Anomaly Detection in UASN Localization Based on Time Series Analysis and Fuzzy Logic

[EN] Underwater acoustic sensor network (UASN) offers a promising solution for exploring underwater resources remotely. For getting a better understanding of sensed data, accurate localization is essential. As the UASN acoustic channel is open and the environment is hostile, the risk of malicious activities is very high, particularly in time-critical military applications. Since the location estimation with false data ends up in wrong positioning, it is necessary to identify and ignore such data to ensure data integrity. Therefore, in this paper, we propose a novel anomaly detection system for UASN localization. To minimize computational power and storage, we designed separate anomaly detection schemes for sensor nodes and anchor nodes. We propose an auto-regressive prediction-based scheme for detecting anomalies at sensor nodes. For anchor nodes, a fuzzy inference system is designed to identify the presence of anomalous behavior. The detection schemes are implemented at every node for enabling identification of multiple and duplicate anomalies at its origin. We simulated the network, modeled anomalies and analyzed the performance of detection schemes at anchor nodes and sensor nodes. The results indicate that anomaly detection systems offer an acceptable accuracy with high true positive rate and F-Score.Das, AP.; Thampi, SM.; Lloret, J. (2020). Anomaly Detection in UASN Localization Based on Time Series Analysis and Fuzzy Logic. Mobile Networks and Applications (Online). 25(1):55-67. https://doi.org/10.1007/s11036-018-1192-y556725

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

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Secure Neighbor Discovery and Ranging in Wireless Networks

This thesis addresses the security of two fundamental elements of wireless networking: neighbor discovery and ranging. Neighbor discovery consists in discovering devices available for direct communication or in physical proximity. Ranging, or distance bounding, consists in measuring the distance between devices, or providing an upper bound on this distance. Both elements serve as building blocks for a variety of services and applications, notably routing, physical access control, tracking and localization. However, the open nature of wireless networks makes it easy to abuse neighbor discovery and ranging, and thereby compromise overlying services and applications. To prevent this, numerous works proposed protocols that secure these building blocks. But two aspects crucial for the security of such protocols have received relatively little attention: formal verification and attacks on the physical-communication-layer. They are precisely the focus of this thesis. In the first part of the thesis, we contribute a formal analysis of secure communication neighbor discovery protocols. We build a formal model that captures salient characteristics of wireless systems such as node location, message propagation time and link variability, and we provide a specification of secure communication neighbor discovery. Then, we derive an impossibility result for a general class of protocols we term "time-based protocols", stating that no such protocol can provide secure communication neighbor discovery. We also identify the conditions under which the impossibility result is lifted. We then prove that specific protocols in the time-based class (under additional conditions) and specific protocols in a class we term "time- and location-based protocols," satisfy the neighbor discovery specification. We reinforce these results by mechanizing the model and the proofs in the theorem prover Isabelle. In the second part of the thesis, we explore physical-communication-layer attacks that can seemingly decrease the message arrival time without modifying its content. Thus, they can circumvent time-based neighbor discovery protocols and distance bounding protocols. (Indeed, they violate the assumptions necessary to prove protocol correctness in the first part of the thesis.) We focus on Impulse Radio Ultra-Wideband, a physical layer technology particularly well suited for implementing distance bounding, thanks to its ability to perform accurate indoor ranging. First, we adapt physical layer attacks reported in prior work to IEEE 802.15.4a, the de facto standard for Impulse Radio, and evaluate their performance. We show that an adversary can achieve a distance-decrease of up to hundreds of meters with an arbitrarily high probability of success, with only a minor cost in terms of transmission power (few dB). Next, we demonstrate a new attack vector that disrupts time-of-arrival estimation algorithms, in particular those designed to be precise. The distance-decrease achievable by this attack vector is in the order of the channel spread (order of 10 meters in indoor environments). This attack vector can be used in previously reported physical layer attacks, but it also creates a new type of external attack based on malicious interference. We demonstrate that variants of the malicious interference attack are much easier to mount than the previously reported external attack. We also provide design guidelines for modulation schemes and devise receiver algorithms that mitigate physical layer attacks. These countermeasures allow the system designer to trade off security, ranging precision and cost in terms of transmission power and packet length

Who wrote this scientific text?

The IEEE bibliographic database contains a number of proven duplications with indication of the original paper(s) copied. This corpus is used to test a method for the detection of hidden intertextuality (commonly named "plagiarism"). The intertextual distance, combined with the sliding window and with various classification techniques, identifies these duplications with a very low risk of error. These experiments also show that several factors blur the identity of the scientific author, including variable group authorship and the high levels of intertextuality accepted, and sometimes desired, in scientific papers on the same topic

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa

L'intertextualité dans les publications scientifiques

La base de données bibliographiques de l'IEEE contient un certain nombre de duplications avérées avec indication des originaux copiés. Ce corpus est utilisé pour tester une méthode d'attribution d'auteur. La combinaison de la distance intertextuelle avec la fenêtre glissante et diverses techniques de classification permet d'identifier ces duplications avec un risque d'erreur très faible. Cette expérience montre également que plusieurs facteurs brouillent l'identité de l'auteur scientifique, notamment des collectifs de chercheurs à géométrie variable et une forte dose d'intertextualité acceptée voire recherchée