9 research outputs found

    An ecological approach to anomaly detection: the EIA Model.

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    The presented work proposes a new approach for anomaly detection. This approach is based on changes in a population of evolving agents under stress. If conditions are appropriate, changes in the population (modeled by the bioindicators) are representative of the alterations to the environment. This approach, based on an ecological view, improves functionally traditional approaches to the detection of anomalies. To verify this assertion, experiments based on Network Intrussion Detection Systems are presented. The results are compared with the behaviour of other bioinspired approaches and machine learning techniques

    A Risk Management Approach to the “Insider Threat”

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    Recent surveys indicate that the financial impact and operating losses due to insider intrusions are increasing. But these studies often disagree on what constitutes an "insider;" indeed, many define it only implicitly. In theory, appropriate selection of, and enforcement of, properly specified security policies should prevent legitimate users from abusing their access to computer systems, information, and other resources. However, even if policies could be expressed precisely, the natural mapping between the natural language expression of a security policy, and the expression of that policy in a form that can be implemented on a computer system or network, creates gaps in enforcement. This paper defines "insider" precisely, in terms of these gaps, and explores an access-based model for analyzing threats that include those usually termed "insider threats." This model enables an organization to order its resources based on the business value for that resource and of the information it contains. By identifying those users with access to high-value resources, we obtain an ordered list of users who can cause the greatest amount of damage. Concurrently with this, we examine psychological indicators in order to determine which users are at the greatest risk of acting inappropriately. We conclude by examining how to merge this model with one of forensic logging and auditing
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