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Indoor navigation is necessary for users to explore large unfamiliar indoor environments such as airports, shopping malls, and hospital complex, which relies on the capability of continuously tracking a user's location. A typical indoor navigation system is built on top of a suitable Indoor Positioning System (IPS) and requires the user to periodically submit location queries to learn their whereabouts whereby to provide update-to-date navigation information. Received signal strength (RSS)-based IPSes are considered as one of the most classical IPSes, which locates a user by comparing the user's RSS measurement with the fingerprints collected at different locations in advance. Despite its significant advantages, existing RSS-IPSes suffer from two key challenges, the ambiguity of RSS fingerprints and device diversity, that may greatly reduce its positioning accuracy. In this paper, we introduce the design and evaluation of CITS, a novel RSS-based continuous indoor tracking system that can effectively cope with fingerprint ambiguity and device diversity via differential RSS fingerprint matching. Detailed experiment studies confirm the significant advantages of CITS over prior RSS-based solutions. 

Data aggregation is a key primitive in wireless sensor networks and refers to the process in which the sensed data are processed and aggregated en-route by intermediate sensor nodes. Since sensor nodes are commonly resource constrained, they may be compromised by attackers and instructed to launch various attacks. Despite the rich literature on secure data aggregation, most of the prior work focuses on detecting intermediate nodes from modifying partial aggregation results with two security challenges remaining. First, a compromised sensor node can report arbitrary reading of its own, which is fundamentally difficult to detect but widely considered to have limited impact on the final aggregation result. Second, a compromised sensor node can repeatedly attack the aggregation process to prevent the base station from receiving correct aggregation results, leading to a special form of Denial-of-Service attack. VMAT [1] (published in ICDCS 2011) is a representative secure data aggregation scheme with the capability of pinpointing and revoking compromised sensor nodes, which relies on a secure MIN aggregation scheme and converts other additive aggregation functions such as SUM and COUNT to MIN aggregations. In this paper, we introduce a novel enumeration attack against VMAT to highlight the security vulnerability of a sensor node reporting an arbitrary reading of its own. The enumeration attack allows a single compromised sensor node to significantly inflate the final aggregation result without being detected. As a countermeasure, we also introduce an effective defense against the enumeration attack. Theoretical analysis and simulation studies confirm the severe impact of the enumeration attack and the effectiveness of the countermeasure.