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Suhasini, A.
- Encrypting Data before Moving it to the Cloud using Specter Encrytion
Abstract Views :167 |
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Authors
Affiliations
1 Department of Computer Science and Engineering, Annamalai University, Chidambaram - 608002, Tamil Nadu, IN
2 Department of Information Technology, AVCCE, Mayiladuthurai, Nagapattinam – 609305, Tamil Nadu, IN
1 Department of Computer Science and Engineering, Annamalai University, Chidambaram - 608002, Tamil Nadu, IN
2 Department of Information Technology, AVCCE, Mayiladuthurai, Nagapattinam – 609305, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 24 (2015), Pagination:Abstract
Cloud Computing is the current technology that revolutionize the mobile and IT trade. Most of the mobile vendors'area unit providing extended information storage over the cloud either with the third party cloud service supplier like Samsung golem good phones with Drop Box storage. On the opposite hand, Apple iPhone and Windows Phone have their own cloud information storage like iCloud and SkyDrive severally. However, mobile phone cloud application user's area unit hesitant to maneuver their information from their itinerant to the cloud service supplier due to increasing information security and privacy concern. During this paper, a mobile information security cryptography model is planned to encounter this downside. With the technical advancement within the mobile and cloud computing, a cryptography algorithmic programis intended referred to as Specter, Geometric Host for Mobile information SecurityKeywords
Cloud Computing, Data Security, Encryption.Full Text
- Automated Skin Defect Identification System for Orange Fruit Grading Based on Genetic Algorithm
Abstract Views :247 |
PDF Views:103
Authors
R. Thendral
1,
A. Suhasini
1
Affiliations
1 Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar, Chidambaram 608 002, IN
1 Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar, Chidambaram 608 002, IN
Source
Current Science, Vol 112, No 08 (2017), Pagination: 1704-1711Abstract
Using machine vision technology to grade oranges can ensure that only good-quality fruits are exported. One of the most prominent issues in the post-harvest processing of oranges is the efficient determination of skin defects with the intention of classifying the fruits depending on their external appearance. Shape, size, colour and texture are the important grading parameters that dictate the quality and value of many fruit products. The accuracy of the evaluation results is increased by proper combination of different grading parameters. This article presents an efficient orange surface grading system (normal and defective) based on the colour and texture features. As a part of the feature selection step, this article presents a wrapper approach with genetic algorithm to search out and identify the informative feature subset for classification. The selected features were subjected to various classifiers such as support vector machine, back propagation neural network and auto associative neural network (AANN) to study the performance analysis among these three classifiers. The results reveal that AANN classification algorithm has the highest accuracy rate of 94.5% among these three classifiers.Keywords
Colour and Texture Features, Genetic Algorithm, Oranges, Skin Defect Identification.Full Text
References
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- Efficient Multipath Zone-Based Routing in MANET Using (TID-ZMGR) Ticked-ID Based Zone Manager
Abstract Views :282 |
PDF Views:2
Authors
Affiliations
1 Department Computer Science and Engineering, Saranathan College of Engineering, Trichy, Tamil Nadu, IN
2 Department Computer Science and Engineering, Annamalai University, Tamil Nadu, IN
3 Department of Electronics and Communications Engineering, Saranathan College of Engineering, Trichy, Tamil Nadu, IN
1 Department Computer Science and Engineering, Saranathan College of Engineering, Trichy, Tamil Nadu, IN
2 Department Computer Science and Engineering, Annamalai University, Tamil Nadu, IN
3 Department of Electronics and Communications Engineering, Saranathan College of Engineering, Trichy, Tamil Nadu, IN
Source
International Journal of Computer Networks and Applications, Vol 8, No 4 (2021), Pagination: 435-443Abstract
Mobile ad hoc networks (MANETs) is an infrastructure-less network, which is self-organizing, self-configuring and dynamic. The traditional routing protocol is not efficient against the routing challenges. The traditional MANET routing mechanisms involve overhearing, retransmission, and idle listening, which consume high energy. The main obstacles for MANET are end-to-end delay, energy consumption, and packet collision problems. The enhancement of network lifetime and communication performance is still a challenging task. This paper proposes a Ticket-ID zone manager routing protocol (TID-ZMGR) with sleep scheduling for MANETS. The proposed system consists of a zone routing system that is effective in load balancing and energy-efficient. In the proposed approach, nodes in the network are grouped as zones with a zone leader (ZL). The ZL is the node with higher efficiency in terms of energy, link quality, connectivity, and distances. The TID-ZMGR follows a multipath mechanism for balancing the load, and traffic is controlled by distributing the path from source to destination. The implementation of an adaptive sleep duty cycling approach ensures error-free communication around the network. Additionally, the adaptive sleep duty cycling approach increases the overall accuracy by saving the power on border nodes. The efficiency of the proposed work is proved by the comparison work carried out between Ticket-ID Based Routing management system (TID-BRM) Zone-based Routing with Parallel Collision Guided Broadcasting Protocol (ZCG) and Distance aware Zone Routing Protocol (DZRP) with TID-ZMGR. Experimental work evaluation metrics are zonal leader changes, energy consumptions, and network lifetime. Simulation result shows proposed mechanism achieves minimum energy consumption with improved output on throughput and packet delivery ratio.Keywords
