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List of Articles
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Open Access Article
1 - Bidirectional Transformation of Structural Modeling Elements between the UML Class Diagram and Object-Z
A. Rasoolzadegan Ahmad Abdollahzadeh BarforoushIn this paper, a new mechanism is proposed to transform the structural modeling elements of the UML class diagram and Object-Z specifications into each other. A set of bidirectional rules is defined to transform the mentioned elements into each other. Bidirectional tran MoreIn this paper, a new mechanism is proposed to transform the structural modeling elements of the UML class diagram and Object-Z specifications into each other. A set of bidirectional rules is defined to transform the mentioned elements into each other. Bidirectional transformation of the UML class diagram, as one of the most useful diagrams of UML, and Object-Z specifications into each other prepares the ground for the use of the unique advantages of both formal and visual modeling methods. The feasibility of the proposed approach is evaluated using the multi-lift case study. The results of conducting the multi-lift case study show that the proposed mechanism is feasible. Manuscript profile -
Open Access Article
2 - Fuzzy Voting for Anomaly Detection in Cluster-Based Mobile Ad Hoc Networks
Mohammad Rahmanimanesh Saeed JaliliIn this paper, an attack analysis and detection method in cluster-based mobile ad hoc networks with AODV routing protocol is proposed. The proposed method uses the anomaly detection approach for detecting attacks in which the required features for describing the normal MoreIn this paper, an attack analysis and detection method in cluster-based mobile ad hoc networks with AODV routing protocol is proposed. The proposed method uses the anomaly detection approach for detecting attacks in which the required features for describing the normal behavior of AODV protocol are defined via step by step analysis of AODV protocol and independent of any attack. In order to learn the normal behavior of AODV, a fuzzy voting method is used for combining support vector data description (SVDD), mixture of Gaussians (MoG), and self-organizing maps (SOM) one-class classifiers and the combined model is utilized to partially detect the attacks in cluster members. The votes of cluster members are periodically transmitted to the cluster head and final decision on attack detection is carried out in the cluster head. In the proposed method, a fuzzy voting method is used for aggregating the votes of cluster members in the cluster head by which the performance of the method improves significantly in detecting blackhole, rushing, route error fabrication, packet replication, and wormhole attacks. In this paper, an attack analysis method based on feature sensitivity ranking is also proposed that determines which features are influenced more by the mentioned attacks. This sensitivity ranking leads to the detection of the types of attacks launched on the network. Manuscript profile -
Open Access Article
3 - Gravity Oriented One-Class Classifier Based on Support Vector Data Descriptor
H. Ghafarian H. Sadoghi Yazdi Y. AllahyariIn this paper, a one-class classifier based on the Support Vector Data Descriptor (SVDD) is proposed. In SVDD, even outlier samples which are out of the decision boundary, are affecting the boundary. This increases the error of the classifier. In the proposed classifier MoreIn this paper, a one-class classifier based on the Support Vector Data Descriptor (SVDD) is proposed. In SVDD, even outlier samples which are out of the decision boundary, are affecting the boundary. This increases the error of the classifier. In the proposed classifier, decision boundary is determined by all of the samples through a gravity oriented approach. In this way, two classifier is proposed which in one of them knowledge about outliers are also considered. The optimization problem of the proposed method is convex and can be used with the kernel methods. Experiments on the behavior of the proposed classifier regarding changes of the parameters were done. Comparing results of experiments with results of SVDD and Density Induced SVDD shows that the proposed method can decrease the effects of outliers. Manuscript profile -
Open Access Article
4 - Structure-Texture Image Decomposition for Content-Based Image Retrieval
S. Hayati S. Saryazdi H. Nezamabadi-pourIn this paper, a novel low-level image feature extraction and indexing scheme based on structure-texture image decomposition is presented. The main idea of this work is to decompose database images to structure and texture sub-images to decrease the destructive effects MoreIn this paper, a novel low-level image feature extraction and indexing scheme based on structure-texture image decomposition is presented. The main idea of this work is to decompose database images to structure and texture sub-images to decrease the destructive effects of simultaneous existence of structure and texture information in the image in indexing phase. It is also shown that precision in a typical content-based image retrieval system can considerably increase by combining the feature vectors extracted from structure and texture sub-images. An image database containing 10000 images of 82 different semantic groups is used to evaluate the proposed method. The results confirm the effectiveness of this method. Manuscript profile -
Open Access Article
5 - Designing Optimal Fuzzy Classifier Using Particle Swarm Optimization
Seyed-Hamid ZahiriAn important issue in designing a fuzzy classifier is setting its structural and mathematical fuzzy parameters (e.g., number of rules, antecedents, consequents, types and locations of membership functions). In fact, the variations of these parameters establish a wide MoreAn important issue in designing a fuzzy classifier is setting its structural and mathematical fuzzy parameters (e.g., number of rules, antecedents, consequents, types and locations of membership functions). In fact, the variations of these parameters establish a wide range high dimensional search space, which makes heuristic methods some suitable candidates to solve this problem (designing optimal fuzzy parameters). In this paper, a method is described for this purpose. In presented technique, all fuzzy parameters of a fuzzy classifier, are interpreted in structure of particles and PSO algorithm is employed to find the optimal one. Extensive experimental results on well-known benchmarks and practical pattern recognition problem (automatic target recognition) demonstrate the effectiveness of the proposed method. Manuscript profile -
Open Access Article
6 - Design of a New Format-Compliant Partial Encryption Scheme for H.264 Video Design of a New Format-Compliant Partial Encryption Scheme for H.264 Video
S. Rasoolifar M. KhademiH.264 is the latest video compression standard and its compression efficiency is twice as much as previous standards. Due to the advantages of this standard and its widespread use in various video applications, the protection of this standard has become necessary. In th MoreH.264 is the latest video compression standard and its compression efficiency is twice as much as previous standards. Due to the advantages of this standard and its widespread use in various video applications, the protection of this standard has become necessary. In this paper, a new partial encryption scheme is presented for H.264 video which keeps the video format unchanged. In this method, parameters with high sensitivity to H.264 video texture and motion components are encrypted during compression. That is, such parameters as Intra4x4PredMode, Intra Residual Data, Ref-Index and MVD are encrypted using stream ciphers. This encryption scheme obtains high encryption efficiency through reducing the encrypted data volume along with high perceptual security. In addition to these properties, parameter selection and encryption in the proposed method is implemented in a way that the encrypted video format is kept compliant and thus can be utilized in different applications such as commercial and entertainment applications. Manuscript profile
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