CScrypt: a compressive-sensing-based encryption engine for the Internet of Things: demo abstract

Xue, Wanli and Luo, Chengwen and Rana, Rajib and Hu, Wen and Seneviratne, Aruna (2016) CScrypt: a compressive-sensing-based encryption engine for the Internet of Things: demo abstract. In: 14th ACM Conference on Embedded Network Sensor Systems (SenSys '16), 14-16 Nov 2016, Stanford, Calif, USA.

Abstract

Internet of Things (IoT) have been connecting the physi-
cal world seamlessly and provides tremendous opportunities
to a wide range of applications. However, potential risks
exist when IoT system collects local sensor data and up-
loads to the Cloud. The private data leakage can be severe
with curious database administrator or malicious hackers
who compromise the Cloud. In this demo, we solve this
problem of guaranteeing the user data privacy and secu-
rity using compressive sensing based cryptographic method.
We present CScrypt, a compressive-sensing-based encryp-
tion engine for the Cloud-enabled IoT systems to secure the
interaction between the IoT devices and the Cloud. Our sys-
tem exploits the fact that each individual's biometric data
can be trained to a unique dictionary which can be used as
an encryption key meanwhile to compress the original data.
We will demonstrate a functioning prototype of our system
using live data stream when attending the conference.


Statistics for USQ ePrint 34369
Statistics for this ePrint Item
Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Abstract only published in Proceedings. Permanent restricted access to Published Abstract, in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Institute for Resilient Regions
Date Deposited: 12 Jul 2018 07:28
Last Modified: 04 Sep 2018 03:32
Uncontrolled Keywords: compressive sensing; security; encryption; Internet of Things
Fields of Research : 08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1145/2994551.2996525
URI: http://eprints.usq.edu.au/id/eprint/34369

Actions (login required)

View Item Archive Repository Staff Only