Secure and Efficient Sharing Aggregation Scheme for Data Protection in WSNs

International audienceWireless sensor networks (WSNs) are omnipresent in a multitude of applications. One of the important common requirements of these applications is the data security. Indeed, the exchanged data in WSNs are often considered as a preferred target, which can be a subject of several threats, such as eavesdropping , replay, falsification, alteration, etc. Another important common requirement of WSNs applications is data aggregation. Indeed, the limitations of such networks in terms of energy, bandwidth and storage accentuate the need of data aggregation. In this paper, we address these two issues. We propose a new efficient approach for data integrity and credibility protection for WSNs, while ensuring the data aggregation. We consider a cluster-based network architecture, where sensor nodes are equally distributed in clusters. Each sensor node is in charge to deliver one bit of the sensed data and at the same time observe the remaining parts through a parity control based encryption approach. In this manner, the sensed data could be effectively and securely controlled with a low overhead compared to the classical aggregation approaches, where all the nodes transmit individually the sensed data. To validate the proposed protocol we have simulated it using the simulator CupCarbon and in order to evaluate its efficiency in terms of energy, we have developed a prototype with the TelosB platform, where the obtained results show that our method is less energy consuming

Toward a lightweight machine learning based solution against cyber-intrusions for IoT

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Matrix-based key management scheme for IoT networks

International audienceThe key management is the central element of network security. In fact, key distribution is necessary for securing applications in the context of Internet of Things (IoT). However, existing key management protocols are not directly applicable on IoT due, among other things, to severe and high resource constraints of some devices that make up the IoT network. Therefore, it is necessary that the proposed key management protocols takes in charge these constraints. In this paper, we propose a new lightweight Matrix based key management protocol for Iot network. The formal verification tool AVISPA has been used in order to check these security properties like authentication, integrity and secrecy. Security and performance analysis show that the proposed scheme protects user's sensitive data from several types of attacks by achieving secure end-to-end communication, and is suitable for resource-limited networks

Secure and lightweight remote patient authentication scheme with biometric inputs for mobile healthcare environments

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Robust multimodal biometric authentication on IoT device through ear shape and arm gesture

International audienceNowadays, authentication is required for both physical access to buildings and internal access to computers and systems. Biometrics are one of the emerging technologies used to protect these highly sensitive structures. However, biometric systems based on a single trait enclose several problems such as noise sensitivity and vulnerability to spoof attacks. In this regard, we present in this paper a fully unobtrusive and robust multimodal authentication system that automatically authenticates a user by the way he/she answers his/her phone, after extracting ear and arm gesture biometric modalities from this single action. To deal the challenges facing ear and arm gesture authentication systems in real-world applications, we propose a new method based on image fragmentation that makes the ear recognition more robust in relation to occlusion. The ear feature extraction process has been made locally using Local Phase Quantization (LPQ) in order to get robustness with respect to pose and illumination variation. We also propose a set of four statistical metrics to extract features from arm gesture signals. The two modalities are combined on score-level using a weighted sum. In order to evaluate our contribution, we conducted a set of experiments to demonstrate the contribution of each of the two biometrics and the advantage of their fusion on the overall performance of the system. The multimodal biometric system achieves an equal error rate (EER) of 5.15%

Methods for detecting and removing ocular artifacts from EEG signals in drowsy driving warning systems: A survey

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Autonomous Vehicle Security: Literature Review of Real Attack Experiments

International audienceWith recent advances in technology to bring about smarter cities, significant efforts are put forth to enhance living standards through efficient infrastructure and services. Smart mobility is a core aspect of the Smart City concept, looking for the design of smart solutions to the challenging urban traffic issues faced by modern cities. It is envisioned that vehicle automation will come to change our lives and society soon. Autonomous vehicles have been around for years now, driving around streets to test their ability to navigate real-world driving environments. In the long term, they are expected to improve road safety and increase citizens mobility, providing a suitable mode of transport for people who cannot drive. Although the technology is not yet mature, it has aroused the interest of both academia and industry to inherent security challenges that must be addressed before large-scale adoption. There has been a host of research efforts on the security of autonomous vehicles in terms of vulnerabilities, attacks and potential defenses. In this paper, we propose a novel taxonomy of attack surfaces in autonomous vehicles. Based on our taxonomy, we review a selection of relevant and recent research on real attack experiments carried out on many components and automated driving systems. We also perform threat modeling and risk assessment to support security aware design of autonomous vehicles

A Privacy-Preserving Authentication Model Based on Anonymous Certificates in IoT

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Efficient and Lightweight Polynomial-based Key Management Scheme for Dynamic Networks

International audienceWireless sensor networks and Internet of Things (IoT) are part of dynamic networks as new nodes can join while existing members can leave the system at any time. These networks mainly suffer from severe resource constraints like energy, storage and computation, which makes securing communications between nodes a real challenge. Several key establishment protocols have been proposed in the literature. Some of them are based on symmetric polynomials. However, the latter solutions have some limitations, such as the resilience to node capture attacks as well as the storage and computation overheads that are high for constrained nodes. In this paper, we propose a lightweight polynomial-based key management scheme for dynamic networks. The proposed scheme allows nodes to be able to establish secure communications between them, and ensures dynamism by supporting node addition and deletion after the setup phase. It also resists to node capture attack. The performance evaluation shows that our scheme reduces both the storage and computation overheads when compared to other related polynomial-based protocols