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In this paper, a method with a significantly reduced feature set is described which recognizes human actions from video sequences. The proposed method is based on the natural domain knowledge of the human figure such as proportions of the human body. The method is evaluated on two of the publicly available databases in the literature of activity recognition, the Weizmann and the UIUC databases. Results...
Biometric key generation techniques are used to reliably generate cryptographic material from biometric signals. Existing constructions require users to perform a particular activity (e.g., type or say a password, or provide a handwritten signature), and are therefore not suitable for generating keys continuously. In this paper we present a new technique for biometric key generation from free-text...
Botnets have become one of the major tools used by attackers to perform various malicious activities on the Internet, such as launching distributed denial of service attacks, sending spam, leaking personal information, and so on. In this paper, we present BotCatch, a behavior-based botnet detection system that considers multiple coordinated group activities in the monitored network to identify bot-infected...
The Session Initiation Protocol (SIP) is an IETF-defined signaling protocol widely used for controlling communication sessions such as voice and video calls over Internet Protocol (IP). With wide applications of SIP, hiding secret data in some SIP header fields becomes a potential threat to many applications using SIP. In this paper, chaos theory is applied to analyze normal SIP traffic and a feature...
VoIP (Voice Over IP) was ranked third among the top 11 technologies of the decade in 2011. It is one of the most popular networking services. As it is readily adopted, the VoIP traffic is increasing steadily. The large amount of data transported by VoIP makes it ideal for creating covert channels. Attacks based on covert channels becomes a new challenge for network security. In this paper, possible...
In this paper we deal with pedestrian detection and propose the use of group lasso to learn from data a compact and meaningful representation out of a high dimensional dictionary of local features. Group lasso, a regularized method with a sparsity-enforcing penalty term, has the very nice property of performing feature selection while preserving the internal structure of the dictionary. In our study...
This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm...
The identification of P2P traffic has become a principal concern for the research community in the last years. Although several P2P traffic identification proposals can be found in the specialized literature, the problem still persists mainly due to obfuscation and privacy matters. This paper presents a flow-based P2P traffic identification scheme which is based on a multiple classification procedure...
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