From Map to Dist: the Evolution of a Large-Scale Wlan Monitoring System

The edge of the Internet is increasingly becoming wireless. Therefore, monitoring the wireless edge is important to understanding the security and performance aspects of the Internet experience. We have designed and implemented a large-scale WLAN monitoring system, the Distributed Internet Security Testbed (DIST), at Dartmouth College. It is equipped with distributed arrays of “sniffers” that cover 210 diverse campus locations and more than 5,000 users. In this paper, we describe our approach, designs and solutions for addressing the technical challenges that have resulted from efficiency, scalability, security, and management perspectives. We also present extensive evaluation results on a production network, and summarize the lessons learned

Secure and privacy-aware proxy mobile IPv6 protocol for vehicle-to-grid networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity

Multicast Mobility in Mobile IP Version 6 (MIPv6) : Problem Statement and Brief Survey

Publisher PD

Secure and privacy-aware proxy mobile IPv6 protocol for vehicle-to-grid networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity

Secure and Privacy-Aware Proxy Mobile IPv6 Protocol for Vehicle-to-Grid Networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity

Design of an Automotive IoT Device to Improve Driver Fault Detection Through Road Class Estimation

Unsafe driver habits pose a serious threat to all vehicles on the road. This thesis outlines the development of an automotive IoT device capable of monitoring and reporting adverse driver habits to mitigate the occurrence of unsafe practices. The driver habits targeted are harsh braking, harsh acceleration, harsh cornering, speeding and over revving the vehicle. With the intention of evaluating and expanding upon the industry method of fault detection, a working prototype is designed to handle initialization, data collection, vehicle state tracking, fault detection and communication. A method of decoding the broadcasted messages on the vehicle bus is presented and unsafe driver habits are detected using static limits. An analysis of the initial design’s performance revealed that the industry method of detecting faults fails to account for the vehicle’s speed and is unable to detect faults on all roadways. A framework for analyzing fault profiles at varying speeds is presented and yields the relationship between fault magnitude and speed. A method of detecting the type of road driven was developed to dynamically assign fault limits while the vehicle traveled on a highway, city street or in traffic. The improved design correctly detected faults along all types of roads and proved to greatly expand upon the current method of fault detection used by the automotive IoT industry today

ANGELAH: A Framework for Assisting Elders At Home

The ever growing percentage of elderly people within modern societies poses welfare systems under relevant stress. In fact, partial and progressive loss of motor, sensorial, and/or cognitive skills renders elders unable to live autonomously, eventually leading to their hospitalization. This results in both relevant emotional and economic costs. Ubiquitous computing technologies can offer interesting opportunities for in-house safety and autonomy. However, existing systems partially address in-house safety requirements and typically focus on only elder monitoring and emergency detection. The paper presents ANGELAH, a middleware-level solution integrating both ”elder monitoring and emergency detection” solutions and networking solutions. ANGELAH has two main features: i) it enables efficient integration between a variety of sensors and actuators deployed at home for emergency detection and ii) provides a solid framework for creating and managing rescue teams composed of individuals willing to promptly assist elders in case of emergency situations. A prototype of ANGELAH, designed for a case study for helping elders with vision impairments, is developed and interesting results are obtained from both computer simulations and a real-network testbed

Large-scale Wireless Local-area Network Measurement and Privacy Analysis

The edge of the Internet is increasingly becoming wireless. Understanding the wireless edge is therefore important for understanding the performance and security aspects of the Internet experience. This need is especially necessary for enterprise-wide wireless local-area networks (WLANs) as organizations increasingly depend on WLANs for mission- critical tasks. To study a live production WLAN, especially a large-scale network, is a difficult undertaking. Two fundamental difficulties involved are (1) building a scalable network measurement infrastructure to collect traces from a large-scale production WLAN, and (2) preserving user privacy while sharing these collected traces to the network research community. In this dissertation, we present our experience in designing and implementing one of the largest distributed WLAN measurement systems in the United States, the Dartmouth Internet Security Testbed (DIST), with a particular focus on our solutions to the challenges of efficiency, scalability, and security. We also present an extensive evaluation of the DIST system. To understand the severity of some potential trace-sharing risks for an enterprise-wide large-scale wireless network, we conduct privacy analysis on one kind of wireless network traces, a user-association log, collected from a large-scale WLAN. We introduce a machine-learning based approach that can extract and quantify sensitive information from a user-association log, even though it is sanitized. Finally, we present a case study that evaluates the tradeoff between utility and privacy on WLAN trace sanitization