Visible to the public Secure Data Provenance for the Internet of Things

TitleSecure Data Provenance for the Internet of Things
Publication TypeConference Paper
Year of Publication2017
AuthorsAman, Muhammad Naveed, Chua, Kee Chaing, Sikdar, Biplab
Conference NameProceedings of the 3rd ACM International Workshop on IoT Privacy, Trust, and Security
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4969-7
KeywordsCollaboration, composability, data provenance, Human Behavior, human factor, information theoretic security, IoT security, Metrics, Networked Control Systems Security, policy, pubcrawl, Resiliency, Scalability, theoretical cryptography
Abstract

The vision of smart environments, systems, and services is driven by the development of the Internet of Things (IoT). IoT devices produce large amounts of data and this data is used to make critical decisions in many systems. The data produced by these devices has to satisfy various security related requirements in order to be useful in practical scenarios. One of these requirements is data provenance which allows a user to trust the data regarding its origin and location. The low cost of many IoT devices and the fact that they may be deployed in unprotected spaces requires security protocols to be efficient and secure against physical attacks. This paper proposes a light-weight protocol for data provenance in the IoT. The proposed protocol uses physical unclonable functions (PUFs) to provide physical security and uniquely identify an IoT device. Moreover, wireless channel characteristics are used to uniquely identify a wireless link between an IoT device and a server/user. A brief security and performance analysis are presented to give a preliminary validation of the protocol.

URLhttp://doi.acm.org/10.1145/3055245.3055255
DOI10.1145/3055245.3055255
Citation Keyaman_secure_2017