ACTIVE SIGNATURE MATCHING WITH RICH STYLUS DATA

This publication disclosed a great stylus signature use case for login app/system, encryption/decrypt file and generating password. Signature on different people will be with different “Inking pressure”, “Holding force”, “Moving speed”, “Writing angle”, “Writing direction” and “Signature shape”. System can check such rich stylus data to do Signature Matching job. Signature is easier to remember and harder forged by hacker

2D correlation for signature matching

Master'sMASTER OF ENGINEERIN

A MULTI-GIGABIT NETWORK PACKET INSPECTION AND ANALYSIS ARCHITECTURE FOR INTRUSION DETECTION AND PREVENTION UTILIZING PIPELINING AND CONTENT-ADDRESSABLE MEMORY

Increases in network traffic volume and transmission speeds have given rise to the need for extremely fast packet processing. Many traditional processor-based network devices are no longer sufficient to handle tasks such as packet analysis and intrusion detection at multi-Gigabit rates. This thesis proposes two novel pipelined hardware architectures to relieve the computational load of a processor within network switches and routers. First, the Embedded Protocol Analyzer Pre-Processor (ePAPP) is capable of taking an unclassified packet byte stream directly off of a network cable at line speed and separating the data into individually classified protocol fields. Second, the CAM-Assisted Signature-Matching Architecture (CASMA) uses ternary content-addressable memory to perform the task of stateless intrusion detection signature-matching. The Snort open-source software network intrusion detection system is used as a model for intrusion detection functionality. Structured ASIC synthesis results show that ePAPP supports speeds of 2.89 Gb/s using less than 1% of available logic cells. CASMA is shown to support 1.25 Gb/s using less than 6% of available logic cells. The CASMA architecture is demonstrated to be able to implement 1729 of 1993 or 86.8% of the attack signatures, or rules, packaged with Snort version 2.1.2

Automatic Signature Matching in Component Composition

Reuse is not a new concept in software engineering. Ideas, abstractions, and processes have been reused by programmers since the very early days of software development. In the beginning, since storage media was very expensive, software reuse was basically to serve computers and their mechanical resources, as it substantially conserved memory. When the limitations on physical resources started to diminish, software engineers began to invent reuse approaches to save human resources as well. In addition, as the size and complexity of software systems constantly grow, organized and systematic reuse becomes essential in order to develop those systems in timely and cost-effective fashion. That is one main reason why new technologies and approaches for building software systems, such as object-oriented and component-based development, emerged in the last two or three decades. The focus of this thesis is on software components as building blocks of today's software systems. We consider components as software black boxes whose specification and external behavior are known. We assume that this information can somehow be extracted for each deployed software component. The first and basic assumption then would be the availability of a searchable repository of software components and their external behavioral specifications. Web services are a good example of such components. The most important advantage of software components is that they can be reused repeatedly in building different software systems. Reuse presents challenging problems, one of which is studied in this thesis. This problem, the composition problem, simply is creating a composite component from a collection of available components that, by interacting with each other, provide a requested functionality. When there are a large number of components available to be reused, finding a solution to the composition problem manually would require a considerable time and human effort. This could make the search practically impossible or unwieldy. However, performing the search automatically would save a significant amount of development time, cost and human effort. Solving this problem would be a huge step forward in the component-based software development. In this thesis, we concentrate on a subproblem of the composition problem, composition planning or synthesis, which is defined as finding a collection of useful components from the repository and the necessary communications among them to satisfy a requested functionality. For scalability purposes, we study automatic solutions to composition planning and propose two approaches in this regard. In one, we take advantage of graphs to model the repository, which is the collection of available components along with their behavioral specification. Graph search algorithms and a few composition-specific algorithms are used to find solutions for given component requests. In the other approach, we extend a logical reasoning algorithm and come up with algorithms for solving the composition planning problem. In both approaches we provide algorithms for finding the possibility of a composition, as well as finding the composition itself. We propose different types of composition and show how applying each would impact the behavior of a composite component. We provide the necessary formalism for capturing these types of composition through two different models: interface automata and composition algebra. Interface automata is an automaton-based model for representing the behavior of software components. The other model in this regard is composition algebra, which is an algebraic model based on CSP (Communicating Sequential Processes), CCS (Calculus of Communicating Systems), and interface automata. These formal models are used to validate the results returned by the composition approaches. We also compare the two composition approaches and show why each of them is suitable for specific types of the problem according to the repository attributes. We then evaluate the performance of the reasoning-based approach and provide some experimental results. In these experiments, we study how different attributes of the repository components could impact the performance of the reasoning-based approach in solving the composition planning problem

Hyperspectral Imagery Target Detection Using Improved Anomaly Detection and Signature Matching Methods

This research extends the field of hyperspectral target detection by developing autonomous anomaly detection and signature matching methodologies that reduce false alarms relative to existing benchmark detectors, and are practical for use in an operational environment. The proposed anomaly detection methodology adapts multivariate outlier detection algorithms for use with hyperspectral datasets containing tens of thousands of non-homogeneous, high-dimensional spectral signatures. In so doing, the limitations of existing, non-robust, anomaly detectors are identified, an autonomous clustering methodology is developed to divide an image into homogeneous background materials, and competing multivariate outlier detection methods are evaluated for their ability to uncover hyperspectral anomalies. To arrive at a final detection algorithm, robust parameter design methods are employed to determine parameter settings that achieve good detection performance over a range of hyperspectral images and targets, thereby removing the burden of these decisions from the user. The final anomaly detection algorithm is tested against existing local and global anomaly detectors, and is shown to achieve superior detection accuracy when applied to a diverse set of hyperspectral images. The proposed signature matching methodology employs image-based atmospheric correction techniques in an automated process to transform a target reflectance signature library into a set of image signatures. This set of signatures is combined with an existing linear filter to form a target detector that is shown to perform as well or better relative to detectors that rely on complicated, information-intensive, atmospheric correction schemes. The performance of the proposed methodology is assessed using a range of target materials in both woodland and desert hyperspectral scenes