This paper investigates how intrusion detection system (IDS) sensors should best be placed on a network when there are several competing evaluation criteria. This is a computationally difficult problem and we show how...
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ISBN:
(纸本)9783642040900
This paper investigates how intrusion detection system (IDS) sensors should best be placed on a network when there are several competing evaluation criteria. This is a computationally difficult problem and we show how Multi-Objective Genetic Algorithms provide an excellent means of searching for optimal placements.
Vehicular ad-hoc networks (vanets) are ad-hoc networks specially thought to provide communication among vehicles. The information in vanets can be shared among vehicles or sent in unicast, multicast or broadcast mode ...
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ISBN:
(纸本)9783642040900
Vehicular ad-hoc networks (vanets) are ad-hoc networks specially thought to provide communication among vehicles. The information in vanets can be shared among vehicles or sent in unicast, multicast or broadcast mode with the main goal of improving safety or even providing multimedia or commercial services. Several protocols and techniques have been proposed to he used in specific scenarios depending on the vehicle density and the spatial distribution. Anyway, it is necessary to have a tool for testing different scenarios and protocols proposed. Although simulation is usually a powerful technique for evaluating wireless or routing protocols, it is also necessary to have a real test bench to implement the protocols that could be already simulated with success. In this paper, we present a real framework for vanets that use wireless communication among vehicles and RFID for different traffic signalling information, such as bus stop or semaphore location, speed limit information, etc.
In the last decades digital forensics have become a prominent activity in modern investigations. Indeed, an important data source is often constituted by information contained in devices on which investigational activ...
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ISBN:
(纸本)9783642040900
In the last decades digital forensics have become a prominent activity in modern investigations. Indeed, an important data source is often constituted by information contained in devices on which investigational activity is performed. Due to the complexity of this inquiring activity, the digital tools used for investigation constitute a central concern. In this paper a clustering-based text mining technique is introduced for investigational purposes. The proposed methodology is experimentally applied to the publicly available Enron dataset that well fits a plausible forensics analysis context.
In recent years there has been an increased interest in Human-Computer Interaction Systems allowing for more natural communication with machines. Such systems are especially important for elderly and disabled persons....
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ISBN:
(纸本)9783642032011
In recent years there has been an increased interest in Human-Computer Interaction Systems allowing for more natural communication with machines. Such systems are especially important for elderly and disabled persons. The paper presents a vision-based system for detection of long voluntary eye blinks and interpretation of blink patterns for communication between man and machine. The blink-controlled applications developed for this system have been described, i.e. the spelling program and the eye-controlled web browser.
This paper considers an expectation optimization model using a possibility measure to the objective function in the fuzzy random programming problem, based on possibilistic programming and stochastic programming. The ...
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ISBN:
(纸本)9783540896180
This paper considers an expectation optimization model using a possibility measure to the objective function in the fuzzy random programming problem, based on possibilistic programming and stochastic programming. The main fuzzy random programming problem is not a well-defined problem due to including random variables and fuzzy numbers. Therefore, in order to solve it analytically, a criterion for goal of objective function is set and the chance constraint are introduced. Then, considering decision maker's subjectivity and flexibility of the original plan, a fuzzy goal for each objective function is introduced. Furthermore, this paper considers that the occurrence probability of each scenario has ambiguity, and is represented as an interval value. Considering this interval of probability, a robust expectation optimization problem is proposed. Main problem is transformed into the deterministic equivalent linear programming problem, and so the analytical solution method extending previous solution approaches is constructed.
Complex systems may have many components that not only interact but also compete with one another to deliver the best they can to reach the desired system objective. As the number of components grows, complexity and c...
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ISBN:
(纸本)9783540896180
Complex systems may have many components that not only interact but also compete with one another to deliver the best they can to reach the desired system objective. As the number of components grows, complexity and communication also grow, making them computationally cumbersome to be treated in a centralized way. It may be better to handle them in a distributed way and decomposed into components/variables that can be seen as a collective of agents or a Multi-Agent System (MAS). The major challenge is to make these agents work in a coordinated way, optimizing their local utilities and contributing towards optimization of the global objective. This paper implements the theory of Collective Intelligence (COIN) using Probability Collectives (PC) in a slightly different way from the original PC approach to achieve the global goal. The approach is demonstrated successfully using Rosenbrock Function in which the variables are seen as agents working independently but collectively towards a global objective.
Bit-level information is useful in image coding especially in image compression. A digital image is constructed by multilevel information of bits, called as bit-plane information. For an 8-bits gray level digital imag...
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ISBN:
(纸本)9783540896180
Bit-level information is useful in image coding especially in image compression. A digital image is constructed by multilevel information of bits, called as bit-plane information. For an 8-bits gray level digital image, bit-plane extraction has ability to extract 8 layers of bit-plane information. Conventional neural network-based face recognition usually used gray images as training and testing data. This paper presents a novel method of using bit-level images as input to feedforward neural network. CMU AMP Face Expression Database is used in the experiments. Experiment result showed improvement in recognition rate, false acceptance rate (FAR), false rejection rate (FRR) and half total error rate (HTER) for the proposed method. Additional improvement is proposed by introducing dummy blank images which consist of plain 0 and 1 images in the neural network training set. Experiment result showed that the final proposed method of introducing dummy blank images improve FAR by 3.5%.
Formal knowledge representation methods in computer-assisted decision making systems are considered. A concept of infosphere and of its historical evolution is presented. Representation of knowledge in the form of fac...
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ISBN:
(纸本)9783642032011
Formal knowledge representation methods in computer-assisted decision making systems are considered. A concept of infosphere and of its historical evolution is presented. Representation of knowledge in the form of factual, implicative and deontic statements as well as of evaluating meta-statements is described and their representation by formal structures is illustrated by examples. It is shown that ontological models based on formal structures can be used both to a reduction of semantic redundancy in knowledge bases and to semantically equivalent reformulation of queries ordered to the knowledge base. Application of ontological models as a source of knowledge used in decision making is illustrated by an example.
The increasing use of encrypted traffic combined with non-standard port associations makes the task of traffic identification increasingly difficult. This work adopts a multi-objective clustering approach to the probl...
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ISBN:
(纸本)9783642040900
The increasing use of encrypted traffic combined with non-standard port associations makes the task of traffic identification increasingly difficult. This work adopts a multi-objective clustering approach to the problem in which a Genetic Algorithm performs both feature selection and cluster count optimization under a flow based representation. Solutions do not use port numbers, IP address or payload. Performance of the resulting model provides 90% detection 0.8% false positive rates with 13 clusters supported by 14 of the original 38 features.
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