SyLPEnIoT: Symmetric Lightweight Predicate Encryption for Data Privacy Applications in IoT Environments

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)


Privacy preserving mechanisms are essential for protecting data in IoT environments. This is particularly challenging as IoT environments often contain heterogeneous resource-constrained devices. One method for protecting privacy is to encrypt data with a pattern or metadata. To prevent information leakage, an evaluation using the pattern must be performed before the data can be retrieved. However, the computational costs associated with typical privacy preserving mechanisms can be costly. This makes such methods ill-suited for resource-constrained devices, as the high energy consumption will quickly drain the battery. This work solves this challenging problem by proposing SyLPEnIoT – Symmetric Lightweight Predicate Encryption for IoT, which is lightweight and efficient compared with existing encryption schemes. Based on the bitwise-XOR operation, we use this basic gate to construct a scheme that transfers encrypted data onto more powerful machines. Furthermore, for resource-constrained IoT devices, the requester can authenticate devices at different levels based on the type of communication. SyLPEnIoT was meticulously designed to run on a gamut of IoT devices, including ultra low-power sensors that are constrained in terms of CPU processing, memory and energy consumption, which are widely deployed in real IoT ecosystems.

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12973 LNCS

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