GenomeFingerprinter and universal genome fingerprint analysis for systematic comparative genomics

How to compare whole genome sequences at large scale has not been achieved via conventional methods based on pair-wisely base-to-base comparison; nevertheless, no attention was paid to handle in-one-sitting a number of genomes crossing genetic category (chromosome, plasmid, and phage) with farther divergences (much less or no homologous) over large size ranges (from Kbp to Mbp). We created a new method, GenomeFingerprinter, to unambiguously produce three-dimensional coordinates from a sequence, followed by one three-dimensional plot and six two-dimensional trajectory projections to illustrate whole genome fingerprints. We further developed a set of concepts and tools and thereby established a new method, universal genome fingerprint analysis. We demonstrated their applications through case studies on over a hundred of genome sequences. Particularly, we defined the total genetic component configuration (TGCC) (i.e., chromosome, plasmid, and phage) for describing a strain as a system, and the universal genome fingerprint map (UGFM) of TGCC for differentiating a strain as a universal system, as well as the systematic comparative genomics (SCG) for comparing in-one-sitting a number of genomes crossing genetic category in diverse strains. By using UGFM, UGFM-TGCC, and UGFM-TGCC-SCG, we compared a number of genome sequences with farther divergences (chromosome, plasmid, and phage; bacterium, archaeal bacterium, and virus) over large size ranges (6Kbp~5Mbp), giving new insights into critical problematic issues in microbial genomics in the post-genomic era. This paper provided a new method for rapidly computing, geometrically visualizing, and intuitively comparing genome sequences at fingerprint level, and hence established a new method of universal genome fingerprint analysis for systematic comparative genomics.Comment: 63 pages, 15 figures, 5 table

FLAG : the fault-line analytic graph and fingerprint classification

Fingerprints can be classified into millions of groups by quantitative measurements of their new representations - Fault-Line Analytic Graphs (FLAG), which describe the relationship between ridge flows and singular points. This new model is highly mathematical, therefore, human interpretation can be reduced to a minimum and the time of identification can be significantly reduced. There are some well known features on fingerprints such as singular points, cores and deltas, which are global features which characterize the fingerprint pattern class, and minutiae which are the local features which characterize an individual fingerprint image. Singular points are more important than minutiae when classifying fingerprints because the geometric relationship among the singular points decide the type of fingerprints. When the number of fingerprint records becomes large, the current methods need to compare a large number of fingerprint candidates to identify a given fingerprint. This is the result of having a few synthetic types to classify a database with millions of fingerprints. It has been difficult to enlarge the minter of classification groups because there was no computational method to systematically describe the geometric relationship among singular points and ridge flows. In order to define a more efficient classification method, this dissertation also provides a systematic approach to detect singular points with almost pinpoint precision of 2x2 pixels using efficient algorithms

Prevention And Detection Mechanism For Security In Passive Rfid System

Low-cost radio frequency identification (RFID) tags conforming to the EPCglobal Class-1 Generation-2 standard are inherently insecure due to computational constraints. This thesis proposed the use of both prevention and detection mechanisms to solve the security and privacy issues. A lightweight cryptographic mutual authentication protocol which is resistant to tracking, denial of service (DoS) and replay attacks is proposed as a prevention mechanism. The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). The proposed protocol using 64 bits index is proved having the lowest non-unequivocally identification probability. In addition, the randomness of the session key generated from the MLCG is verified using NIST test suite. Besides that, the security of the proposed protocol is validated using the formal analysis tool, AVISPA. The correctness of the proposed protocol is demonstrated in a simulation model developed in JAVA TCP/IP socket. Next, the proposed protocol is implemented in RFID system including IAIK UHF Demo tag, TagSense Nano-UHF reader and back-end database. A GUI is created in a form of JAVA application to display data detected from tag. The proposed protocol implemented in real RFID system outperforms other related protocols because of 13.46 % shorter read time and write time consumed. The system is proved to be able to prevent tracking, DoS, and replay attacks from adversaries with moderate computation requirement compared to other related protocols

An automatic fingerprint classification technique based on global features

Fingerprint classification is an important stage in automatic fingerprint identification system (AFIS) because it significantly reduces the processing time to search and retrieve in a large-scale fingerprint database. However, its performance is heavily relied on image quality that comes in various forms such as low contrast, wet, dry, bruise, cuts, stains, etc. This paper proposed an automatic fingerprint classification scheme based on singular points and structural shape of orientation fields. It involves several steps, amongst others: firstly, fingerprint foreground is extracted and then noise patches in the foreground are detected and enhanced. Next, the orientation fields are estimated, and a corrective procedure is performed on the false ones. Afterward, an orientation image is created and singular points are detected. Based on the number of core and delta and their locations, an exclusive membership of the fingerprint can be discovered. Should it fail, the structural shape of the orientation fields neighboring the core or delta is analyzed. The performance of the proposed method is tested using 27,000 fingerprints of NIST Special Database 14. The results obtained are very encouraging with an accuracy rate of 89.31% that markedly outperformed the latest work

