A Confounding-Domain Randomized Approach for Providing Source Location Privacy Preservation for Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) have advanced technologically, allowing for a wide range of Internet of Things (IoT) applications. The Internet of Things (IoT) provides a platform for connecting items to achieve a specific goal with minimal human intervention. Various practical sectors, such as environmental monitoring and defense, demand IoT support with maximum object connectivity, and low human participation, yet face security concerns from strong unauthorized entities. As location privacy is one of these major vulnerabilities, continual monitoring of contextual information may lead the attacker to the asset's position. The location privacy of the source node that detects and reports the presence of an event is critical. In this study, we provide a source location privacy (SLP) preservation technique based on confounding domain angular routing (SLP-CDAR) that attempts to improve security while increasing network lifespan. To avoid traffic analysis attacks, packets first undergo a random walk, followed by a perplexing time domain routing that creates additional diversionary pathways. The packets are then routed via angle routing, followed by a random path, and finally delivered to the base station using the forward random walk technique. The experimental results prove that the proposed scheme enhances the location privacy strength while providing an improved network lifetime, and a swift increase in the entropy.

KEYWORDS:

• Angular routing
• Confounding time-domain transmission
• Location disclosure
• Random routing
• Safety period
• Security

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Notes on contributors

Nisha

Nisha received her BSc degree in computer science from Ravenshaw University, Cuttack, India in 2015 and her MSc degree in computer science from Pondicherry University, Puducherry, India in 2017. She is currently pursuing PhD at the department of computer science, Banaras Hindu University, Varanasi, India. Her areas of interest are the internet of things, network security, wireless sensor networks, security and privacy in IOT.

S. Suresh

S Suresh received his MCA degree from Presidency College, Chennai, India in 2009 and PhD from the National Institute of Technology, Tiruchirapalli, India in 2015. He is currently working as an assistant professor in the department of computer science, Institute of Science, Banaras Hindu University, Varanasi, India. His areas of interest are theoretical computer science, machine learning and IoT, big data analytics, distributed and cloud computing. Email: [email protected]