MemEnc: A Lightweight, Low-Power, and Transparent Memory Encryption Engine for IoT
Naina Gupta, Arpan Jati, Anupam Chattopadhyay · IEEE Internet of Things Journal · 2020
Recent advancement in technologies has led to the widespread adoption and deployment of Internet-of-Things devices. Because of the ubiquitous nature of these devices, they process large amounts of personal and sensitive data. These data are typically stored on DRAM chips, and hence becomes an easy target for attackers. Memory encryption is a commonly adopted solution to provide confidentiality. However, realizing a lightweight, low-latency, low-power solution for resource-constrained devices is a challenge. To address this, we designed MemEnc, a purely hardware-based solution that performs encryption on-the-fly and handles memory requests transparently without any OS intervention. MemEnc runs at a maximum frequency of 401 MHz and requires about 23.2 kGE (gate equivalents) on 65-nm ASIC and consumes only 1.9 mW of power at 250 MHz. Using comprehensive benchmarking, we also analyze the applicability of the proposed solution on real-world workloads. Our experiments show that certain real-time applications can run with full memory encryption and still meet system requirements. Moreover, we integrated our memory encryption engine with ARM TrustZone and present comparative results for the different case studies with Intel SGX. We show that static and dynamic efficiency-security tradeoff is necessary for all scenarios.