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Abstract: A DoS attack can be regarded as an attempt of attackers to prevent legal users from gaining a normal network service. The TCP connection management protocol sets a position for a classic DoS attack, namely, the SYN flood attack. In this attack some sources send a large number of TCP SYN segments, without completing the third handshake step to quickly exhaust connection resources of the under attack system. This paper models the under attack server by using the queuing theory in which attack requests are recognized based on their long service time. Then it proposes a framework in which the defense issue is formulated as an optimization problem and employs the particle swarm optimization (PSO) algorithm to optimally solve this problem. PSO tries to direct the server to an optimum defense point by dynamically setting two TCP parameters, namely, maximum number of connections and maximum duration of a half-open connection. The simulation results show that the proposed defense strategy improves the performance of the under attack system in terms of rejection probability of connection requests and efficient consumption of buffer space. [Copyright &y& Elsevier]

Abstract: In this paper an attempt is made to extend some standard results in set theory on the basis of soft set relations. Antisymmetric relation and transitive closure of a soft set relation are introduced and an analogue of Warshall’s algorithm is proposed for calculating the transitive closure of a soft set relation. Ordering on a soft set is defined and some set theoretical results based on this are proved. [Copyright &y& Elsevier]

Abstract: In this paper, an algorithm for approximate calculation of the attainable sets of nonlinear control systems with integral constraint on controls is presented. A numerical example of the computer application of this algorithm is also given. [Copyright &y& Elsevier]

Abstract: In this paper we propose a robust clustering method for handling -type fuzzy numbers. The proposed method based on similarity measures is not necessary to specify the cluster number and initials. Several numerical examples demonstrate the effectiveness of the proposed robust clustering method, especially robust to outliers, different cluster shapes and initial guess. We then apply this algorithm to three real data sets. These are Taiwanese tea, student data and patient blood pressure data sets. Because tea evaluation comes under an expert subjective judgment for Taiwanese tea, the quality levels are ambiguity and imprecision inherent to human perception. Thus, -type fuzzy numbers are used to describe these quality levels. The proposed robust clustering method successfully establishes a performance evaluation system to help consumers better understand and choose Taiwanese tea. Similarly, -type fuzzy numbers are also used to describe data types for student and patient blood pressure data. The proposed method actually presents good clustering results for these real data sets. [Copyright &y& Elsevier]