A Comprehensive Survey on Routing and Security in Mobile Wireless Sensor Networks

With the continuous advances in mobile wirelesssensor networks (MWSNs), the research community hasresponded to the challenges and constraints in the design of thesenetworks by proposing efficient routing protocols that focus onparticular performance metrics such as residual energy utilization,mobility, topology, scalability, localization, data collection routing,Quality of Service (QoS), etc. In addition, the introduction ofmobility in WSN has brought new challenges for the routing,stability, security, and reliability of WSNs. Therefore, in thisarticle, we present a comprehensive and meticulous investigationin the routing protocols and security challenges in the theory ofMWSNs which was developed in recent years

Copyright protection of scalar and multimedia sensor network data using digital watermarking

This thesis records the research on watermarking techniques to address the issue of copyright protection of the scalar data in WSNs and image data in WMSNs, in order to ensure that the proprietary information remains safe between the sensor nodes in both. The first objective is to develop LKR watermarking technique for the copyright protection of scalar data in WSNs. The second objective is to develop GPKR watermarking technique for copyright protection of image data in WMSN

Simulation of attacks for security in wireless sensor network

The increasing complexity and low-power constraints of current Wireless Sensor Networks (WSN) require efficient methodologies for network simulation and embedded software performance analysis of nodes. In addition, security is also a very important feature that has to be addressed in most WSNs, since they may work with sensitive data and operate in hostile unattended environments. In this paper, a methodology for security analysis of Wireless Sensor Networks is presented. The methodology allows designing attack-aware embedded software/firmware or attack countermeasures to provide security in WSNs. The proposed methodology includes attacker modeling and attack simulation with performance analysis (node?s software execution time and power consumption estimation). After an analysis of different WSN attack types, an attacker model is proposed. This model defines three different types of attackers that can emulate most WSN attacks. In addition, this paper presents a virtual platform that is able to model the node hardware, embedded software and basic wireless channel features. This virtual simulation analyzes the embedded software behavior and node power consumption while it takes into account the network deployment and topology. Additionally, this simulator integrates the previously mentioned attacker model. Thus, the impact of attacks on power consumption and software behavior/execution-time can be analyzed. This provides developers with essential information about the effects that one or multiple attacks could have on the network, helping them to develop more secure WSN systems. This WSN attack simulator is an essential element of the attack-aware embedded software development methodology that is also introduced in this work.This work has been funded by the Spanish MICINN under the TEC2011-28666-C04-02 and TEC2014-58036-C4-3-R project

Maximize resource utilization based channel access model with presence of reactive jammer for underwater wireless sensor network

Underwater sensor networks (UWSNs) are vulnerable to jamming attacks. Especially, reactive jamming which emerged as a greatest security threat to UWSNs. Reactive jammer are difficult to be removed, defended and identified. Since reactive jammer can control and regulate (i.e., the duration of the jam signal) the probability of jamming for maintaining high vulnerability with low detection probability. The existing model are generally designed considering terrestrial wireless sensor networks (TWSNs). Further, these models are limited in their ability to detect jamming correctly, distinguish between the corrupted and uncorrupted parts of a packet, and be adaptive with the dynamic environment. Cooperative jamming model has presented in recent times to utilize resource efficiently. However, very limited work is carried out using cooperative jamming detection. For overcoming research challenges, this work present Maximize Resource Utilization based Channel Access (MRUCA). The MRUCA uses cross layer design for mitigating reactive jammer (i.e., MRUCA jointly optimizes the cooperative hopping probabilities and channel accessibility probabilities of authenticated sensor device). Along with channel, load capacity of authenticated sensor device is estimated to utilize (maximize) resource efficiently. Experiment outcome shows the proposed MRUCA model attain superior performance than state-of-art model in terms of packet transmission, BER and Detection rate

Security challenges of Internet of Underwater Things : a systematic literature review

