Andrea Continella

2papers

2 Papers

CRJun 1, 2021
Toward a Secure Crowdsourced Location Tracking System

Chinmay Garg, Aravind Machiry, Andrea Continella et al.

Low-energy Bluetooth devices have become ubiquitous and widely used for different applications. Among these, Bluetooth trackers are becoming popular as they allow users to track the location of their physical objects. To do so, Bluetooth trackers are often built-in within other commercial products connected to a larger crowdsourced tracking system. Such a system, however, can pose a threat to the security and privacy of the users, for instance, by revealing the location of a user's valuable object. In this paper, we introduce a set of security properties and investigate the state of commercial crowdsourced tracking systems, which present common design flaws that make them insecure. Leveraging the results of our investigation, we propose a new design for a secure crowdsourced tracking system (SECrow), which allows devices to leverage the benefits of the crowdsourced model without sacrificing security and privacy. Our preliminary evaluation shows that SECrow is a practical, secure, and effective crowdsourced tracking solution

CRApr 28, 2020
A Retrospective Analysis of User Exposure to (Illicit) Cryptocurrency Mining on the Web

Ralph Holz, Diego Perino, Matteo Varvello et al.

In late 2017, a sudden proliferation of malicious JavaScript was reported on the Web: browser-based mining exploited the CPU time of website visitors to mine the cryptocurrency Monero. Several studies measured the deployment of such code and developed defenses. However, previous work did not establish how many users were really exposed to the identified mining sites and whether there was a real risk given common user browsing behavior. In this paper, we present a retroactive analysis to close this research gap. We pool large-scale, longitudinal data from several vantage points, gathered during the prime time of illicit cryptomining, to measure the impact on web users. We leverage data from passive traffic monitoring of university networks and a large European ISP, with suspected mining sites identified in previous active scans. We corroborate our results with data from a browser extension with a large user base that tracks site visits. We also monitor open HTTP proxies and the Tor network for malicious injection of code. We find that the risk for most Web users was always very low, much lower than what deployment scans suggested. Any exposure period was also very brief. However, we also identify a previously unknown and exploited attack vector on mobile devices.