Towards Multiple Pattern Type Privacy Protection in Complex Event Processing Through Event Obfuscation Strategies

Autor:	Saravana Murthy Palanisamy
Rok vydání:	2020
Předmět:	Obfuscation (software) Negation Computer science Mechanism (biology) Event (computing) Quality of service Complex event processing Computer security computer.software_genre computer Private information retrieval Conjunction (grammar)
Zdroj:	Lecture Notes in Computer Science ISBN: 9783030661717 DPM/CBT@ESORICS
DOI:	10.1007/978-3-030-66172-4_11
Popis:	For a Complex Event Processing (CEP) system to be widely accepted, mitigating leaks of private information is paramount. In CEP systems, often private information are revealed through patterns instead of single events. There are very few mechanisms that protect privacy at the level of patterns. However these mechanisms consider only sequential patterns, one of the common pattern types in CEP. But this is highly confined since there are other common pattern types like conjunction, negation etc. So as a first step towards multiple pattern type privacy protection, in this paper we present a hybrid pattern level privacy protection mechanism that considers three common pattern types: sequence, conjunction and negation. Our approach is based on three event obfuscation strategies: event reordering, event suppression and introduction of fake events to conceal private patterns on the one hand, while minimizing impact on useful non-sensitive information required by IoT services to provide a certain Quality of Service (QoS) on the other hand. Our evaluations over real-world datasets show that our algorithms are effective in maximizing QoS while preserving privacy.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::078a0679eb5e6b76a8eac9e825335dad https://doi.org/10.1007/978-3-030-66172-4_11 Zobrazit plný text záznamu