Recognizing Patterns in Transmitted Signals for Identification Purposes

The ability to identify and authenticate entities in cyberspace such as users, computers, cell phones, smart cards, and radio frequency identification (RFID) tags is usually accomplished by having the entity demonstrate knowledge of a secret key. When the entity is portable and physically accessible, like an RFID tag, it can be difficult to secure given the memory, processing, and economic constraints. This work proposes to use unique patterns in the transmitted signals caused by manufacturing differences to identify and authenticate a wireless device such as an RFID tag. Both manufacturer identification and tag identification are performed on a population of 300 tags from three different manufacturers. A methodology to select features for identifying signals with high accuracy is developed and applied to passive RFID tags. The classifier algorithms K-Nearest Neighbors, Parzen Windows, and Support Vector Machines are investigated. The tag\u27s manufacturer can be identified with 99.93\% true positive rate. An individual tag is identified with 99.8\% accuracy, which is better than previously published work. Using a Hidden Markov Model with framed timing and power data, the tag manufacturer can be identified with 97.37\% accuracy and has a compact representation. An authentication system based on unique features of the signals is proposed assuming that the readers that interrogate the tags may be compromised by a malicious adversary. For RFID tags, a set of timing-only features can provide an accuracy of 97.22\%, which is better than previously published work, is easier to measure, and appears to be more stable than power features

RFID signal acquisition and identification

RFID is one of the fastest growing technologies grouped under Automatic Identification (auto ID). RFID tags are very low cost and used for identification of objects. RFID is a global technology that is used in industries, medical, wall mart, airport baggage, Libraries, Smart cards, even in every transported object has its own RFID tag. Therefore, concern of security and privacy should be there to prevent unauthorized access. A method is proposed to prevent cloning and counterfeiting of tags based on RF Fingerprinting. RF fingerprinting of a tag is based upon physical attributed such as an electromagnetic (EM) signal of the tag. By capturing the EM signal of RFID tags a method known as Dynamic wavelet fingerprinting is applied to generate fingerprint images of signals. Our proposed method consists of four stages: Namely Real time data acquiring by use of a CRO, Dynamic wavelet fingerprinting (DWFP) of the signal, Feature extraction, and Classification. Feature is extracted such as Eccentricity, perimeter, centroid , extent, area and orientation. Ann classifier is used which is a one vs. One classifier. To improve the performance of classification multi-feature based serial feature fusion technique has been proposed, which shows a significant improvement in classification performance. RF fingerprint allows prevention of unauthorized access, identification and detecting cloning of sensitive devices. To identify tags and to detect counterfeit RF fingerprinting can be used. The cost of the tag does not increase and can be used in existing tag with only requirement of softwar

Design of nameplates editor

Diplomová práce se zabývá problematikou typových štítků, používaných pro značení výrobků v sériové výrobě. V rešeršní části práce je uvedena problematika používaných médií typových štítků a jejich tisku. Je analyzována problematika obsahu a návrhu štítků. Výsledkem práce je grafický editor pro návrh štítků a jejich převod do jazyku ZPL II. Tento jazyk používají zejména tiskárny firmy Zebra Technologies, které jsou velmi rozšířené.The diploma thesis deals with the problematics of type labels, used for marking of products in series production. The research part of the thesis deals with the issues of the used label media and label printing. The issue of content and design of labels is analyzed. The result of thesis is a graphic editor for designing labels and their translation into ZPL II. This language is mainly used by Zebra Technologies printers, which are very common used in industry.

An Approach to Near Field Data Selection in Radio Frequency Identification

Personal identification is needed in many civil activities, and the common identification cards, such as a driver\u27s license, have become the standard document de facto. Radio frequency identification has complicated this matter. Unlike their printed predecessors, contemporary RFID cards lack a practical way for users to control access to their individual fields of data. This leaves them more available to unauthorized parties, and more prone to abuse. Here, then was undertaken a means to test a novel RFID card technology that allows overlays to be used for reliable, reversible data access settings. Similar to other proposed switching mechanisms, it offers advantages that may greatly improve outcomes. RFID use is increasing in identity documents such as drivers\u27 licenses and passports, and with it concern over the theft of personal information, which can enable unauthorized tracking or fraud. Effort put into designing a strong foundation technology now may allow for widespread development on them later

Fingerprinting RFID Tags

Radio frequency identification (RFID) tags are low-cost devices that are used to uniquely identify the objects to which they are attached. Due to the low cost and small size that are driving the technology, a tag has limited computational capabilities and resources. These limitations constrain the use of conventional encryption algorithms and security protocols to prevent cloning and counterfeiting of an RFID tag. Therefore, we propose to create an electronic fingerprint of a tag based upon the physical attributes of the tag. We have fingerprinted RFID tags based upon their minimum power responses measured at multiple frequencies. The fingerprint can be used effectively to identify the tags in the future with high probability and to detect counterfeit tags. This mechanism does not increase the cost of the tag and can be applied to any existing tag, because it is independent of the computational capabilities and resources of the RFID tag