Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, December 2006. / Thesis Advisor(s): Ha, Tri T. ; Su, Weilian. "December 2006." Description based on title screen as viewed on March 12, 2008. Includes bibliographical references (p. 55-56). Also available in print.

In passive RFID systems, how to reduce the collision among tags is an important issue at the medium access control layer. The Framed Slotted ALOHA and its variations are well-known anti-collision algorithms for RFID systems. However, when the Framed Slotted ALOHA is used, the system efficiency and the average time delay deteriorate rapidly when the total number of tags increases. On the other hand, the total number of slots in a frame can¡¦t be infinity. In this thesis, we first compare existing anti-collision protocols and then propose a novel algorithm based on the Enhanced Dynamic Framed Slotted ALOHA (EDFSA) and the Progressing Scanning (PS) algorithm. The proposed algorithm is called Dynamic Grouping (DG). The DG algorithm partitions the RFID tags according to the distances from tags to the reader in order to avoid using too many slots in a frame. Inparticular, the DG algorithm estimates the spatial distribution of tags based on previous scanning results and then adjusts the partition accordingly. Unlike PS algorithm, the DG algorithm is applicable when the RFID tags are uniformly distributed or normally distributed.

Various established and emerging applications of RFID technology have been and are being implemented by companies in different parts of the world. However, RFID technology is susceptible to a variety of security and privacy concerns, as it is prone to attacks such as eavesdropping, denial of service, tag cloning and user tracking. This is mainly because RFID tags, specifically low-cost tags, have low computational capability to support complex cryptographic algorithms. Tag cloning is a key problem to be considered since it leads to severe economic losses. One of the possible approaches to address tag cloning is using an intrusion detection system. Intrusion detection systems in RFID networks, on top of the existing lightweight cryptographic algorithms, provide an additional layer of protection where other security mechanisms may fail. This thesis presents an intrusion detection mechanism that detects anomalies caused by one or more cloned RFID tags in the system. We make use of a Hybrid Fuzzy Genetics-Based Machine Learning algorithm to design an intrusion detection model from RFID system-generated event logs. For the purpose of training and evaluation of our proposed approach, part of the RFID system-generated dataset provided by the University of Tasmania’s School of Computing and Information Systems was used, in addition to simulated datasets. The results of our experiments show that the model can achieve high detection rates and low false positive rates when identifying anomalies caused by one or more cloned tags. In addition, the model yields linguistically interpretable rules that can be used to support decision making during the detection of anomaly caused by the cloned tags.

