Informatics Publishing Limited

K. Ravikumar ¹, A. Udhayakumar ², A. Anitha ³

Affiliations
1 Tamil University, Thanjavur, IN
2 Karpagam University, Coimbatore, IN
3 AM Jain College, Chennai, IN

Abstract

In this paper, thus the research analysis, design and implementation phase has been described for our research. It is proposed framework architecture for the Secure Multiparty Electronic Payments in mobile computing in order to support self-protection in AmI scenarios. The architecture of our framework is device-and platform independent and focuses on the use of auctions protocols for electronic payments policies. The top priority was the security of the auctions. All secret information that is exchanged between the auctions host and the peers is encrypted and protected against illegitimate modifications. it will extend the modularity of the proposed framework in order to allow individual utility functions and a replaceable module for determining the winning policy. Further, the integration of our framework into the refinement process of semantic high-level policies is in progress.

Keywords

Multi-party Security, Mobile Computing, Cryptography, Negotiation.

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A. Anitha ¹

Affiliations
1 Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli-627012, Tamil Nadu, IN

Abstract

The explosive growth of data in the internet makes the people with difficulty in accessing interested pages. Although several methods including Markov model and association rule are available for web access prediction, they have their own limitations in terms of predicting ability and state space complexity. In this paper, it is proposed to identify browsing pattern of people having similar interest using agglomerative clustering approach using k nearest neighbors, modified Markov model and association rule mining. The goal of this paper is to improve prediction accuracy. The homogeneity of clusters is improved very well by exact agglomeration. While doing agglomerative clustering there exist a trade-off between speed and accuracy. The slowness is overcome by reducing the object considered during agglomeration to k, instead of N-1 and by eliminating distant neighbors having similarity value above predefined threshold. Unlike rough sets, this approach considers objects that definitely belonging to a cluster during agglomeration. Hence, cluster validity is improved and computational complexity is reduced. Then, a dynamic Markov model is applied to generate matching states dynamically using cluster for test session. When ambiguity arises, Association rule mining and time-stamp parameter are used to resolve prediction conflicts. The comparative results are presented depicting the improvement in predictive accuracy of the proposed hybrid approach over other systems.

Keywords

Agglomerative Clustering, Association Rule, Markov Model, Pattern Discovery.

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A. Anitha ¹, S. V. Revathi ², S. Jeevanantham ², E. Eliza Godwin ²

Affiliations
1 School of Information Technology and Engineering, VIT University, Vellore, IN
2 VIT University, Vellore, IN

Abstract

The Internet plays a major role in today’s environment but many attacks are happening over the networks and it may cause serious issues. Intrusion detection system provides a way to prevent the network anomalies and threats. It plays a vital role in network security. The violation activity happenings over the networks can be prevented by intrusion detection system, it collects the detected activity using security information and event management (SIEM). Some IDS have the ability to respond to the detected intrusions. Systems with response capabilities are typically referred to as an intrusion prevention system. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are mostly used for threats detection.

Keywords

Intrusion Detection, Neural Networks, Knowledge Base.

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S. Rajakarthihan ¹, K. Gangadevi ¹, A. Anitha ¹, P. Palanichamy ²

Affiliations
1 Department of Physics, Thiagarajar College, Madurai-625009, IN
2 Non-Destructive Evaluation Division, Indira Gandhi Centre for Atomic Research, Kalpakkam-603102, IN

Abstract

Polymethylmethacrylate (PMMA) sample of 10 mm thickness and 15 mm diameter were prepared form a half a meter rod and exposed to ϒ-ray dose of different duration in an irradiation chamber with Ir-192 source. The polymer has been subjected to gamma radiation from 45 to 177 mGy dosages. Characterization by Ultrasonics, Fourier transform infra-red spectroscopy (FTIR) and ultraviolet-visible (UV-Vis) was done before and after irradiation. Precise ultrasonic measurements were made in the irradiated sample using 2 MHz longitudinal ultrasonic wave contact type transducer. Ultrasonic velocity measurements have been employed to investigate the microstructural changes in the irradiated sample. It was found that there is a decrease in velocity as the exposed dose is increased. FTIR study for the irradiated samples shows the enhanced CH stretching vibration. The UV-Vis studies for the irradiated samples indicate the shift in wavelength of absorption bands with the increasing irradiation dose was recorded. The result shows the variation in structural and optical properties of PMMA which is helpful for its stability under mild dose irradiations.

