817 resultados para Intrusion Detection, Computer Security, Misuse
Resumo:
We describe a tool for analysing information flow in security hardware. It identifies both sub-circuits critical to the preservation of security as well as the potential for information flow due to hardware failure. The tool allows for the composition of both logical and physical views of circuit designs. An example based on a cryptographic device is provided.
Resumo:
The verification of information flow properties of security devices is difficult because it involves the analysis of schematic diagrams, artwork, embedded software, etc. In addition, a typical security device has many modes, partial information flow, and needs to be fault tolerant. We propose a new approach to the verification of such devices based upon checking abstract information flow properties expressed as graphs. This approach has been implemented in software, and successfully used to find possible paths of information flow through security devices.
Resumo:
Security protocols preserve essential properties, such as confidentiality and authentication, of electronically transmitted data. However, such properties cannot be directly expressed or verified in contemporary formal methods. Via a detailed example, we describe the phases needed to formalise and verify the correctness of a security protocol in the state-oriented Z formalism.
Resumo:
Security protocols are often modelled at a high level of abstraction, potentially overlooking implementation-dependent vulnerabilities. Here we use the Z specification language's rich set of data structures to formally model potentially ambiguous messages that may be exploited in a 'type flaw' attack. We then show how to formally verify whether or not such an attack is actually possible in a particular protocol using Z's schema calculus.
Resumo:
This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.
Resumo:
This thesis deals with the challenging problem of designing systems able to perceive objects in underwater environments. In the last few decades research activities in robotics have advanced the state of art regarding intervention capabilities of autonomous systems. State of art in fields such as localization and navigation, real time perception and cognition, safe action and manipulation capabilities, applied to ground environments (both indoor and outdoor) has now reached such a readiness level that it allows high level autonomous operations. On the opposite side, the underwater environment remains a very difficult one for autonomous robots. Water influences the mechanical and electrical design of systems, interferes with sensors by limiting their capabilities, heavily impacts on data transmissions, and generally requires systems with low power consumption in order to enable reasonable mission duration. Interest in underwater applications is driven by needs of exploring and intervening in environments in which human capabilities are very limited. Nowadays, most underwater field operations are carried out by manned or remotely operated vehicles, deployed for explorations and limited intervention missions. Manned vehicles, directly on-board controlled, expose human operators to risks related to the stay in field of the mission, within a hostile environment. Remotely Operated Vehicles (ROV) currently represent the most advanced technology for underwater intervention services available on the market. These vehicles can be remotely operated for long time but they need support from an oceanographic vessel with multiple teams of highly specialized pilots. Vehicles equipped with multiple state-of-art sensors and capable to autonomously plan missions have been deployed in the last ten years and exploited as observers for underwater fauna, seabed, ship wrecks, and so on. On the other hand, underwater operations like object recovery and equipment maintenance are still challenging tasks to be conducted without human supervision since they require object perception and localization with much higher accuracy and robustness, to a degree seldom available in Autonomous Underwater Vehicles (AUV). This thesis reports the study, from design to deployment and evaluation, of a general purpose and configurable platform dedicated to stereo-vision perception in underwater environments. Several aspects related to the peculiar environment characteristics have been taken into account during all stages of system design and evaluation: depth of operation and light conditions, together with water turbidity and external weather, heavily impact on perception capabilities. The vision platform proposed in this work is a modular system comprising off-the-shelf components for both the imaging sensors and the computational unit, linked by a high performance ethernet network bus. The adopted design philosophy aims at achieving high flexibility in terms of feasible perception applications, that should not be as limited as in case of a special-purpose and dedicated hardware. Flexibility is required by the variability of underwater environments, with water conditions ranging from clear to turbid, light backscattering varying with daylight and depth, strong color distortion, and other environmental factors. Furthermore, the proposed modular design ensures an easier maintenance and update of the system over time. Performance of the proposed system, in terms of perception capabilities, has been evaluated in several underwater contexts taking advantage of the opportunity offered by the MARIS national project. Design issues like energy power consumption, heat dissipation and network capabilities have been evaluated in different scenarios. Finally, real-world experiments, conducted in multiple and variable underwater contexts, including open sea waters, have led to the collection of several datasets that have been publicly released to the scientific community. The vision system has been integrated in a state of the art AUV equipped with a robotic arm and gripper, and has been exploited in the robot control loop to successfully perform underwater grasping operations.
Resumo:
A method is proposed to offer privacy in computer communications, using symmetric product block ciphers. The security protocol involved a cipher negotiation stage, in which two communicating parties select privately a cipher from a public cipher space. The cipher negotiation process includes an on-line cipher evaluation stage, in which the cryptographic strength of the proposed cipher is estimated. The cryptographic strength of the ciphers is measured by confusion and diffusion. A method is proposed to describe quantitatively these two properties. For the calculation of confusion and diffusion a number of parameters are defined, such as the confusion and diffusion matrices and the marginal diffusion. These parameters involve computationally intensive calculations that are performed off-line, before any communication takes place. Once they are calculated, they are used to obtain estimation equations, which are used for on-line, fast evaluation of the confusion and diffusion of the negotiated cipher. A technique proposed in this thesis describes how to calculate the parameters and how to use the results for fast estimation of confusion and diffusion for any cipher instance within the defined cipher space.
Resumo:
This paper aims to identify the communication goal(s) of a user's information-seeking query out of a finite set of within-domain goals in natural language queries. It proposes using Tree-Augmented Naive Bayes networks (TANs) for goal detection. The problem is formulated as N binary decisions, and each is performed by a TAN. Comparative study has been carried out to compare the performance with Naive Bayes, fully-connected TANs, and multi-layer neural networks. Experimental results show that TANs consistently give better results when tested on the ATIS and DARPA Communicator corpora.
Resumo:
Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.
Resumo:
Increasingly users are seen as the weak link in the chain, when it comes to the security of corporate information. Should the users of computer systems act in any inappropriate or insecure manner, then they may put their employers in danger of financial losses, information degradation or litigation, and themselves in danger of dismissal or prosecution. This is a particularly important concern for knowledge-intensive organisations, such as universities, as the effective conduct of their core teaching and research activities is becoming ever more reliant on the availability, integrity and accuracy of computer-based information resources. One increasingly important mechanism for reducing the occurrence of inappropriate behaviours, and in so doing, protecting corporate information, is through the formulation and application of a formal ‘acceptable use policy (AUP). Whilst the AUP has attracted some academic interest, it has tended to be prescriptive and overly focussed on the role of the Internet, and there is relatively little empirical material that explicitly addresses the purpose, positioning or content of real acceptable use policies. The broad aim of the study, reported in this paper, is to fill this gap in the literature by critically examining the structure and composition of a sample of authentic policies – taken from the higher education sector – rather than simply making general prescriptions about what they ought to contain. There are two important conclusions to be drawn from this study: (1) the primary role of the AUP appears to be as a mechanism for dealing with unacceptable behaviour, rather than proactively promoting desirable and effective security behaviours, and (2) the wide variation found in the coverage and positioning of the reviewed policies is unlikely to be fostering a coherent approach to security management, across the higher education sector.