Water covers approximately 71% of the earth surface, yet much of the underwater world remains unexplored due to technology limitations. Internet of Underwater Things (IoUT) is a network of underwater objects that enables monitoring subsea environment remotely. Underwater Wireless Sensor Network (UWSN) is the main enabling technology for IoUT. UWSNs are characterised by the limitations of the underlying acoustic communication medium, high energy consumption, lack of hardware resources to implement computationally intensive tasks and dynamic network topology due to node mobility. These characteristics render UNWSNs vulnerable to different attacks, such as Wormhole, Sybil, flooding, jamming, spoofing and Denial of Service (DoS) attacks. This article reviews peer-reviewed literature that addresses the security challenges and attacks on UWSNs as well as possible mitigative solutions. Findings show that the biggest contributing factors to security threats in UWSNs are the limited energy supply, the limited communication medium and the harsh underwater communication conditions. Researchers in this field agree that the security measures of terrestrial wireless sensor networks are not directly applicable to UWSNs due to the unique nature of the underwater environment where resource management becomes a significant challenge. This article also outlines future research directions on security and privacy challenges of IoUT and UWSN

Analysis of Security Attacks & Taxonomy in Underwater Wireless Sensor Networks

Abstract: Underwater Wireless Sensor Networks (UWSN) have gained more attention from researchers in recent years due to their advancement in marine monitoring, deployment of various applications, and ocean surveillance. The UWSN is an attractive field for both researchers and the industrial side. Due to the harsh underwater environment, own capabilities, open acoustic channel, it's also vulnerable to malicious attacks and threats. Attackers can easily take advantage of these characteristics to steal the data between the source and destination. Many review articles are addressed some of the security attacks and Taxonomy of the Underwater Wireless Sensor Networks. In this study, we have briefly addressed the Taxonomy of the UWSNs from the most recent research articles related to the well-known research databases. This paper also discussed the security threats on each layer of the Underwater Wireless sensor networks. This study will help the researcher’s design the routing protocols to cover the known security threats and help industries manufacture the devices to observe these threats and security issues

Cooperative Authentication in Underwater Acoustic Sensor Networks

With the growing use of underwater acoustic communications (UWAC) for both industrial and military operations, there is a need to ensure communication security. A particular challenge is represented by underwater acoustic networks (UWANs), which are often left unattended over long periods of time. Currently, due to physical and performance limitations, UWAC packets rarely include encryption, leaving the UWAN exposed to external attacks faking legitimate messages. In this paper, we propose a new algorithm for message authentication in a UWAN setting. We begin by observing that, due to the strong spatial dependency of the underwater acoustic channel, an attacker can attempt to mimic the channel associated with the legitimate transmitter only for a small set of receivers, typically just for a single one. Taking this into account, our scheme relies on trusted nodes that independently help a sink node in the authentication process. For each incoming packet, the sink fuses beliefs evaluated by the trusted nodes to reach an authentication decision. These beliefs are based on estimated statistical channel parameters, chosen to be the most sensitive to the transmitter-receiver displacement. Our simulation results show accurate identification of an attacker's packet. We also report results from a sea experiment demonstrating the effectiveness of our approach.Comment: Author version of paper accepted for publication in the IEEE Transactions on Wireless Communication

AIDPS:Adaptive Intrusion Detection and Prevention System for Underwater Acoustic Sensor Networks

Underwater Acoustic Sensor Networks (UW-ASNs) are predominantly used for underwater environments and find applications in many areas. However, a lack of security considerations, the unstable and challenging nature of the underwater environment, and the resource-constrained nature of the sensor nodes used for UW-ASNs (which makes them incapable of adopting security primitives) make the UW-ASN prone to vulnerabilities. This paper proposes an Adaptive decentralised Intrusion Detection and Prevention System called AIDPS for UW-ASNs. The proposed AIDPS can improve the security of the UW-ASNs so that they can efficiently detect underwater-related attacks (e.g., blackhole, grayhole and flooding attacks). To determine the most effective configuration of the proposed construction, we conduct a number of experiments using several state-of-the-art machine learning algorithms (e.g., Adaptive Random Forest (ARF), light gradient-boosting machine, and K-nearest neighbours) and concept drift detection algorithms (e.g., ADWIN, kdqTree, and Page-Hinkley). Our experimental results show that incremental ARF using ADWIN provides optimal performance when implemented with One-class support vector machine (SVM) anomaly-based detectors. Furthermore, our extensive evaluation results also show that the proposed scheme outperforms state-of-the-art bench-marking methods while providing a wider range of desirable features such as scalability and complexity