Volume-06 , Special Issue-11 , Dec - 2018 Go Back

The exponential growth in wireless environment ensures extended mobility to the end-users. Mobility provides different levels of flexibity in operation but induces certain security risks. The security risks exist mainly in the form of unauthorized or fake access points to which end users can connect. The illegitimate connections could lead to eavesdropping on the end users and initiating security attacks (such as evil twins exploit). In this paper, we propose a method which uses label-hopping technique to detect fake wireless Access Point (AP). Once detected, such fake AP could be identified and removed from the wireless environment. We use Wireless Local Area Network (WLAN) based environment, as an example for applying the proposed technique. The proposed technique is extensible to mobile wireless networks such as 4th=5th generation mobile.

The concept of mobility for end users has intro-duced both security risk and an exponential growth of base stations and Wireless Access Points

[1] N. Sathya Narayanan, Milan Patnaik, V. Kamakoti, ProMAC: A proactive model predictive control based MAC protocol for cognitive radio vehicular networks, Computer Commu-nications, Volume 93, 2016, Pages 27-38,ISSN0140-3664, https://doi.org/10.1016/j.comcom.2016.05.012.
[2] K. Bauer, H. Gonzales and D. McCoy, Mitigating Evil Twin Attacks in 802.11, IEEE International Performance, Com-puting and Communications Conference, Austin, Texas, 2008, pp. 513-516. doi: 10:1109/PCCC.2008.4745081
[3] M. Martellini, A. Stanislav, S Gaycken, and C. Wilson, Information Security of Highly Critical Wireless Networks, Springer International Publishing, 2017, pp. 11-15. doi: 10.1007=978-3-319-52905-9 4
[4] D. Pleskonjic, S. Omerovic, and S. Tomazic, Network Sys-tems Intrusion: Concept, Detection, Decision, and Prevention, IPSI BgD Transactions on Internet Research, vol. 3(1), 2007.
[5] Anik Shah, Animesh Shah, ”A Survey: Wireless Lan Security Protocols”, IJECS, vol. 4, no. 3, pp. 10968-10971, March 2015.
[6] U. Deshpande, T. Henderson, D. Kotz. Channel sampling strategies for monitoring wireless networks., In: Proceedings of the second workshop on wireless network measurements, Boston, April 2006.
[7] S Raman, B Venkat, G Raina, Mitigating Some Security Attacks in MPLS-VPN Model “C”, International Journal on Advances in Networks and Services, vol. 5(3 4),2012.
[8] J.Lawrence Carter, M. N.Wegman, Universal classes of hash functions Elseveir Journal of Computer and System Sciences, vol. 8(2), pp. 143154, 1979.
[9] V Boyko, P MacKenzie, and S Patel, Provably Secure Password-Authenticated Key Exchange Using Diffie-Hellman, Advances in Cryptology — EUROCRYPT 2000, Springer, Ed.B Preneel, pp.156171, 2000.
[10] D Wang, P Wang, Offline Dictionary Attack on Password Authentication Schemes Using Smart Cards., In: Desmedt Y. (eds) Information Security. Lecture Notes in Computer Science, vol 7807. Springer, 2015.
[11] T H Cormen, C E Leiserson, R L Rivest, C Stein, Introduction algorithms, MIT press, 2009.
[12] Ting, M T David, O Hussain, and G LaRoche, Systems and methods for multi-factor authentication, U.S. Patent 9; 118; 656, 2015.
[13] N Karapanos, M Claudio Marforio, S Claudio and C Srdjan, Sound-Proof: Usable Two-Factor Authentication Based on Ambient Sound,In USENIX Security Symposium, pp. 483 498,2015.
[14] Romero, Francisco Javier Dominguez, Kyriakos Exadactylos, and Andrea De Pasquale. ”Cell barring in a cellular communi-cation network.” U.S. Patent 8,718,655, issued May 6, 2014.

S.P. Meenakshi, Jacintha Thomas, K S Balaji, Sathya Narayanan N, Shankar Raman, V Kamakoti, "Detecting Unauthorized Access Points in Wireless Environment", International Journal of Computer Sciences and Engineering, Vol.06, Issue.11, pp.246-250, 2018.

Video data hiding is a very Abstract – Video data hiding is very important research topic. Security of information is major concern of information technology and communication. This paper introduces svd and Least Significant bit substitution technique for hiding data in video file. In this paper data hiding a form of cryptography embeds data into digital media for the purpose of identification, annotation. These algorithms are a basic algorithm of encryption and decryption for data hiding. The framework is tested by all kind of videos such as .mp4, .3gp, .avi etc., and gets successful output for all video data hiding process. The three components Red, Green, Blue of (RGB) space are utilized by this scheme to embed watermark into the cover image. Specifically the combinations of Singular Value Decomposition (SVD) of Blue channel are used to embed the data hiding. The singular values of wavelet subband coefficients of Blue channel are use in different scaling factors to embed the singular values of the data. The SVD increases the security, robustness and imperceptibility of the scheme. The proposed scheme used by security, while hiding the video to provide security for encrypts and decrypt process. The simulation results show that the process of hiding the video by security.

