A multiagent based strategy for detecting attacks in databases in a distributed mode

This paper presents a distributed hierarchical multiagent architecture for detecting SQL injection attacks against databases. It uses a novel strategy, which is supported by a Case-Based Reasoning mechanism, which provides to the classifier agents with a great capacity of learning and adaptation to face this type of attack. The architecture combines strategies of intrusion detection systems such as misuse detection and anomaly detection. It has been tested and the results are presented in this paper.

Enhancing student learning with case-based teaching and audience response systems in an interdisciplinary Food Science course

A growing body of research in higher education suggests that teachers should move away from traditional lecturing towards more active and student-focus education approaches. Several classroom techniques are available to engage students and achieve more effective teaching and better learning experiences. The purpose of this paper is to share an example of how two of them – case-based teaching, and the use of response technologies – were implemented into a graduate-level food science course. The paper focuses in particular on teaching sensory science and sensometrics, including several concrete examples used during the course, and discussing in each case some of the observed outcomes. Overall, it was observed that the particular initiatives were effective in engaging student participation and promoting a more active way of learning. Case-base teaching provided students with the opportunity to apply their knowledge and their analytical skills to complex, real-life scenarios relevant to the subject matter. The use of audience response systems further facilitated class discussion, and was extremely well received by the students, providing a more enjoyable classroom experience.