An embedded sensor node microcontroller with crypto-processors

Wireless sensor network applications range from industrial automation and control, agricultural and environmental protection, to surveillance and medicine. In most applications, data are highly sensitive and must be protected from any type of attack and abuse. Security challenges in wireless sensor networks are mainly defined by the power and computing resources of sensor devices, memory size, quality of radio channels and susceptibility to physical capture. In this article, an embedded sensor node microcontroller designed to support sensor network applications with severe security demands is presented. It features a low power 16-bitprocessor core supported by a number of hardware accelerators designed to perform complex operations required by advanced crypto algorithms. The microcontroller integrates an embedded Flash and an 8-channel 12-bit analog-to-digital converter making it a good solution for low-power sensor nodes. The article discusses the most important security topics in wireless sensor networks and presents the architecture of the proposed hardware solution. Furthermore, it gives details on the chip implementation, verification and hardware evaluation. Finally, the chip power dissipation and performance figures are estimated and analyzed

MobChain:Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus

Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). However, a user’s full control over a smart device can allow tampering of the location proof. Witness-oriented location proof systems (LPS) have emerged to resist the generation of false proofs and mitigate collusion attacks. However, witness-oriented LPS are still susceptible to three-way collusion attacks (involving the user, location authority, and the witness). To overcome the threat of three-way collusion in existing schemes, we introduce a decentralized consensus protocol called MobChain in this paper. In this scheme the selection of a witness and location authority is achieved through a distributed consensus of nodes in an underlying P2P network that establishes a private blockchain. The persistent provenance data over the blockchain provides strong security guarantees; as a result, the forging and manipulation of location becomes impractical. MobChain provides secure location provenance architecture, relying on decentralized decision making for the selection of participants of the protocol thereby addressing the three-way collusion problem. Our prototype implementation and comparison with the state-of-the-art solutions show that MobChain is computationally efficient and highly available while improving the security of LPS

Trustworthy Edge Machine Learning: A Survey

The convergence of Edge Computing (EC) and Machine Learning (ML), known as Edge Machine Learning (EML), has become a highly regarded research area by utilizing distributed network resources to perform joint training and inference in a cooperative manner. However, EML faces various challenges due to resource constraints, heterogeneous network environments, and diverse service requirements of different applications, which together affect the trustworthiness of EML in the eyes of its stakeholders. This survey provides a comprehensive summary of definitions, attributes, frameworks, techniques, and solutions for trustworthy EML. Specifically, we first emphasize the importance of trustworthy EML within the context of Sixth-Generation (6G) networks. We then discuss the necessity of trustworthiness from the perspective of challenges encountered during deployment and real-world application scenarios. Subsequently, we provide a preliminary definition of trustworthy EML and explore its key attributes. Following this, we introduce fundamental frameworks and enabling technologies for trustworthy EML systems, and provide an in-depth literature review of the latest solutions to enhance trustworthiness of EML. Finally, we discuss corresponding research challenges and open issues.Comment: 27 pages, 7 figures, 10 table

Monitoring the health and integrity of Wireless Sensor Networks

Wireless Sensor Networks (WSNs) will play a major role in the Internet of Things collecting the data that will support decision-making and enable the automation of many applications. Nevertheless, the introduction of these devices into our daily life raises serious concerns about their integrity. Therefore, at any given point, one must be able to tell whether or not a node has been compromised. Moreover, it is crucial to understand how the compromise of a particular node or set of nodes may affect the network operation. In this thesis, we present a framework to monitor the health and integrity of WSNs that allows us to detect compromised devices and comprehend how they might impact a network’s performance. We start by investigating the use of attestation to identify malicious nodes and advance the state of the art by exploring limitations of existing mechanisms. Firstly, we tackle effectiveness and scalability by combining attestation with measurements inspection and show that the right combination of both schemes can achieve high accuracy whilst significantly reducing power consumption. Secondly, we propose a novel stochastic software-based attestation approach that relaxes a fundamental and yet overlooked assumption made in the literature significantly reducing time and energy consumption while improving the detection rate of honest devices. Lastly, we propose a mathematical model to represent the health of a WSN according to its abilities to perform its functions. Our model combines the knowledge regarding compromised nodes with additional information that quantifies the importance of each node. In this context, we propose a new centrality measure and analyse how well existing metrics can rank the importance each sensor node has on the network connectivity. We demonstrate that while no measure is invariably better, our proposed metric outperforms the others in the vast majority of cases.Open Acces

Intrusion Prevention and Detection in Wireless Sensor Networks

The broadcast nature of the transmission medium in wireless sensor networks makes information more vulnerable than in wired applications. In this dissertation we first propose a distributed, deterministic key management protocol designed to satisfy authentication and confidentiality, without the need of a key distribution center. Next we propose Scatter, a secure code authentication scheme for efficient reprogramming sensor networks. Scatter avoids the use of Elliptic Key Cryptography and manages to surpass all previous attempts for secure code dissemination in terms of energy consumption and time efficiency. Next we introduce the problem of intrusion detection in sensor networks. We define the problem formally based on a generic system model and we prove a necessary and sufficient condition for successful detection of the attacker. Finally we present the architecture and implementation of an intrusion detection system which is based on a distributed architecture and it is lightweight enough to run on the nodes