Video Data hiding, Encryption, Decryption, Security Data, SVD

Noise models in digital image processing Ajay Kumar Boyat1 and Brijendra Kumar Joshi2-2, April 2015.
[2] A survey on security issues: digital images Srinivas Koppu1, madhuviswanatham-18-06-2016.
[3] A Survey on Separable Reversible Data Hiding in Encrypted Image Ganesh Gunjal- 7, July 2015.
[4] Secure Reversible Image Data Hiding over Encrypted Domain via Key Modulation J. W. Zhang-2014.
[5] A Survey on Data Hiding Techniques in Encrypted Images- Minu Lalitha Madhavu- 1, January 2016.
[6] Alexandre H. Paqueta, Rabab K. Ward, Ioannis Pitas, Wavelet packets-Based digital watermarking for image Verification and authentication. Signal Processing.2003.
[7] T. Amornraksa, K. Janthawongwilai. Enhanced images watermarking based on amplitude modulation. Journal Image and Vision Computing.2006.
[8] Haohao song_, songyu yu, xiaokang yang, li song, Chen wang. Contourlet-Based
[9] Han-Min Tsai, Long-WenChang. Secure reversible visible mage watermarking with authentication. J Signal Processing: Image Communication.2010.
[10] YounhoLee, Heeyoul Kim, Yongsu Park. A new data hiding scheme for binary image authentication with small image distortion.J Information Sciences.2009

P.S.S. Akilashri, M.Kannan, "Secure Data Hiding in Encrypted Video Using SVD", International Journal of Computer Sciences and Engineering, Vol.06, Issue.11, pp.251-255, 2018.

Sentiment analysis is one of the fastest growing research areas in computer science, which is helpful to analyze people’s opinions, sentiments, evaluations, attitudes and emotions from written language. It is widely studied in data mining, web mining, and text mining. This survey paper presents a comprehensive study on various recently used sentiment analysis techniques. The main target of this survey paper is to give full image of sentimental analysis techniques and the related field with brief details. The cluster of datasets given as a input and the accuracy level is checked by using discourse relations. The limitations and features are also discussed.

Sentiment analysis, Discourse relations, Baseline algorithms, Text mining

[1] Liu. B,"Sentiment analysis and opinion mining", Synthesis Lectures On Human Language Technologies,vol.5,no.1, pp.1-167,2012
[2] Pang B. Lee, L. and Vaithyanathan, S., ,“Sentiment classification using machine learning techniques”, In Proceedings of The Acl-02 Conference On Empirical Methods In Natural Language Processing,vol.10,no., pp.79-86,July 2002
[3] Chaovalit P. and Zhou L.,"Movie review mining", A Comparison Between Supervised And Unsupervised Classification Approaches,vol.,no., pp.,January 2005
[4] Miller G.A,"WordNet a lexical database for english", Communications Of The Acm,vol.38, no.11, pp.39-41,1995 [5] Tripathy A, Agrawal A and Rath S.K,"Classification of Sentimental Reviews Using Machine Learning Techniques", Procedia Computer Science,vol.57,no., pp.821-829,2015
[6] Shahana P.H. and Omman B,"Evaluation of Features on Sentimental Analysis", Procedia Computer Science,vol.46,no., pp.1585-1592,2015
[7]Jeyapriya A. and Selvi K,"Extracting aspects and mining opinions in product reviews using supervised learning algorithm", In Electronics And Communication Systems,vol.,no., pp.548-552,February 2015
[8] Kanakaraj M. and Guddeti R.M.R,"Performance analysis of Ensemble methods on Twitter sentiment analysis using NLP techniques", In Semantic Computing., pp.169-170,February 2015
[9] Mouthami K, Devi K.N. and Bhaskaran V.M,"Sentiment analysis and classification based on textual reviews", In Information Communication And Embedded Systems,pp.271-276,February 2013
[10]Bhadane C., Dalal H. and Doshi H,"Sentiment analysis: Measuring opinions", Procedia Computer Science,vol.45,no., pp.808-814,2015
[11] Gautam G. and Yadav D,"Sentiment analysis of twitter data using machine learning approaches and semantic analysis", In Contemporary Computing,, pp.437-442,August 2014
[12]Zhou X, Tao X., Yong J and Yang Z,"Sentiment analysis on tweets for social events", In Computer Supported Cooperative Work In Design (Cscwd), pp.557-562,June 2013
[13]Go A, Bhayani R. and Huang L,"Twitter sentiment classification using distant supervision", Cs224N Project Report,vol.1,no., pp.12,2009
[14]Khan F.H., Qamar U. and Javed M.Y,"Sentiview: A visual sentiment analysis framework", In Information Society (I-Society),vol.,no., pp.291-296,November 2014
[15]da Silva N.F., Hruschka E.R. and Hruschka E.R,"Tweet sentiment analysis with classifier ensembles", Decision Support Systems,vol.66,no., pp.170-179,2014
[16]Michael W. Berry,"Soft Computing in Data Science", Communications In Computer And Information Science,vol.,no., pp.,2-3 Sep 2015
[17]Patel S.N. and Choksi M.J.B,"A Survey of Sentiment Classification Techniques", Journal For Research,vol.1,no., pp.1,2015
[18]Heerschop B., Goossen F., Hogenboom A., Frasincar F., Kaymak U. and de Jong F,"Polarity analysis of texts using discourse structure", In Proceedings Of Cimk,vol.,no., pp.1061-1070,2011
[19]Hernault H., Bollegala D. and Ishizuka M,"A semi-supervised approach to improve classification of infrequent discourse relations using feature vector extension", In Proceedings Of The Emnlp,vol.,no., pp.399-409,2010
[20]Joty S Carenini G. and Ng R.T,"A novel discriminative framework for sentence-level discourse analysis", In Proceedings Of Emnlp,vol.,no., pp.904-915,2012
[21]Mann W.C. and Thompson S.A,"Rhetorial structure theory", Towards A Functional Theory Of Text Organization,vol.8,no.3, pp.243-281,1988
[22]Narayanan R., Liu, B. and Choudhary A,"Sentiment analysis of conditional sentences", In Proceedings Of Emnlp,vol.,no., pp.180-189,2009
[23]Pang B. and Lee L,"Opinion mining and sentiment analysis", Information Retrieval,vol.2,no.1, pp.1-135,2008 [24]Polanyi L. and Zaenen A,"Contextual valence shifters", Computing Attitude And Affect In.,vol.,no., pp.,2006
[25]Qiu, L. Zhang, W. Hu C. and Zhao K,""a self-supervised model for sentiment classification"", In Proceedings Of Cikm,vol.,no., pp.929-936,2009"
[26] Somasundaran S., Namata G. , Wiebe J. and Getoor L,"Supervised and unsupervised methods in employing discourse relations for improving opinion polarity classification", In Proceedings Of The Enmlp,vol.,no.,pp.170-179,2009

