Chiu Chiang Tan

Counting RFID Tags Efficiently and Anonymously

Radio Frequency IDentification (RFID) technology has attracted much attention due to its variety of applications, e.g., inventory control and object tracking. One important problem in RFID systems is how to quickly estimate the number of distinct tags without reading each tag individually. This problem plays a crucial role in many real-time monitoring and privacy-preserving applications. In this paper, we present an efficient and anonymous scheme for tag population estimation. This scheme leverages the position of the first reply from a group of tags in a frame. Results from mathematical analysis and extensive simulation demonstrate that our scheme outperforms other protocols proposed in the previous work.

Secure and Serverless RFID Authentication and Search Protocols

With the increased popularity of RFID applications, different authentication schemes have been proposed to provide security and privacy protection for users. Most recent RFID protocols use a central database to store the RFID tag data. The RFID reader first queries the RFID tag and returns the reply to the database. After authentication, the database returns the tag data to the reader. In this paper, we propose a more flexible authentication protocol that provides comparable protection without the need for a central database. We also suggest a protocol for secure search for RFID tags. We believe that as RFID applications become widespread, the ability to securely search for RFID tags will be increasingly useful.

Body sensor network security: an identity-based cryptography approach

A body sensor network (BSN), is a network of sensors deployed on a persons body, usually for health care monitoring. Since the sensors collect personal medical data, security and privacy are important components in a body sensor network. At the same time, the collected data has to readily available in the event of an emergency. In this paper, we present IBE-Lite, a lightweight identity-based encryption suitable for sensors, and developed protocols based on IBE-Lite for a BSN.

IMDGuard: Securing implantable medical devices with the external wearable guardian

Recent studies have revealed security vulnerabilities in implantable medical devices (IMDs). Security design for IMDs is complicated by the requirement that IMDs remain operable in an emergency when appropriate security credentials may be unavailable. In this paper, we introduce IMDGuard, a comprehensive security scheme for heart-related IMDs to fulfill this requirement. IMDGuard incorporates two techniques tailored to provide desirable protections for IMDs. One is an ECG based key establishment without prior shared secrets, and the other is an access control mechanism resilient to adversary spoofing attacks. The security and performance of IMDGuard are evaluated on our prototype implementation.

How to Monitor for Missing RFID tags

As RFID tags become more widespread, new approaches for managing larger numbers of RFID tags will be needed. In this paper, we consider the problem of how to accurately and efficiently monitor a set of RFID tags for missing tags. Our approach accurately monitors a set of tags without collecting IDs from them. It differs from traditional research which focuses on faster ways for collecting IDs from every tag. We present two monitoring protocols, one designed for a trusted reader and another for an untrusted reader.

SybilDefender: Defend against sybil attacks in large social networks

Distributed systems without trusted identities are particularly vulnerable to sybil attacks, where an adversary creates multiple bogus identities to compromise the running of the system. This paper presents SybilDefender, a sybil defense mechanism that leverages the network topologies to defend against sybil attacks in social networks. Based on performing a limited number of random walks within the social graphs, SybilDefender is efficient and scalable to large social networks. Our experiments on two 3,000,000 node real-world social topologies show that SybilDefender outperforms the state of the art by one to two orders of magnitude in both accuracy and running time. SybilDefender can effectively identify the sybil nodes and detect the sybil community around a sybil node, even when the number of sybil nodes introduced by each attack edge is close to the theoretically detectable lower bound. Besides, we propose two approaches to limiting the number of attack edges in online social networks. The survey results of our Facebook application show that the assumption made by previous work that all the relationships in social networks are trusted does not apply to online social networks, and it is feasible to limit the number of attack edges in online social networks by relationship rating.

IBE-Lite: A Lightweight Identity-Based Cryptography for Body Sensor Networks

A body sensor network (BSN) is a network of sensors deployed on a persons body for health care monitoring. Since the sensors collect personal medical data, security and privacy are important components in a BSN. In this paper, we developed IBE-Lite, a lightweight identity-based encryption suitable for sensors in a BSN. We present protocols based on IBE-Lite that balance security and privacy with accessibility and perform evaluation using experiments conducted on commercially available sensors.

Severless Search and Authentication Protocols for RFID

With the increasing popularity of RFID applications, different authentication schemes have been proposed to provide security and privacy protection to users. Most recent RFID protocols use a central database to store the RFID tag data. An RFID reader first queries the RFID tag and returns the reply to the database. After authentication, the database returns the tag data to the reader. In this paper, we proposed a more flexible authentication protocol that provides comparable protection without the need for a central database. We also suggest a protocol for secure search for RFID tags. We believe that as RFID applications become widespread, the ability to search for RFID tags will be increasingly useful

Finding popular categories for RFID tags

As RFID tags are increasingly attached to everyday items, it quickly becomes impractical to collect data from every tag in order to extract useful information. In this paper, we consider the problem of identifying popular categories of RFID tags out of a large collection of tags, without reading all the tag data. We propose two algorithms based on the idea of group testing, which allows us to efficiently derive popular categories of tags. We evaluate our solutions using both theoretical analysis and simulation.

Efficient Tag Identification in Mobile RFID Systems

In this paper we consider how to efficiently identify tags on the moving conveyor. Considering conditions like the path loss and multi-path effect in realistic settings, we first propose a probabilistic model for RFID tag identification. Based on this model, we propose efficient solutions to identify moving RFID tags, according to the fixed-path mobility on the conveyor. A dynamic program based solution and an adaptive solution are proposed to select optimized frame sizes during the query cycles. Simulation results indicate that by leveraging the probabilistic model our solutions can achieve much better performance than using parameters for the ideal propagation situations.