On assiste de nos jours à une utilisation croissante des systèmes RFID (Radio Frequency IDentification systems) dans diversdomaines d’application (logistique, systèmes de production, inventaires, traçabilité, etc.). Certaines de ces applicationsprésentent un caractère critique à l’image du respect de la chaîne de froid lors de l’acheminement de denrées alimentaires oudans le cas de systèmes de manutention de bagages dans les aéroports. Or, la sensibilité des systèmes RFID vis-à-vis de leurenvironnement, notamment des perturbations électromagnétiques ou de la présence d’obstacles, les rend vulnérables. Demême, de par le nombre important d’éléments (étiquettes, lecteurs) mis en oeuvre dans de tels systèmes, des comportementserronés peuvent survenir en raison de fautes dans les divers éléments constituant le système. D’où l’importance et la nécessitéde traiter le problème de la sûreté de fonctionnement et de la tolérance aux fautes dans le but de rendre ces systèmes plusrobustes.L’objectif de cette thèse concerne la proposition d’approches logicielles de test et de diagnostic en ligne adaptées aux systèmesRFID en vue d’améliorer leur robustesse. Depuis quelques années, une exploitation efficace des systèmes RFID a vu ledéveloppement d’intergiciels ou de middlewares RFID, dont le rôle est de proposer des services permettant la gestion desquantités de données importantes en provenance des lecteurs RFID. L’utilisation de tels intergiciels est d’un grand intérêt pourla sûreté de fonctionnement des systèmes RFID en raison de la nature distribuée de ces systèmes ; en particulier, grâce àl’intégration des mécanismes de sûreté de fonctionnement, plus précisément le test et le diagnostic en ligne, au niveau dumiddleware. Dans cette thématique, nous avons proposé plusieurs solutions pour couvrir les deux couches centrales du systèmeà savoir la couche middleware et son interface de communication avec les sources de données, le protocole LLRP (Low LevelReader Protocol). Nous avons proposé une solution middleware compatible avec le standard de communication des systèmesRFID, et utilisée comme un réceptacle pour une solution algorithmique de diagnostic probabiliste qui permet de détecter lesdéfaillances potentielles des composants du système sur la base d’un modèle probabiliste qui tient compte de l’environnementd’exécution. Ensuite, nous avons proposé un mécanisme d’analyse des fichiers log de l’interface de communication LLRP,complémentaire à l’algorithme probabiliste et qui permet d’approfondir le diagnostic en recherchant les causes de la défaillancedétectée sur la base de différentes signatures de défaillances déjà établies. Enfin, nous avons proposé une extension dustandard de communication LLRP qui tient compte de plusieurs comportements défaillants dans le but de rendre ce dernier plusfiable. / We are witnessing today a growing use of RFID (Radio Frequency IDentification) systems in various application areas (logistics,production systems, product traceability, etc.). Some of these applications are critical such as food-related cold chain logistics orbaggage handling systems in airports. Nevertheless, RFID are very sensitive to their environment, including electromagneticdisturbances or presence of obstacles, making them error-prone. Also, because of the large number of elements (tags, readers,and sensors) constituting current RFID systems, erroneous behaviors are more frequent. Hence, it is important to address all theproblems related to RFID system dependability and deal with them in order to make these systems more robust.The goal of this thesis is the development of software test and online diagnosis facilities for RFID systems to improve theirrobustness. In recent years, the effective use of RFID systems has seen the development of RFID middleware solutions, whoserole is to provide services for the management of large amounts of raw data of the various RFID sources. Due to the distributednature of current RFID systems, the use of such solutions is of great interest regarding the improvement of RFID systemdependability. In particular, thanks to the integration of dependability mechanisms, specifically the online test and diagnosisapproaches in the RFID middleware solution. In addition, because of the middleware is considered as the backbone of an RFIDsystem, whereby the whole RFID dataflow passes; all the needed information will be availabe to our proposed approaches toperform a correct diagnosis. We proposed several solutions to cover the two main layers of RFID systems; namely, themiddleware layer and the communication layer between the middleware and the data sources, the Low Level Reader Protocol(LLRP). We have proposed a LLRP compliant middleware solution, used to accommodate a probabilistic diagnosis algorithm todetect potential failures of the RFID system components on the basis of a probabilistic model that takes into account theexecution conditions. Then, we proposed a complementary mechanism to the previous algorithm for analyzing the log files ofthe LLRP communication interface allowing further analysis by looking for the causes of the detected failures on the basis of an already defined set of failure signatures. Finally, we proposed an extension of the LLRP standard to make it more reliable bytaking into account several RFID failures.