MANET, ZL, ZCG, DZRP, TID-ZMGR.Full Text
References
- Ravilla D, Putta CSR (2012) Energy Management in zone routing protocol (ZRP). In: Wyld D, Zizka J, Nagamalai D (eds) Advances in computer science, engineering & applications. Advances in intelligent systems and computing, vol 167. Springer, Berlin, Heidelberg, pp 355–366
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- Nair AL, Perumal Sankar S (2016) Sleep scheduling technique for geographic routing in MANET. Int J Adv Res Electric Electron Instrum Eng 5(2):674–680
- Beijar N (2008) Zone routing protocol (ZRP). Networking Laboratory, Helsinki University of Technology, Espoo
- Aastha Mishra,Shweta Singh,Arun Kumar Tripathi, (2019). Comparison of MANET routing protocols, A Monthly Journal of Computer Science and Information Technology (IJCSMC), Vol. 8, Issue. 2, ISSN 2320–088X, pg. 67–74
- K.Spurthi, T.N.shankar, An Efficient Cluster Computing Mechanism for Wormhole Attack Detection in MANET, International Journal of Advanced Science and Technology 29(7)(2020)
- Hossain, S., Hussain, M. S., Ema, R. R., Dutta, S., Sarkar, S., & Islam, T. (2019). Detecting Blackhole attack by selecting appropriate routes for authentic message passing using SHA-3 and Diffie-Hellman algorithm in AODV and AOMDV routing protocols in MANET. (2019),10th International Conference on Computing, Communication, and Networking Technologies (ICCCNT)
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- Khan, M. F., Aadil, F., Maqsood, M., Bukhari, S. H. R., Hussain, M., & Nam, Y. (2019). Moth fame clustering algorithm for internet of vehicle (MFCA-IoV)
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- Shakya M, Markam K (2016) Comparison of AODV and DSR routing protocols by using group mobility model with varying pause time in vehicular ad-hoc network. International Journal of Hybrid Information Technology Vol.9, No.2 (2016), pp. 177-182 http://dx.doi.org/10.14257/ijhit.2016.9.2.15
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- D. G. Zhang, S. Liu, X. H. Liu, T. Zhang and Y. Y. Cui, “Novel dynamic source routing protocol (DSR) based on genetic algorithm-bacterial foraging optimization (GA-BFO),” International Journal of Communication Systems, vol. 31, no. 18, pp. e3824, 2018.
- Venkatasubramanian, S., Suhasini, A. & Vennila, C. An Efficient Route Optimization Using Ticket-ID Based Routing Management System (T-ID BRM). Wireless Pers Commun (2021). https://doi.org/10.1007/s11277-021-08731-6.
- Detection of Black and Grey Hole Attacks Using Hybrid Cat with PSO-Based Deep Learning Algorithm in MANET
Abstract Views :138 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Chidambaram, Tamil Nadu, India., IN
2 Department of Computer Science and Engineering, Annamalai University, Chidambaram, Tamil Nadu, India, IN
3 Electronics and Communication Department, Saranathan College of Engineering, Trichy, Tamil Nadu,, IN
1 Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Chidambaram, Tamil Nadu, India., IN
2 Department of Computer Science and Engineering, Annamalai University, Chidambaram, Tamil Nadu, India, IN
3 Electronics and Communication Department, Saranathan College of Engineering, Trichy, Tamil Nadu,, IN
Source
International Journal of Computer Networks and Applications, Vol 9, No 6 (2022), Pagination: 724-735Abstract
.The newest example of wireless networks, known as mobile ad hoc networks (MANETs), offers some qualities, including a topology that can change dynamically, a baseless network, a range of transmission, a routing procedure, and reliability. In a black hole attack on a computer network, packets are deleted as opposed to being forwarded through a router. This often happens when a router has been corrupted by several circumstances. A routing attack called a "black hole" has the power to bring down an entire network. One of the most common types of assaults on MANETs is the Grey Hole Attack, in which a hostile node allows routing but prevents data transmission. MANET security is a top priority because they are far more susceptible to assaults than wired infrastructure. This study focused on detecting black and grey-hole attacks in MANET by using deep learning techniques. The forwarding ratio metric is used in the individual attack detection phase to distinguish between the defective and normal nodes. The encounter records are manipulated by malicious nodes in the collusion attack detection phase for escaping the detection process. The attacks are detected by using different deep learning techniques like Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) network. The parameter tuning operation is carried out by using the Hybrid Cat-Particle Swarm Optimization (HCPSO). The simulation results shown in our proposed system detect with better accuracy.Keywords
Black Hole Attack, Convolutional Neural Network, Mobile Ad-Hoc Networks, Long Short-Term Memory, Hybrid Cat-Particle Swarm Optimization, Grey Hole Attacks.Full Text
References
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