Expandable Mix-Zones as a Deception Technique for Providing Location Privacy on Internet of Things

Abstract

As military and security operations increasingly rely on interconnected devices, safeguarding the precise locations of personnel and assets has become critical. Existing solutions for location privacy rely on encryption and obfuscation, but they often fail under real-time adversarial scrutiny. Traditional approaches lack adaptability, leaving military personnel and assets vulnerable to tracking and targeted attacks.

Researchers at Florida Atlantic University have developed Expandable Mix-Zones, a novel deception technique that enhances location privacy in Internet of Things (IoT) and Internet of Battlefield Things (IoBT) environments. This innovation strategically mixes and anonymizes multiple user locations within dynamic spatial boundaries, making it significantly harder for adversaries to track individuals or assets. Unlike conventional static privacy measures, Expandable Mix-Zones dynamically adjust their size and location based on real-time operational needs. The technology has been demonstrated in simulations using a Random Walk model, which validates its enhanced effectiveness by introducing controlled location uncertainty. This approach obscures movement patterns and reduces the risk of targeted attacks while ensuring seamless operational efficiency.

FAU seeks to advance this innovation into the marketplace through licensing or development partnerships.

Benefit

Market Application

Publications

Expandable Mix-Zones as a Deception Technique for Providing Location Privacy on Internet-of-Battlefield Things (IoBT)