V. N. Kamalesh ¹, S. K. Srivatsa ²

Affiliations
1 Dept. of Computer Science & Engg., Sathyabama University, IN
2 St. Joseph College of Engineering, Chennai, IN

Abstract

The topological design of a computer communication network assigns the links and link capacities for connecting network nodes within several constraints, with a goal to achieve a specified performance at a minimal cost. A reasonable approach is to generate a potential network topology. This paper presents a spanning tree based method for systematic numbering of nodes in any communication network. When the nodes are numbered in a systematic manner the potential network topology generated will have lesser amount of perturbation before an acceptable network is found.

Keywords

Topological Design, Computer, Link Deficit Algorithm, Wireless Network, Minimum Spanning Tree

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M. Rajendiran ¹, S. K. Srivatsa ²

Affiliations
1 Department of Master of Computer Applications, Panimalar Engineering College, Chennai -600123, IN
2 Department of Computer Science and Engineering, Sathyabama University, Chennai- 600119, IN

Abstract

In recent years' mobile ad hoc networks (MANETs), a group oriented services has one of the primary application classes. It supports such services that use multicast routing. Therefore it is required to design stable and an efficient routing protocol for MANETs to support better packet delivery ratio, minimum delays and decreased overheads. In this paper, a multicast routing protocol based mesh networks that finds stable multicast path from source to receivers is proposed. In this model only the nodes that fulfill the delay requirements can flood the JOIN-QUERY messages. The contributing nodes are assumed to follow M/M/1 queuing systems. The queuing systems contain maximum value for queuing and contention delay which can be evaluated as the ratio of maximum queue size over the service time in a node. This model enhances link stability with contention delay and queuing system. The stable routes are found based on selection of stable forwarding nodes that have high stability of link connectivity. The link stability is calculated by using parameters link received power, distance between neighboring nodes and link quality. The performance of the proposed model is simulated over a large number of MANET nodes with wide range of mobility with two well known mesh based multicast routing protocol. It is observed that the proposed model produces better throughput and reduced overheads.

Keywords

Multicast Routing, MANET, Stable Forwarding Node, Multicast Routing, Link Stability

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B. Senthil Kumar ¹, S. K. Srivatsa ²

Affiliations
1 St. Peter’s University, Chennai - 600054, Tamil Nadu, IN
2 Anna University, Chennai - 600025, Tamil Nadu, IN

Abstract

Background: Cognitive radio is being recognized as an intelligent technology due to its ability to rapidly and autonomously adapt operating parameters to changing environments and conditions. In order to reliably and swiftly detect spectrum holes in cognitive radios, spectrum sensing must be used. Accurate spectrum sensing is important in improving the efficiency of cognitive radio networks. False sensing results in either waste of spectrum or harmful interference to primary users who may remotely or physically capture the sensors and manipulate the sensing reports. Methods: A novel framework and an innovative approach have been introduced to eliminate the malicious behaviors of secondary users. It is found that spectrum sensing alone cannot prevent the malicious behavior without any information on users’ reputation. Based on the evaluation of malicious behavior resistance methods, joint spectrum sensing and malicious nodes detection approach for optimal prevention from sensing falsification is being proposed. Findings: The proposed approach minimizes Linear Minimum Mean-Square Errors (LMMSEs) when it is compared with the existing algorithms such spectrum sensing based on HSMM and FNN based spectrum sensing are plotted versus detection probability, false alarm probability. With more malicious nodes proposed schemes are more effective to restrain the false alarms. Improvement/Application: The proposed spectrum sensesframework with attack detection which is very effective to determine the malicious users in spectrum holes.

Keywords

Fuzzy Neural Network, Linear Minimum Mean Square Error, Primary User, Secondary User, Spectrum Sensing

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S. Vishnu Priyan ¹, S. K. Srivatsa ²

Affiliations
1 St. Peter’s University, Chennai - 600054, Tamil Nadu, IN
2 Anna University, Chennai - 600025, Tamil Nadu, IN

Abstract

Background: The existing JPEG error analysis schemes do not offer agreeable results particularly when the duplicated area is small. Region duplication is an uncomplicated and efficient process to produce digital image forgeries, where a constant segment of pixels in an image, following feasible geometrical and illumination transformations are copied and pasted to a different location in the same image. Methods: In this research work, JPEG error analysis scheme is introduced for the purpose of consistent recognition of duplicated and distorted areas in a JPEG digital image forensics. Here, presented a new Multi-directional Curvelet Transform with Fourier Transform matching Invariant Rotation (MCFTIR) region duplication detection scheme to identify duplicated regions for JPEG images. This scheme begins with estimating the overlapping blocks of a JPEG image and it is organized in accordance with the statistics of multiple curvelet sub-bands. During the second phase, the amount of candidate block pairs of JPEG images has been significantly diminished by means of spatial distance between each pair of blocks for JPEG image. For duplicate region removed images theoretically analyzing the effects of these errors on single and double JPEG compression, with five major phases like Shape-Preserving Image Resizing (SPIR) scheme for the purpose of image resizing, noises are appended to image and eliminated with the help of Hybrid Non-Local Means Filtering (HNLMF) denoising framework, Image compression through Discrete Cosine Transform – Singular Value Decomposition (DCT-SVD) was computed for single and double image compression, images were quantized by means of numerous quantization matrices, quantization matrix results are estimated with Mamdani model based Adaptive Neural Fuzzy Inference System (MANFIS) and detecting the quantization table of a JPEG image. Findings: The proposed MCFTIR methods significantly outperform existing techniques in terms of the parameters like Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) especially for the images of small sizes. It also show that the new MCFTIR method can consistently identify JPEG image blocks which are as tiny as 8x8 pixels and compressed through quality factors as elevated as 98. This performance is significant for the purpose of analyzing and locating small tampered regions inside a composite image.

Keywords

Duplicate Region Detection, Image Denoising, Image Resizing, JPEG Image Compression, Mamdani Model Based Adaptive Neural Fuzzy Inference System (MANFIS), Multi-Directional Curvelet Transform with Fourier Transform Matching Invariant Rotation (MCFTIR)

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R. Vallikannu ¹, A. George ², S. K. Srivatsa ³

Affiliations
1 Hindustan University, Chennai - 603103, Tamil Nadu, IN
2 Periyar Maniyammai University, Thanjavur - 613403, Tamil Nadu, IN
3 Prathyusha Engineering College, Tiruvallur - 602025, Tamil Nadu, IN

Abstract

Recent introduction of hybrid architectures in Mobile Adhoc NETworks (MANETs) made researchers to concentrate on routing techniques to prolong the network lifetime with improved performance and scalability. Major research activity has been carried out to explore and improve constrained lifespan of the network by proposing on - demand power aware routing protocols. However, these protocols try to increase the network life time but doesn’t guarantee a network remain operational forever. Charging of premature failure nodes which were frequently used as relying nodes is essential to prolong network lifespan. Therefore, to improve network connectivity and lifespan, it’s essential to charge energy drained nodes based on their expected lifetime. Hence, we propose a dynamic and secure routing cum energy recharging scheme using Mobile Power Back Ferry Nodes (MPBF) to recharge energy drained nodes. Consumption of energy from the MPBF nodes affords a most trustworthy energy supply than deriving energy from other sources. This approach retains the node energy to maximum time with improved battery life by selecting a gateway based on link weight age. Secure Source- Based Loose Synchronization (SOBAS) protocol is used for authenticated power transfer. The total number of MPBF nodes required for the optimum energy conservation is determined by the target detection mechanism assigned by the Secured Sink Trail (SST). Using this joint methodology, the network lifetime and percentage of energy consumption of mobile nodes under two different scenarios (a) Variable node velocity and network traffic with fixed node density (b) Variable node density and node velocity with fixed network traffic are analyzed. We evaluate the proposed scheme performance through NS2 simulations. The results show that the proposed scheme can retain the network lifetime for a longer duration. Its performance is compared with power aware and ACO based Dynamic Power Control and load balanced energy efficient routing protocols under different QoS scenarios.

Keywords

Joint routing, Energy Conservation, Mobile Power Back (MPB), Residual Energy, Secure Sink Trial, SOBAS, QoS Analysis.

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C. Ambikavathi ¹, S. K. Srivatsa ²

Affiliations
1 Sathyabama University, Chennai, Tamil Nadu, IN
2 Prathyusha Institute of Technology and Management, Chennai, Tamil Nadu, IN

Abstract

Objectives: Intrusion Detection System (IDS) models and methods are integrated for better detection of intruders and mitigation of false alarms. Integrated IDS is proposed to provide security in a cloud environment. Methods: The distributed and dynamic nature of cloud environment leads to critical issues like huge log analysis, heterogeneous traffic aggregation and scalability, etc. Intrusion specific data classification and false alarms degrades performance. This integrated model integrates both IDS models and IDS methodologies. Host-based IDS (H-IDS) model integrates with network-based IDS (N-IDS) model, as well as signature and anomaly based IDS methods are integrated to get the best of each. Findings: Whenever a Virtual Machine (VM) is created, H-IDS is in-built into its operating system to monitor the activities within that VM. N-IDS is deployed at strategic locations within the cloud network to monitor the traffic between the virtual machines and from the outside environment. Any malicious activity initiated by a cloud user using their virtual machine is detected by H-IDS. The packets flowing through the cloud network are captured and analyzed by N-IDS to detect infected packets send by hackers. The weakness of one methodology is compromised by the other during integration, but if the methods are used separately they are ineffective. Known attacks can be detected by signature based IDS and the new/unknown attack patterns are identified by anomaly based IDS. The major drawback of anomaly based IDS is high false alarm rate. It can be overcome by signature based IDS. This proposed work is implemented using Opennebula, for constructing a cloud environment and tested with IDS tools. Improvements: This integration leads to improve cloud security and trust among consumers. IDS specific issues are also rectified such as false alarms, heterogeneity etc.

Keywords

Anomaly Based Detection, Cloud Computing, Intrusion Detection System, Signature Based Detection, Virtualization.

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