2,129 research outputs found
Guest Editorial: Special issue on software engineering for mobile applications
Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch
Detecting Fake Reviews: Just a Matter of Data
Along with the ever-increasing portfolio of products online, the incentive for market participants to write fake reviews to gain a competitive edge has increased as well. This article demonstrates the effectiveness of using different combinations of spam detection features to detect fake reviews other than the review-based features typically used. Using a spectrum of feature sets offers greater accuracy in identifying fake reviews than using review-based features only, and using a machine learning algorithm for classification and different amounts of feature sets further elucidates the difference in performance. Results compared by benchmarking show that applying a technique prioritizing feature importance benefits from prioritizing features from multiple feature sets and that creating feature sets based on reviews, reviewers and product data can achieve the greatest accuracy
Defending against Sybil Devices in Crowdsourced Mapping Services
Real-time crowdsourced maps such as Waze provide timely updates on traffic,
congestion, accidents and points of interest. In this paper, we demonstrate how
lack of strong location authentication allows creation of software-based {\em
Sybil devices} that expose crowdsourced map systems to a variety of security
and privacy attacks. Our experiments show that a single Sybil device with
limited resources can cause havoc on Waze, reporting false congestion and
accidents and automatically rerouting user traffic. More importantly, we
describe techniques to generate Sybil devices at scale, creating armies of
virtual vehicles capable of remotely tracking precise movements for large user
populations while avoiding detection. We propose a new approach to defend
against Sybil devices based on {\em co-location edges}, authenticated records
that attest to the one-time physical co-location of a pair of devices. Over
time, co-location edges combine to form large {\em proximity graphs} that
attest to physical interactions between devices, allowing scalable detection of
virtual vehicles. We demonstrate the efficacy of this approach using
large-scale simulations, and discuss how they can be used to dramatically
reduce the impact of attacks against crowdsourced mapping services.Comment: Measure and integratio
- …