PADS: Practical Attestation for Highly Dynamic Swarm Topologies

Remote attestation protocols are widely used to detect device configuration (e.g., software and/or data) compromise in Internet of Things (IoT) scenarios. Unfortunately, the performances of such protocols are unsatisfactory when dealing with thousands of smart devices. Recently, researchers are focusing on addressing this limitation. The approach is to run attestation in a collective way, with the goal of reducing computation and communication. Despite these advances, current solutions for attestation are still unsatisfactory because of their complex management and strict assumptions concerning the topology (e.g., being time invariant or maintaining a fixed topology). In this paper, we propose PADS, a secure, efficient, and practical protocol for attesting potentially large networks of smart devices with unstructured or dynamic topologies. PADS builds upon the recent concept of non-interactive attestation, by reducing the collective attestation problem into a minimum consensus one. We compare PADS with a state-of-the art collective attestation protocol and validate it by using realistic simulations that show practicality and efficiency. The results confirm the suitability of PADS for low-end devices, and highly unstructured networks.Comment: Submitted to ESORICS 201

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

Intrusion-aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.Comment: 19 pages, 7 figure