Beyond their benign uses, civilian drones have increasingly been used in problematic ways that have stirred concern from the public and authorities. While many anti-drone systems have been proposed to take them down, such systems often rely on a fundamental assumption that the presence of the drone has already been detected and is known to the defender. However, there is a lack of an automated cost-effective drone detection system. In this paper, we investigate a drone detection system that is designed tao autonomously detect and characterize drones using radio frequency wireless signals. In particular, two technical approaches are proposed. The first approach is active tracking where the system sends a radio signal and then listens for its reflected component. The second approach is passive listening where it receives, extracts, and then analyzes observed wireless signal. We perform a set of preliminary experiments to explore the feasibility of the approaches using WARP and USRP software-defined platforms. Our preliminary results illustrate the feasibility of the proposed system and identify the challenges for future research.

Wireless sensor networks are highly vulnerable to the failure of base stations. An adversary can render a wireless sensor network useless by launching remote, softwarebased attacks or physical attacks on the base stations. This paper addresses the problem of defending a base station against physical attacks by concealing the geographic location of a base station. Typical packet traffic in a sensor network reveals pronounced patterns that allow an adversary analyzing packet traffic to deduce the location of a base station. The paper investigates several countermeasures against traffic analysis techniques aimed at disguising the location of a base station. First, a degree of randomness is introduced in the multi-hop path a packet takes from a sensor node to a base station. Second, random fake paths are introduced to confuse an adversary from tracking a packet as it moves towards a base station. Finally, multiple, random areas of high communication activity are created to deceive an adversary as to the true location of the base station. The paper evaluates these techniques analytically and via simulation using three evaluation criteria: total entropy of the network, total energy consumed, and the ability to guard against heuristic-based techniques to locate a base station.

One of the most compelling social questions, which until now was left unanswered by current technology, is "Who's that?" This question is usually asked about a new unfamiliar person in a social setting who piques your curiosity. This article presents WhozThat, a system that ties together online social networks with mobile smart- phones to answer this common and essential social question. WhozThat builds an infrastructure that shares social networking IDs locally, using wireless technology, while also leveraging a wireless connection to the Internet's social networks to bind identity with location. In addition, WhozThat offers an entire ecosystem on which increasingly complex context-aware applications can be built; that is, once the environment knows who one is, the environment can adapt its content based on the individual's identity or even the collective tastes of a local group. We describe a prototype of the basic WhozThat system and also describe a more advanced service we built, a context-aware music player. We also discuss security and privacy issues introduced by mobile social networks.