Keywords

ϒ-Ray Irradiation, Ultrasonic Velocity, FTIR, UV-Visible.

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A. Anitha ¹, S. Mythili ²

Affiliations
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN

Abstract

Security is the most vital issue to be addressed in Wireless Sensor Networks (WSNs). The WSN dominates since it has an effectiveness of applications in numerous fields. Though it has effectiveness towards its applications likewise it is susceptible to two different kinds of attacks (i.e.) external attacks and internal attacks existence of constrained reckoning resources, low memory, inadequate battery lifetime, handling control, and nonexistence of interfere resilient packet. Handle internal attacks such as selective forwarding attacks (SFAs) and black hole attacks (BHA) are considered to be the most common security extortions in wireless sensor networks. The attacker nodes will execute mischievous activities during data communication by creating traffic load, delaying packet delivery, dropping packets selectively or dropping all packets, energy consumption, and depleting all network resources. These attacks can be handled efficiently by implementing the proposed methodology for detecting, preventing, and recovering Cluster Heads (CHs), Cluster Members (CMs), and Transient Nodes (TNs) from SFAs and BHA in intra-cluster multi-hop. It is accomplished by proposing a robust strategy for overcoming internal attacks on cluster head, cluster member, and transient node. The Fuzzy C-Means clustering is used to discover the prominent cluster head. The uncertainty entropy model is used to detect internal attacks by removing the malicious node from the transition path. The intermediate node is been selected based on the degree and dimension. The experimental results of the proposed Robust Tristate Security Mechanism (RTSSM) against SFAs and BHA are evaluated with packet delivery ratio, throughput, and packet drop and the results prove the effectiveness of the proposed methodology and it also aids in the extension of the network lifetime.

Keywords

Cluster Head, Cluster Member, Intra-Cluster, Multi-Hop, Clustering, Wireless Sensor Networks, Uncertainty, Robust, Fuzzy Membership, Entropy.

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A. Anitha ¹, S. Mythili ²

Affiliations
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN

Abstract

Each sensor node functions autonomously to conduct data transmission in wireless sensor networks. It is very essential to focus on energy dissipation and sensor nodes lifespan. There are many existing energy consumption models, and the problem of selecting optimized cluster head along with efficient path selection is still challenging. To address this energy consumption issue in an effective way the proposed work is designed with a two-phase model for performing cluster head selection, clustering, and optimized route selection for the secure transmission of data packets with reduced overhead. The scope of the proposed methodology is to choose the most prominent cluster head and assistant cluster head which aids in prolonging the network lifespan and also securing the inter-cluster components from selective forwarding attack (SFA) and black hole attack (BHA). The proposed methodology is Empowered Chicken Swarm Optimization (ECSO) with Intuitionistic Fuzzy Trust Model (IFTM) in Inter-Cluster communication. ECSO provides an efficient clustering technique and cluster head selection and IFTM provides a secure and fast routing path from SFA and BHA for Inter-Cluster Single-Hop and Multi-Hop Communication. ESCO uses chaos theory for local optima in cluster head selection. The IFTM incorporates reliance of neighbourhood nodes, derived confidence of nodes, estimation of data propagation of nodes and an element of trustworthiness of nodes are used to implement security in inter-cluster communication. Experimental results prove that the proposed methodology outperforms the existing approaches by increasing packet delivery ratio and throughput, and minimizing packet drop ratio and energy consumption.

Keywords

Wireless Sensor Networks, Chicken Swarm Optimization, Intuitionistic Fuzzy Trust Model, Energy Aware, Security, Cluster Head, Clustering and Inter-Cluster Communication.

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