An energy efficient data privacy scheme for IoT devices in mobile cloud computing

Mehdi Bahrami, Arshia A Khan, Mukesh Singhal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

The Internet of Things (IoT) paradigm allows a network of smart objects to sense the environment. Specifically, these objects may obtain IPv6 for connecting to the Internet through 6LoWPAN protocol. These smart objects are able to transfer the data that reads from their embedded sensors and submitted directly to mobile cloud computing. However, outsourcing data to a mobile cloud computing server, as a third-party, is a challenge when data privacy can be violated by the cloud vendor's entities. Traditionally, we use encryption methods, such as AES, to encrypt data for maintaining data privacy and to avoid unauthorized entities access to data. However, traditional encryption methods cannot be run efficiently on IoT devices when they have limited resources, such as low-power battery, low-speed processor with a kilobyte storage capacity. This paper presents a novel light-weight data privacy scheme for these tiny computing devices when the method enables devices to outsource their data to a semi-trusted mobile cloud computing system. We simulate the proposed scheme on Contiki simulation tools to assess the CPU power consumption and the average power consumption of the smart devices while it uses our proposed method. The experimental results show that the proposed scheme does not introduce radical additional power consumption, and the scheme maintains data privacy while the smart devices outsource data to a mobile cloud computing system.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE International Conference on Mobile Services, MS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages190-195
Number of pages6
ISBN (Electronic)9781509026258
DOIs
StatePublished - Dec 16 2016
Event2016 IEEE 5th International Conference on Mobile Services, MS 2016 - San Francisco, United States
Duration: Jun 27 2016Jul 2 2016

Other

Other2016 IEEE 5th International Conference on Mobile Services, MS 2016
CountryUnited States
CitySan Francisco
Period6/27/167/2/16

Keywords

  • Data Privacy
  • Data Security
  • Internet of Things
  • IoT
  • MCC
  • MIoT
  • Mobile Cloud Computing

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