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Phd Thesis In Computer System Security
can be based on home security thesis and library system or library management system thesis. Important documents and properties are ever under risk of being lost or destroyed. With the help of security system these documents can be protected from thieves or fire accidents and other hazards. Students of cryptography and researchers can do thesis on security system. Main users of security systems are multinational companies, military applications, and jewellery shops, hospital management, home security system, and library management security system. Security system performance is differs in different situations. For home security level is small but for organization security system must be high and also need high performance protecting software and hardware etc. Thesis can be based on various types of security such as home security, nation’s security, computer security, library management security system and child’s physical security.
Simulator such as VNS proved to be an effective training tool for
beginning security lessons. An interface from VNS to a small network security
prototype such as A2D2 developed by Angela Cearns at UCCS will
provide a more realistic learning, feedback, and evaluation environment for
computer network security. This project will explore the design and
development of such Hybrid system.
Security metrics for computer systems ..
Parallel computing on local area networks is based on a variety of mechanisms targeting the properties of this environment. However, these mechanisms do not effectively extend to wide area networks due to issues such as heterogeneity, security, and administrative boundaries. I present a prototype system which allows application programmers to write parallel programs in Java and allows Java-capable browsers to execute parallel tasks. It comprises a virtual machine model which isolates the program from the execution environment, and a runtime system realizing this machine on the Web. Load balancing and fault masking are transparently provided by the runtime system.
As the number of networked computers grows and the amount of sensitive information available on them grows as well there is an increasing need to ensure the security of these systems. The security of computer networks is not a new issue. We have dealt with the need for security for a long time with such measures as passwords and encryption. These will always provide an important initial line of defense. However, given a clever and malicious individual these defenses can often be circumvented. Intrusion detection is therefore needed as another way to protect computer systems. This thesis describes a novel three stage algorithm for building classification models in the presence of non-stationary, temporal, high dimensional data, in general, and for detecting network intrusion detections, in particular. Given a set of training data records the algorithm begins by identifying "interesting'' temporal patterns in this data using a modal logic. This approach is distinguished from other work in this area where frequent patterns are identified. We show that when frequency is replaced by our measure of "interestingness'' the problem of finding temporal patterns is NP-complete. We then offer an efficient heuristic approach that has proven effective in experiments. Having identified interesting patterns, these patterns then become the predictor variables in the construction of a Multivariate Adaptive Regression Splines (MARS) model. This approach will be justified, after surveying other methods for solving the classification problem, by its ability to capture complex nonlinear relationships between the predictor and response variables which is comparable to other heuristic approaches such as neural networks and classification trees, while offering improved computational properties such as rapid convergence and interpret-ability. After considering a variety of approaches to the problems of over-fitting which is inherent when modeling high dimensional data and non-stationarity, we describe our approach to addressing these issues through the use of truncated Stein shrinkage. This approach is motivated by showing the inadmissibility of the maximum likelihood estimator (MLE) in the high dimensional (dimension >= 3) data. We then discuss the application of our approach as participants in the 1999 DARPA Intrusion Detection Evaluation where we were able to exhibit the benefits of our approach. Finally, we suggest another area of research where we believe that our work would meet with similar success, namely, the area of disease classification.
New approaches to operating system security extensibility
It begins with an overview of the state of affairs, and several threat models. It continues with a description of Signet, a method to use SIM cards as trusted computing hardware to provide secure signed receipts. Next, Epothecary describes a low-infrastructure system for tracking pharmaceuticals that also significantly and asymmetrically increases costs for counterfeiters. The balance consists of a description of a low-cost Biometric Terminal currently in use by NGOs in India performing DOTS-based tuberculosis treatment, Blacknoise, an investigation into the use of low-cost cameraphones with noisy imaging sensors for image-based steganography, and finally Innoculous, a low-cost, crowdsourcing system for combating the spread of computer viruses, particularly among non-networked computers, while also collecting valuable "epidemiological" data.
From a theoretical perspective, we consider a discrete approximation model from light scattering theory which allows us to compute the speckle pattern for a given surface. Under this computational model, we show that given a speckle pattern, it is computationally hard to reconstruct the physical surface characteristics by simulating the multiple scattering of light. Using TextureSpeckle as a security primitive, we design secure protocols to enable a variety of scenarios such as: i) supply chain security, where applications range from drug tracking to inventory management, ii) mobile based secure transfer of money (mobile money), where any paper can be changed to an on-demand currency, and iii) fingerprint ecosystem, a cloud based system, where any physical object can be identified and authenticated on-demand.
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