PUF-based secure checker protocol for Networked RFID Systems

Radio Frequency Identification (RFID) system is anemerging technology for automating object identification. TheNetworked RFID System (NRS) is a component of a distributedobject identification network which facilitates automated supplychain management. It also makes the Internet of Things (IoT)concept a reality. To increase the business feasibility of NRSimplementation, the system should be able to ensure the visibilityand traceability of the object throughout the chain using achecker protocol. By doing so, the protocol will check thegenuineness of the object and the genuineness of the object’sprevious travel path on-site. While doing so, the protocol needs toensure the security requirement of the system. To this end, wepropose a secure checker protocol for NRS which will use a PUF(Physically Unclonable Function) and simple cryptographicprimitives. The protocol provides security (protect privacy of thepartners, injection of fake objects, non-repudiation, andunclonability), visibility and traceability for NRS. It is alsosuitable for passive tags.

RFID translation into Australian hospitals: an exploration through Actor-Network Theoretical(ANT) Lens

Radio Frequency Identification (RFID) is a technology that has been deployed successfully for asset tracking within hospitals aimed at improving the quality of processes. In the Australian hospitals context however, adoption of this technology seem sporadic. This research reports on a long-term investigation to gain a deeper understanding of the socio-technical factors involved in the adoption of RFID in Australian hospitals. The research was conducted using interpretive multiple case methodology and results analyzed through the Actor-Network Theoretical (ANT) Lens. © 2013 Infonomics Society.

Policy-based SQLIA detection and prevention approach for RFID systems

While SQL injection attacks have been plaguing web application systems for years, the possibility of them affecting RFID systems was only identified very recently. However, very little work exists to mitigate this serious security threat to RFID-enabled enterprise systems. In this paper, we propose a policy-based SQLIA detection and prevention method for RFID systems. The proposed technique creates data validation and sanitization policies during content analysis and enforces those policies during runtime monitoring. We tested all possible types of dynamic queries that may be generated in RFID systems with all possible types of attacks that can be mounted on those systems. We present an analysis and evaluation of the proposed approach to demonstrate the effectiveness of the proposed approach in mitigating SQLIA.

Fast and scalable counterfeits estimation for large-scale RFID systems

Many algorithms have been introduced to deterministically authenticate Radio Frequency Identification (RFID) tags, while little work has been done to address scalability issue in batch authentications. Deterministic approaches verify tags one by one, and the communication overhead and time cost grow linearly with increasing size of tags. We design a fast and scalable counterfeits estimation scheme, INformative Counting (INC), which achieves sublinear authentication time and communication cost in batch verifications. The key novelty of INC builds on an FM-Sketch variant authentication synopsis that can capture key counting information using only sublinear space. With the help of this well-designed data structure, INC is able to provide authentication results with accurate estimates of the number of counterfeiting tags and genuine tags, while previous batch authentication methods merely provide 0/1 results indicating the existence of counterfeits. We conduct detailed theoretical analysis and extensive experiments to examine this design and the results show that INC significantly outperforms previous work in terms of effectiveness and efficiency.

Filtering redundant data from RFID data streams

Radio Frequency Identification (RFID) enabled systems are evolving in many applications that need to know the physical location of objects such as supply chain management. Naturally, RFID systems create large volumes of duplicate data. As the duplicate data wastes communication, processing, and storage resources as well as delaying decision-making, filtering duplicate data from RFID data stream is an important and challenging problem. Existing Bloom Filter-based approaches for filtering duplicate RFID data streams are complex and slow as they use multiple hash functions. In this paper, we propose an approach for filtering duplicate data from RFID data streams. The proposed approach is based on modified Bloom Filter and uses only a single hash function. We performed extensive empirical study of the proposed approach and compared it against the Bloom Filter, d-Left Time Bloom Filter, and the Count Bloom Filter approaches. The results show that the proposed approach outperforms the baseline approaches in terms of false positive rate, execution time, and true positive rate.