Serverless computing like Function-as-a-Service (FaaS) is attractive for IoT service providers, liberating the providers from server maintenance. Since a data processing function is executed on the cloud instead of a dedicated server in the FaaS platform, the service users send their private data in their IoT devices to the third-party cloud, taking privacy leakage risks. Homomorphic encryption (HE) can preserve the privacy by enabling encrypted data processing on the cloud, but using HE for every data item incurs large computation and communication overheads. This work proposes SelectiveCrypt, a compiler-assisted semantic-aware encryption scheme that applies different cryptographic primitives depending on the operations on each data item. SelectiveCrypt homomorphically encrypts data items if arithmetic operations are applied to the data, while SelectiveCrypt encrypts data items with a symmetric key if the data are stored in the cloud without any arithmetic operation. The SelectiveCrypt framework consists of a compiler and its runtime system. The SelectiveCrypt compiler statically analyzes the data processing, determines an appropriate cryptographic primitive for each data item, and automatically transforms arithmetic operations into the homomorphic computation. The SelectiveCrypt runtime encrypts and decrypts the data items according to the static analysis result. This work evaluates the prototype SelectiveCrypt framework with five benchmarks that reflect real-world IoT scenarios. The evaluation results show that the SelectiveCrypt framework successfully reduces response time and communication overhead by 1.59 times and 9.61 times, respectively, compared with a HE scheme.
|Number of pages||12|
|Journal||IEEE Internet of Things Journal|
|Publication status||Published - 2021 Apr 1|
Bibliographical noteFunding Information:
Manuscript received May 24, 2020; revised August 10, 2020 and September 18, 2020; accepted October 8, 2020. Date of publication October 16, 2020; date of current version March 24, 2021. This work was supported by the Institute of Information and Communication Technology Planning and Evaluation (IITP) Funded by the Ministry of Science and ICT under Grant IITP-2017-0-00195, Grant IITP-2018-0-01392, and Grant IITP-2020-0-01847. (Corresponding author: Hanjun Kim.) Bongjun Kim and Seonyeong Heo are with the Department of Computer Science and Engineering, POSTECH, Pohang 37673, South Korea (e-mail: email@example.com; firstname.lastname@example.org).
© 2014 IEEE.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications