Informatics Publishing Limited

G. Victo Sudha George ¹, V. Cyril Raj ²

Affiliations
1 Department of Computer Science and Engineering, Dr. M.G.R Educational and Research Institute University, Chennai-600095, Tamil Nadu, IN
2 Engineering and Technology, Dr. M.G.R Educational and Research Institute University, Chennai-600095, Tamil Nadu, IN

Abstract

This paper focuses on a stable feature selection framework using Cross Validation technique and SVM-RFE. Though SVMRFE has outperformed many of its counterparts in feature subset selection for accurate cancer classification, its greediness in selecting optimal feature subset affect the stability of selection process in successive runs that brings down the confidence on the selected features. In this paper, we propose an iterative backward feature selection method using SVMRFE motivated by cross-validation technique. Cumulative Ranking Score (CRS) is a parameter formulated to determine the class discrimination ability of each feature. The proposed method is applied on the publically available breast cancer dataset and found top 10 highly discriminative genes. Later the SVM classifier is trained using the top 10 genes identified by the proposed method and the original SVM-RFE separately and tested. It is proved that the proposed method has improved the classification accuracy significantly compared to the original SVM-RFE.

Keywords

Stable Feature Selection; Gene Expression Profile; Cross Validation; Backward Selection Method

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R. Manojkumar ¹, V. Cyril Raj ¹

Affiliations
1 Computer Science and Engineering, Dr MGR Educational and Research Institute, Maduravoyal, Chennai, TamilNadu, IN

Abstract

This paper proposes techniques to detect the vulnerabilities by performing scanning process for all website and web applications. The revealing process for vulnerabilities in ASP.NET websites/ applications is a complex process, where most of the code is anonymous and there are no citations to determine the purpose of the code. Due to the fact that ASP.NET which is part of .NET framework that separate the HTML code from the programming code in two files, one for (aspx) file and another for the programming code depending on the compiled language Visual Basic , C#, Java Script. Since the VB and C# are the most common languages in use around the world with ASP.NET files, we have adopted these two compiled languages in the construction of our proposed algorithm in addition to aspx files. Therefore, the scanning process inspects at least those three types of files aspx, VB and C#.

Keywords

Vulnerability, Web App, .NET Framework, Exploit, Assessment.

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B. Thanudas ¹, S. Sreelal ¹, B. S. Manoj ², V. Cyril Raj ³, Sumathy Eswaran ³

Affiliations
1 Vikram Sarabhai Space Centre, Thiruvananthapuram, Kerala, IN
2 Indian Institute of Space Science and Technology, Thiruvananthapuram, Kerala, IN
3 Dr.M.G.R. Educational and Research Institute University, Chennai, Tamil Nadu, IN

Abstract

Enterprise network security is becoming a very important and challenging task. Off-the-shelf tools and products are often found to be insufficient for large enterprises and government Research & Development (R&D) organizations. Many times, enterprise system administrators do not have the freedom to customize the network security systems of commercial type to the fullest needs of the enterprise. In addition, requirements of Government R&D establishments on providing the state-of-the-art information/cyber-security, are unable to be met by the commercial off-the-shelf enterprise network security suits. Such network security solutions like firewalls and intrusion detection systems (IDSs) provide only limited protection from the fast growing highly sophisticated cyber malwares (HSCMs). In this paper, we propose the agent-controller based security infrastructure for enterprise network for the use in Indian Space Research Organization (ISRO) and other government scientific R&D departments. The agent-controller infrastructure is tightly integrated with the organization’s network system in order to provide a highly customized solution.

Keywords

Enterprise Networks, Network Security, Highly Sophisticated Cyber Malwares, Agents, Controller, Intrusion Detection System, Firewall, Botnet, Anti-Virus.

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J. Ilamchezhian ¹, V. Cyril Raj ¹

Affiliations
1 Dr. MGR Educational and Research Institute, Chennai, Tamilnadu, IN

Abstract

The 3D Point cloud segmentation process is used in Image processing to detect the edges and the 3D structure and widely used in the computer vision and robotics. The 3D point cloud segmentation consists of three major processes: Point cloud data fitting on the 3D Array (Grid), Gradient calculation and thinning process. This process is computationally expensive due to many multiplication and addition which are required to calculate the gradient for the identification of edges, to find the location where a point to be located and stored and thinning process. This is why the existing algorithms are very slow to run on a single processor sequential programming. Therefore it is necessary to make it parallel for the high performance and to speed-up the computation. In this study, a parallel processing approach was used for the segmentation of 3D Point cloud image. The proposed method uses a 3D Vector structure grid concept for the creation of Virtual Grid to store the huge number of unordered points for the fast processing in order to find the neighborhood points. Our algorithm focuses on the fast extraction of edges by segmentation using gradient 3D sobel operator in parallel approach. The results show that the parallel approach will be efficient and provides a better performance in finding the edges. We evaluated this approach with 3 artificially generated data sets in two implementations: one in sequential and the other one in parallel. This new approach produces improved speedup in the edge detections process.

Keywords

Edge Detection, Gradient Method, Laser Scanning, Normal Vector Estimation, OpenMP, Point Cloud, Principal Component Analysis (PCA), Segmentation, Terrestrial Laser Scanning (TLS).

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S . Jeyabalan ¹, V. Cyril Raj ¹

Affiliations
1 Department of Computer Science Engineering, Dr. M.G.R. Educational and Research Institute University, Chennai - 600095, Tamil Nadu, IN

Abstract

In this research article, the network concepts are proving extensive study of gene function, Protein–Protein Interaction and biochemical communication pathway. Method/Analysis: The understanding of huge-size protein network data is depending on skill to identify significant cluster in its data sets, which is a computationally precise task. This brings a new scope to carry out research work which helps for determining new paths in graph and assist to solve the problem for identifying pathways in protein interaction networks. Findings: This idea breaks through to implement new technique called efficient spanning tree algorithm for finding an efficient pathway with in networks under numerous biologically motivated constraints. This method helps to hunt for protein pathways over Protein-Protein Interaction network. Application/Improvements: The analysis results confirmed that the proposed algorithm is capable of restructuring the signal pathways and to identify well qualified paths in an unsupervised method.

Keywords

Algorithm, Cluster, E-MST, Protein.

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R. Cristin ¹, V. Cyril Raj ²

Affiliations
1 Department of CSE, St. Peter’s University, Chennai - 600054, Tamil Nadu, IN
2 Dr. M.G.R University, Chennai - 600032, Tamil Nadu, IN

Abstract

Objectives: One of the principal problem in image forensics is identifying if a particular image is manipulated or not. Nowadays powerful image editing software increases the difficulty in finding the authentic image. Our approach is to detect curved surface manipulated area inserted in the photograph by describing a geometrical technique. Methods/ Statistical Analysis: This technique is combined with multiple image segmentation methodologies. The main objective of our work is to identify the manipulated area from the reflected images. Findings: Our contribution of this paper is to design a new geometrical relationship between the original and fake images. We use the new notations for this geometrical representation and combine these notations to the basic image segmentation methods. Finally we identify the fake reflected image using the different approaches and compare the results and produce the best performance of our work. Application/Improvements: The experimental result shows that our method achieves promising performance for tampering the curved surface reflections. The result of our work, we compared the 100 images and produce the best PSNR value and compression ratio.

Keywords

Curved Surface, Forgery Detection, Image Forensics, Reflection, Top-Hat.

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