Shield

Abstract

The openness of PS systems renders them vulnerable to malicious users that can pollute the measurement collection process, in an attempt to degrade the PS system data and, overall, its usefulness. Mitigating such adversarial behavior is hard. Cryptographic protection, authentication, authorization, and access control can help but they do not fully address the problem. Reports from faulty insiders (participants with credentials) can target the process intelligently, forcing the PS system to deviate from the actual sensed phenomenon. Filtering out those faulty reports is challenging, with practically no prior knowledge on the participants' trustworthiness, dynamically changing phenomena, and possibly large numbers of compromised devices. This paper proposes SHIELD, a novel data verification framework for PS systems that can complement any security architecture. SHIELD handles available, contradicting evidence, classifies efficiently incoming reports, and effectively separates and rejects those that are faulty. As a result, the deemed correct data can accurately represent the sensed phenomena, even when 45% of the reports are faulty, intelligently selected by coordinated adversaries and targeted optimally across the system's coverage area.

Recurring verification of interaction authenticity within bluetooth networks

“…The overarching objective of our work (the verification of authentic interactions within WPANs) is largely motivated by past work in authentication [8,12,18,22,27,31,[36][37][38][40][41][42]. Authentication is a process to verify (i.e., establish the truth of) an attribute value claimed by or for a system entity [50].…”

Participatory location fingerprinting through stationary crowd in a public or commercial indoor environment

“…The rationale is that confidence can be estimated based on the conditional probability of occurrence of a particular traffic event at a particular location given that supporting reports have been generated. Also, Gisdakis, Giannetsos and Papadimitratos [9] have proposed a comprehensive framework that is agnostic of the cause of a faulty measurement. Each report is transformed into a probability mass, so as to compute the hypothesis with the maximum belief; the belief corresponding to this hypothesis; and the local conflict of the probability mass, as per Dempster-Shafer Theory.…”

Hardened Registration Process for Participatory Sensing

“…Providers or between Service Providers and Queriers) or exploit the vulnerability of the openness of the participatory sensing system by polluting the data collection to degrade the participatory sensing system. Cryptographic protection, authentication, authorization and state-of-the-art techniques such as SHIELD framework [17] that combine evidence handling and data-mining techniques to identify and filter out malicious contributions are effective solutions to ensure the confidentiality and integrity of the participatory sensing system.…”