Efficient Detection of Counterfeit Products in Large-scale RFID Systems Using Batch Authentication Protocols

RFID technology facilitates processing of product information, making it a promising technology for anti-counterfeiting. However, in large-scale RFID applications, such as supply chain, retail industry, pharmaceutical industry, total tag estimation and tag authentication are two major research issues. Though there are per-tag authentication protocols and probabilistic approaches for total tag estimation in RFID systems, the RFID authentication protocols are mainly per-tag-based where the reader authenticates one tag at each time. For a batch of tags, current RFID systems have to identify them and then authenticate each tag sequentially, one at a time. This increases the protocol execution time due to the large volume of authentication data. In this paper, we propose to detect counterfeit tags in large-scale system using efficient batch authentication protocol. We propose FSA-based protocol, FTest, to meet the requirements of prompt and reliable batch authentication in large-scale RFID applications. FTest can determine the validity of a batch of tags with minimal execution time which is a major goal of large-scale RFID systems. FTest can reduce protocol execution time by ensuring that the percentage of potential counterfeit products is under the user-defined threshold. The experimental result demonstrates that FTest performs significantly better than the existing counterfeit detection approaches, for example, existing authentication techniques

RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

New Applications of Radio Frequency Identification Stations for Monitoring Fish Passage through Headwater Road Crossings and Natural Reaches

Within the Ouachita National Forest, roads and streams intersect each other thousands of times. Many of these road crossings alter stream hydrology and potentially limit longitudinal fish movement. To investigate the potential impacts of these road crossings on fish passage, we monitored movements of 3 native fish species (n = 2,171) individually tagged with radio frequency identification (RFID) tags in 2012 and 2013. We installed solar-powered RFID stations in 2 streams with road crossings and 2 reference streams without road crossings. Each of the 4 monitoring stations included a pair of antennas bracketing a road crossing (or similarly-sized natural reach) to continuously detect upstream or downstream passage. To monitor natural reference streams, we avoided full-duplex RFID technology, which would have required rigid in-stream structures. Alternatively, we utilized new applications of RFID technology such as direct in-stream installation of half-duplex wire antennas and figure-eight crossover antenna designs. These techniques appear promising, but technical difficulties limited the consistency of fish passage detection and consequently limited the strength of ecological conclusions. Even so, we report evidence that fish passed at significantly higher rates across reference reaches than reaches with road crossings. Furthermore, Creek Chub (Semotilus atromaculatus) passed reference reaches at significantly higher rates than Highland Stonerollers (Campostoma spadiceum), which passed at higher rates than Longear Sunfish (Lepomis megalotis). Stream intermittency appeared to exacerbate reduced passage rates associated with the road crossings

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed