network that can be managed by a cohesive sensor manager. A simple framework that can support security based on situation assessment is best suited for chaotic and harsh environments. The objective of this research is designing an evolutionary algorithm with controllable parameters to solve existing and new security threats in a heterogeneous communication network. An in-depth analysis of the different threats and the security measures applied considering the resource constrained network is explored. Any framework works best, if the correlated or orthogonal performance parameters are carefully considered based on system goals and functions. Hence, a trade-off between the different performance parameters based on weights from partially ordered sets is applied to satisfy application specific requirements and security measures. The proposed novel framework controls heterogeneous sensor network requirements,and balance the resources optimally and efficiently while communicating securely using a multi-objection function. In addition, the framework can measure the affect of single or combined denial of service attacks and also predict new attacks under both cooperative and non-cooperative sensor nodes. The cognitive intuition of the framework is evaluated under different simulated real time scenarios such as Health-care monitoring, Emergency Responder, VANET, Biometric security access system, and Battlefield monitoring. The proposed three-tiered Cognitive Security Framework is capable of performing situation assessment and performs the appropriate security measures to maintain reliability and security of the system. The first tier of the proposed framework, a crosslayer cognitive security protocol defends the communication link between nodes during denial-of-Service attacks by re-routing data through secure nodes. The cognitive nature of the protocol balances resources and security making optimal decisions to obtain reachable and reliable solutions. The versatility and robustness of the protocol is justified by the results obtained in simulating health-care and emergency responder applications under Sybil and Wormhole attacks. The protocol considers metrics from each layer of the network model to obtain an optimal and feasible resource efficient solution. In the second tier, the emergent behavior of the protocol is further extended to mine information from the nodes to defend the network against denial-of-service attack using Bayesian models. The jammer attack is considered the most vulnerable attack, and therefore simulated vehicular ad-hoc network is experimented with varied types of jammer. Classification of the jammer under various attack scenarios is formulated to predict the genuineness of the attacks on the sensor nodes using receiver operating characteristics. In addition to detecting the jammer attack, a simple technique of locating the jammer under cooperative nodes is implemented. This feature enables the network in isolating the jammer or the reputation of node is affected, thus removing the malicious node from participating in future routes. Finally, a intrusion detection system using `bait\u27 architecture is analyzed where resources is traded-off for the sake of security due to sensitivity of the application. The architecture strategically enables ant agents to detect and track the intruders threateningthe network. The proposed framework is evaluated based on accuracy and speed of intrusion detection before the network is compromised. This process of detecting the intrusion earlier helps learn future attacks, but also serves as a defense countermeasure. The simulated scenarios of this dissertation show that Cognitive Security Framework isbest suited for both homogeneous and heterogeneous sensor networks

Robust multiple frequency multiple power localization schemes in the presence of multiple jamming attacks

Localization of the wireless sensor network is a vital area acquiring an impressive research concern and called upon to expand more with the rising of its applications. As localization is gaining prominence in wireless sensor network, it is vulnerable to jamming attacks. Jamming attacks disrupt communication opportunity among the sender and receiver and deeply impact the localization process, leading to a huge error of the estimated sensor node position. Therefore, detection and elimination of jamming influence are absolutely indispensable. Range-based techniques especially Received Signal Strength (RSS) is facing severe impact of these attacks. This paper proposes algorithms based on Combination Multiple Frequency Multiple Power Localization (C-MFMPL) and Step Function Multiple Frequency Multiple Power Localization (SF-MFMPL). The algorithms have been tested in the presence of multiple types of jamming attacks including capture and replay, random and constant jammers over a log normal shadow fading propagation model. In order to overcome the impact of random and constant jammers, the proposed method uses two sets of frequencies shared by the implemented anchor nodes to obtain the averaged RSS readings all over the transmitted frequencies successfully. In addition, three stages of filters have been used to cope with the replayed beacons caused by the capture and replay jammers. In this paper the localization performance of the proposed algorithms for the ideal case which is defined by without the existence of the jamming attack are compared with the case of jamming attacks. The main contribution of this paper is to achieve robust localization performance in the presence of multiple jamming attacks under log normal shadow fading environment with a different simulation conditions and scenarios