A New Product Anti-Counterfeiting Blockchain Using a Truly Decentralized Dynamic Consensus Protocol

The growth of counterfeit goods has plagued the international community for decades. Nowadays, the battle against counterfeiting remains a significant challenge. Most of the current anti‐counterfeiting systems are centralized. Motivated by the evolution of blockchain technology, we propose (Block‐Supply), a decentralized anti‐counterfeiting supply chain that exploits NFC and blockchain technologies. This paper also proposes a new truly decentralized consensus protocol that, unlike most of the existing protocols, does not require PoW and randomly employs a different set of different size of validators each time a new block is proposed. Our protocol utilizes a game theoretical model to analyze the risk likelihood of the block\u27s proposing nodes. This risk likelihood is used to determine the number of validators involved in the consensus process. Additionally, the game model enforces the honest consensus nodes\u27 behavior by rewarding honest players and penalizing dishonest ones. Our protocol utilizes a novel, decentralized, dynamic mapping between the nodes that participate in the consensus process. This mapping ensures that the interaction between these nodes is executed anonymously and blindly. This way of mapping withstands many attacks that require knowing the identities of the participating nodes in advance, such as DDoS, Bribery, and Eclipse attacks

Enchancing RFID data quality and reliability using approximate filtering techniques

Radio Frequency Identification (RFID) is an emerging auto-identification technology that uses radio waves to identify and track physical objects without the line of sight. While delivering significant improvements in various aspects, such as, stock management and inventory accuracy, there are serious data management issues that affect RFID data quality in preparing reliable solutions. The raw read rate in real world RFID deployments is often in the 60-70% range and naturally unreliable because of redundant and false readings. The redundant readings result in unnecessary storage and affect the efficiency of data processing. Furthermore, false readings that focused on false positive readings generated by cloned tag could be mistakenly considered as valid and affects the final results and decisions. Therefore, two approaches to enhance the RFID data quality and reliability were proposed. A redundant reading filtering approach based on modified Bloom Filter is presented as the existing Bloom Filter based approaches are quite intricate. Meanwhile, even though tag cloning has been identified as one of the serious RFID security issue, it only received little attention in the literature. Therefore we developed a lightweight anti-cloning approach based on modified Count- Min sketch vector and tag reading frequency from e-pedigree in observing identical Electronic Product Code (EPC) of the low cost tag in local site and distributed region in supply chain. Experimental results showed, that the first proposed approach, Duplicate Filtering Hash (DFH) achieved the lowest false positive rate of 0.06% and the highest true positive rate of 89.94% as compared to other baseline approaches. DFH is 71.1% faster than d-Left Time Bloom Filter (DLTBF) while reducing amount of hashing and achieved 100% true negative rate. The second proposed approach, Managing Counterfeit Hash (MCH) performs fastest and 25.7% faster than baseline protocol (BASE) and achieved 99% detection accuracy while DeClone 64% and BASE 77%. Thus, this study successfully proposed approaches that can enhance the RFID data quality and reliability

2015, UMaine News Press Releases

This is a catalog of press releases put out by the University of Maine Division of Marketing and Communications between January 2, 2015 and December 31, 2015