Preserving Privacy and Quality of Service in Complex Event Processing through Event Reordering
| Autor: | Kurt Rothermel, Saravana Murthy Palanisamy, Frank Dürr, Muhammad Adnan Tariq |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science Event (computing) Quality of service Automotive industry Complex event processing Access control 02 engineering and technology 020204 information systems 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) 020201 artificial intelligence & image processing The Internet business Private information retrieval Computer network |
| Zdroj: | DEBS |
| DOI: | 10.1145/3210284.3210296 |
| Popis: | The Internet of Things (IoT) envisions a huge number of networked sensors connected to the internet. These sensors collect large streams of data which serve as input to wide range of IoT applications and services such as e-health, e-commerce, and automotive services. Complex Event Processing (CEP) is a powerful tool that transforms streams of raw sensor data into meaningful information required by these IoT services. Often these streams of data collected by sensors carry privacy-sensitive information about the user. Thus, protecting privacy is of paramount importance in IoT services based on CEP.In this paper we present a novel pattern-level access control mechanism for CEP based services that conceals private information while minimizing the impact on useful non-sensitive information required by the services to provide a certain quality of service (QoS). The idea is to reorder events from the event stream to conceal privacy-sensitive event patterns while preserving non-privacy sensitive event patterns to maximize QoS. We propose two approaches, namely an ILP-based approach and a graph-based approach, calculating an optimal reordering of events. Our evaluation results show that these approaches are effective in concealing private patterns without significant loss of QoS. |
| Databáze: | OpenAIRE |
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