SHIELD: a data verification framework for participatory sensing systems
SHIELD: a data verification framework for participatory sensing systems
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SHIELD：参与式传感系统的数据验证框架
DOI：
10.1145/2766498.2766503
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Panos Papadimitratos
中科院分区：
文献类型：
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作者：
S. Gisdakis;Thanassis Giannetsos;Panos Papadimitratos
PS系统的开放性使得它们容易受到恶意用户的攻击，这些恶意用户可能会污染测量收集过程，试图降低PS系统数据的质量，并总体上降低其有用性。减轻这种敌对行为是困难的。密码保护、身份验证、授权和访问控制可以提供帮助，但它们不能完全解决问题。来自错误内部人员（具有证书的参与者）的报告可以智能地针对过程，迫使PS系统偏离实际感测到的现象。过滤出这些错误的报告是具有挑战性的，几乎没有参与者的可信度，动态变化的现象，以及可能大量的受损设备的先验知识。本文提出了SHIELD，一种新的数据验证框架PS系统，可以补充任何安全架构。盾牌处理现有的，矛盾的证据，有效地分类传入的报告，并有效地分离和拒绝那些有缺陷的。因此，即使45%的报告是错误的，被认为是正确的数据也可以准确地代表感知到的现象，由协调的对手智能选择，并在系统的覆盖区域内进行最佳定位。
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.