A Chaotic IP Watermarking in Physical Layout Level Based on FPGA

A new chaotic map based IP (Intellectual Property) watermarking scheme at physical design level is presented. An encrypted watermark is embedded into the physical layout of a circuit by configuring LUT (Lookup Table) as specific functions when it is placed and routed onto the FPGA (Field-Programmable Gate Array). The main contribution is the use of multiple chaotic maps in the processes of watermark design and embedding, which efficiently improves the security of watermark. A hashed chaotic sequence is used to scramble the watermark. Secondly, two pseudo-random sequences are generated by using chaotic maps. One is used to determine unused LUT locations, and the other divides the watermark into groups. The watermark identifies original owner and is difficult to detect. This scheme was tested on a Xilinx Virtex XCV600-6bg432 FPGA. The experimental results show that our method has low impact on functionality, short path delay and high robustness in comparison with other methods

Biometrics for internet‐of‐things security: A review

The large number of Internet‐of‐Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. Regarding authentication, contemporary biometric‐based authentication systems for IoT are discussed and classified based on different biometric traits and the number of biometric traits employed in the system. As for encryption, biometric‐cryptographic systems, which integrate biometrics with cryptography and take advantage of both to provide enhanced security for IoT, are thoroughly reviewed and discussed. Moreover, challenges arising from applying biometrics to IoT and potential solutions are identified and analyzed. With an insight into the state‐of‐the‐art research in biometrics for IoT security, this review paper helps advance the study in the field and assists researchers in gaining a good understanding of forward‐looking issues and future research directions

Assessing AI output in legal decision-making with nearest neighbors

Artificial intelligence (“AI”) systems are widely used to assist or automate decision-making. Although there are general metrics for the performance of AI systems, there is, as yet, no well-established gauge to assess the quality of particular AI recommendations or decisions. This presents a serious problem in the emerging use of AI in legal applications because the legal system aims for good performance not only in the aggregate but also in individual cases. This Article presents the concept of using nearest neighbors to assess individual AI output. This nearest neighbor analysis has the benefit of being easy to understand and apply for judges, lawyers, and juries. In addition, it is fundamentally compatible with existing AI methodologies. This Article explains how the concept could be applied for probing AI output in a number of use cases, including civil discovery, risk prediction, and forensic comparison, while also presenting its limitations

Automatic identification of artistic pigments by Raman spectroscopy using fuzzy logic and principal component analysis

This work offers an automatic identification system of Raman spectra of artistic pigments. The proposed methodology is based on a fuzzy logic system, and uses principal component analysis to reduce redundancies in data and the correlation operator as an index of similarity between two Raman spectra. Moreover, as sometimes pigments are used in mixtures by artist, the designed system is able to recognize binary mixtures of pigments on the basis of their Raman fingerprints.Peer ReviewedPostprint (published version

Skin Tissue Terahertz Imaging for Fingerprint Biometrics

abstract: Fingerprints have been widely used as a practical method of biometrics authentication or identification with a significant level of security. However, several spoofing methods have been used in the last few years to bypass fingerprint scanners, thus compromising data security. The most common attacks occur by the use of fake fingerprint during image capturing. Imposters can build a fake fingerprint from a latent fingerprint left on items such as glasses, doorknobs, glossy paper, etc. Current mobile fingerprint scanning technology is incapable of differentiating real from artificial fingers made from gelatin molds and other materials. In this work, the adequacy of terahertz imaging was studied as an alternative fingerprint scanning technique that will enhance biometrics security by identifying superficial skin traits. Terahertz waves (0.1 – 10 THz) are a non-ionizing radiation with significant penetration depth in several non-metallic materials. Several finger skin features, such as valley depth and sweat ducts, can possibly be imaged by employing the necessary imaging topology. As such, two imaging approaches 1) using quasi-optical components and 2) using near-field probing were investigated. The numerical study is accomplished using a commercial Finite Element Method tool (ANSYS, HFSS) and several laboratory experiments are conducted to evaluate the imaging performance of the topologies. The study has shown that terahertz waves can provide high spatial resolution images of the skin undulations (valleys and ridges) and under certain conditions identify the sweat duct pattern.Dissertation/ThesisMasters Thesis Electrical Engineering 201