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VTrack: Accurate, Energy-aware Road Traffic Delay Estimation Using Mobile Phones
"... Traffic delays and congestion are a major source of inefficiency, wasted fuel, and commuter frustration. Measuring and localizing these delays, and routing users around them, is an important step towards reducing the time people spend stuck in traffic. As others have noted, the proliferation of comm ..."
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Cited by 119 (7 self)
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Traffic delays and congestion are a major source of inefficiency, wasted fuel, and commuter frustration. Measuring and localizing these delays, and routing users around them, is an important step towards reducing the time people spend stuck in traffic. As others have noted, the proliferation of commodity smartphones that can provide location estimates using a variety of sensors—GPS, WiFi, and/or cellular triangulation— opens up the attractive possibility of using position samples from drivers ’ phones to monitor traffic delays at a fine spatiotemporal granularity. This paper presents VTrack, a system for travel time estimation using this sensor data that addresses two key challenges: energy consumption and sensor unreliability. While GPS provides highly accurate location estimates, it has several limitations: some phones don’t have GPS at
Vanish: Increasing Data Privacy with Self-Destructing Data
"... Today’s technical and legal landscape presents formidable challenges to personal data privacy. First, our increasing reliance on Web services causes personal data to be cached, copied, and archived by third parties, often without our knowledge or control. Second, the disclosure of private data has b ..."
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Cited by 93 (12 self)
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Today’s technical and legal landscape presents formidable challenges to personal data privacy. First, our increasing reliance on Web services causes personal data to be cached, copied, and archived by third parties, often without our knowledge or control. Second, the disclosure of private data has become commonplace due to carelessness, theft, or legal actions. Our research seeks to protect the privacy of past, archived data — such as copies of emails maintained by an email provider — against accidental, malicious, and legal attacks. Specifically, we wish to ensure that all copies of certain data become unreadable after a userspecified time, without any specific action on the part of a user, and even if an attacker obtains both a cached copy of that data and the user’s cryptographic keys and passwords. This paper presents Vanish, a system that meets this challenge through a novel integration of cryptographic techniques with global-scale, P2P, distributed hash tables (DHTs). We implemented a proof-of-concept Vanish prototype to use both the million-plus-node Vuze Bit-Torrent DHT and the restricted-membership OpenDHT. We evaluate experimentally and analytically the functionality, security, and performance properties of Vanish, demonstrating that it is practical to use and meets the privacy-preserving goals described above. We also describe two applications that we prototyped on Vanish: a Firefox plugin for Gmail and other Web sites and a Vanishing File application. 1
VPriv: Protecting Privacy in Location-Based Vehicular Services
"... A variety of location-based vehicular services are currently being woven into the national transportation infrastructure in many countries. These include usage- or congestion-based road pricing, traffic law enforcement, traffic monitoring, “pay-as-you-go ” insurance, and vehicle safety systems. Alth ..."
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Cited by 46 (7 self)
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A variety of location-based vehicular services are currently being woven into the national transportation infrastructure in many countries. These include usage- or congestion-based road pricing, traffic law enforcement, traffic monitoring, “pay-as-you-go ” insurance, and vehicle safety systems. Although such applications promise clear benefits, there are significant potential violations of the location privacy of drivers under standard implementations (i.e., GPS monitoring of cars as they drive, surveillance cameras, and toll transponders). In this paper, we develop and evaluate VPriv, a system that can be used by several such applications without violating the location privacy of drivers. The starting point is the observation that in many applications, some centralized server needs to compute a function of a user’s path—a list of time-position tuples. VPriv provides two components: 1) the first practical protocol to compute path functions for various kinds of tolling, speed and delay estimation, and insurance calculations in a way that does not reveal anything more than the result of the function to the server, and 2) an out-of-band enforcement mechanism using random spot checks that allows the server and application to handle misbehaving users. Our implementation and experimental evaluation of VPriv shows that a modest infrastructure of a few multi-core PCs can easily serve 1 million cars. Using analysis and simulation based on real vehicular data collected over one year from the CarTel project’s testbed of 27 taxis running in the Boston area, we demonstrate that VPriv is resistant to a range of possible attacks. 1
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Sampling-based Motion Planning with Deterministic µ-Calculus Specifications
"... Sampling-based motion planning with deterministic u-calculus specifications ..."
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Sampling-based motion planning with deterministic u-calculus specifications
