Search

This paper demonstrates how to prevent or mitigate insider threats in relational databases. It shows how different order of accesses to the same data items may pose different levels of threat. Moreover, it states the conditions that are required to regard a data item as expired. In addition, it introduces the two different methods of executing insiders΄ tasks, and how to prevent insider threat in those. The models presented in this paper organize accesses to data items in a particular sequence so that the availability of data items is maximized and the expected threat is minimized to the lowest level. Furthermore, it determines when to give an insider an incorrect but acceptable value of a risky data item in order to prevent a possible threat. [ABSTRACT FROM AUTHOR]

Intelligent agents are a new paradigm for developing software applications. Intelligent Agent (IA) can be defined to be an autonomous, problem-solving computational entity capable of effective operation in dynamic and open environments. Intelligent Agents are often deployed in environments in which they can interact, can cooperate, with other agents, including both people and software. In this paper Intelligent Agent architecture is proposed. The proposed architecture is capable to percept the dynamically changing environment. Based upon the perception, historical knowledge and internal design, the Intelligent Agent infers the action effecting the environment and updates the knowledgebase according to the action taken. Based upon the proposed Intelligent Agent architecture an Intelligent Medical Diagnosis System (IMDS) is given. [ABSTRACT FROM AUTHOR]

An inference engine for classification of Electrocardiogram (ECG) signals is developed with the help of a rule based rough set decision system. For this purpose an automated data extraction system from ECG strips is being developed by using a few image processing techniques. A knowledge base is developed after consulting different medical books as well as feedback of reputed cardiologists on interpretation and selection of essential time-plane features of ECG signal. An algorithm for extraction of different time domain features is also developed with the help of differentiation techniques and syntactic approaches. Finally, a rule-based rough set decision system is generated using these time-plane features for the development of an inference engine for disease classification. Two sets of rules are generated for this purpose. The first set is for general separation between normal and diseased subjects. The second set of rules is used for classifications between different diseases. [ABSTRACT FROM AUTHOR]