Made available in DSpace on 2014-12-17T14:55:40Z (GMT). No. of bitstreams: 1 JoseMF.pdf: 585000 bytes, checksum: d743090da952a3d8b178ffb4048abd4b (MD5) Previous issue date: 2009-12-16 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / RFID (Radio Frequency Identification) identifies object by using the radio frequency which is a non-contact automatic identification technique. This technology has shown its powerful practical value and potential in the field of manufacturing, retailing, logistics and hospital automation. Unfortunately, the key problem that impacts the application of RFID system is the security of the information. Recently, researchers have demonstrated solutions to security threats in RFID technology. Among these solutions are several key management protocols. This master dissertations presents a performance evaluation of Neural Cryptography and Diffie-Hellman protocols in RFID systems. For this, we measure the processing time inherent in these protocols. The tests was developed on FPGA (Field-Programmable Gate Array) platform with Nios IIr embedded processor. The research methodology is based on the aggregation of knowledge to development of new RFID systems through a comparative analysis between these two protocols. The main contributions of this work are: performance evaluation of protocols (Diffie-Hellman encryption and Neural) on embedded platform and a survey on RFID security threats. According to the results the Diffie-Hellman key agreement protocol is more suitable for RFID systems / Identifica??o por r?dio freq??ncia, tamb?m chamada de RFID (Radio Frequency Identification), representa uma tecnologia de transmiss?o de dados sem fio. Estes dados s?o relacionados principalmente a c?digos de identifica??o. A tecnologia RFID vem apresentando um grande potencial de utiliza??o em setores da automa??o industrial, residencial e hospitalar. No entanto, estas aplica??es podem resultar em riscos a seguran?a e privacidade dos usu?rios. Recentemente, pesquisadores v?m apresentando poss?veis solu??es as amea?as de seguran?a da tecnologia. Entre estas solu??es est?o os protocolos de distribui??o de chaves criptogr?ficas. O presente trabalho tem como objetivo realizar uma avalia??o de desempenho dos protocolos de Criptografia Neural e Diffie-Hellman na gera??o de chaves em sistemas RFID. Para isso, iremos mensurar o tempo de processamento destes protocolos. Para os testes foi desenvolvido uma plataforma em FPGA (Field-Programmable Gate Array) com o processador embarcado Nios IIr. Sobre esta plataforma foram utilizados os protocolos de Criptografia Neural e Diffie-Hellman no processo de gera??o de chaves criptogr?ficas. A metodologia de pesquisa baseia-se na agrega??o de conhecimento ao desenvolvimento de novos sistemas RFID atrav?s de uma an?lise comparativa entre esses dois protocolos de seguran?a da informa??o. As principais contribui??es deste trabalho s?o: avalia??o de desempenho dos protocolos (Diffie- Hellman e Criptografia Neural) em uma plataforma embarcada e um levantamento bibliogr?fico de pesquisas relacionadas ? seguran?a da informa??o em sistemas RFID. Nos resultados obtidos foi poss?vel observar que o protocolo de Diffie-Hellman ? mais apropriado para sistemas RFID

The continuous integration of wireless communication systems in medical and healthcare applications has made the actualisation of reliable healthcare applications and services for patient care and smart home a reality. Diverse indoor approaches are sought to improve the quality of living and consequently longevity. The research centres on the development of smart healthcare solutions using various indoor technologies and techniques for active and assisted living. At first, smart health solutions for ambient and wearable assisted living in smart homes are sought. This requires a detailed study of indoor localisation. Different indoor localisation technologies including acoustic, magnetic, optical and radio frequency are evaluated and compared. From the evaluation, radio frequency-based technologies, with interest in wireless fidelity (Wi-Fi) and radio frequency identification (RFID) are isolated for smart healthcare. The research focus is sought on auto-identification technologies, with design considerations and performance constraints evaluated. Moreover, the design of various antennas for different indoor technologies to achieve innovative healthcare solutions is of interest. First, a meander line passive RFID tag antenna resonating at the European ultra-high frequency is designed, simulated and evaluated. Second, a frequency-reconfigurable patch antenna with the capability to resonate at ten distinct frequencies to support Wi-Fi and worldwide interoperability for microwave access applications is designed and simulated. Afterwards, a low-profile, lightweight, textile patch antenna using denim material substrate is designed and experimentally verified. It is established that, by loading proper rectangular slots and introducing strip lines, substantial size antenna miniaturisation is achieved. Further, novel wearable and ambient methodologies to further ameliorate smart healthcare and smart homes are developed. Machine learning and deep learning methods using multivariate Gaussian and Long short-term memory recurrent neural network are used to experimentally validate the viability of the new approaches. This work follows the construction of the SmartWall of passive RFID tags to achieve non-invasive data acquisition that is highly unobtrusive. / Tertiary Education Trust Fund (TETFund) of the Federal Government of Nigeria

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