K.Lino FathimaChinnaRani, M. Kasthuri, N.Solomon PraveenKumar, "A Survey on Sentimental Analysis Techniques", International Journal of Computer Sciences and Engineering, Vol.06, Issue.11, pp.256-263, 2018.

Circulant networks is one of most popular interconnection networks since it has a simple structure and is easy to implement. Graph embedding is an important parameter to evaluate the quality of an interconnection network and wirelength is an important measure of an embedding. In this paper, we embed circulant network into cycle-of-butterfly with minimum wirelength.

Embedding; Congestion; Wirelength; Circulant networks; cycle-of-butterfly

[1] X.Yang, Q.Dong, Y.Y.Tang, Embedding meshes/tori in faulty crossed cubes, Inf Process Lett, Vol. 110, no. 14-15, 559 - 564, 2010.
[2] T. Dvorak, Dense sets and embedding binary trees into hypercubes, Discrete Applied Math-ematics, Vol. 155, no. 4, 506 - 514, 2007.
[3] G.K. Wong, D.A. Coppersmith, A combinatorial problem related to multimodule memory organization, J. Assoc. Comput. Machin., Vol. 21, no. 3, 392 - 401, 1994.
[4] E.T. Boesch, J. Wang, Reliable circulant networks with minimum transmission delay, IEEE Trans. Parallel Distrib. Syst, Vol. 32, no. 12, 1286 - 1291, 1985.
[5] J.C. Bermond, F. Comellas, D.F. Hsu, Distributed loop computer networks, A survey Journal of Parallel and Distributed Computing, Vol. 24, no. 1, 2 - 10, 1995.
[6] R. Beivide, E. Herrada, J.L. Balc azar, A. Arruabarrena, Optimal Distance Networks of Low Degree for Parallel Computers, IEEE Transactions on Computers, Vol. 40, no. 10, 1109 - 1124, 1991.
[7] R.S. Wilkov, Analysis and Design of Reliable Computer Networks, IEEE Trans. Communi-cations, Vol. 20, no. 3, 660 - 678, 1972.
[8] M. Karlin, New binary coding results by circulants, IEEE Transac- tions on Information Theory, Vol. 15, no. 1, 81 - 92, 1969.
[9] J.M. Xu, Topological Structure and Analysis of Interconnection Networks, Kluwer Academic Publishers, 2001.
[10] Y.L. Lai, K. Williams, A survey of solved problems and applications on bandwidth, edgesum, and profile of graphs, J. Graph Theory, Vol. 31, 75 - 94, 1999.
[11] J. Fan, X. Jia, Embedding meshes into crossed cubes, Information Sciences, Vol. 177, no. 15, 3151 - 3160, 2007.
[12] W.K. Chen, M.F.M. Stallmann, On embedding binary trees into hypercubes, Journal on Parallel and Distributed Computing, Vol. 24, 132 - 138, 1995.
[13] S.L. Bezrukov, Embedding complete trees into the hypercube, Discrete Applied Mathematics, Vol. 110, no. 2-3, 101 - 119, 2001.
[14] J.-F. Fang, K.-C. Lai, Embedding the incomplete hypercube in books, Information Processing Letters, Vol. 96, 1 - 6, 2005.
[15] P.-L. Lai, C.-H. Tsai, Embedding of tori and grids into twisted cubes, Theoretical Computer Science, Vol. 411, no. 40-42, 3763 - 3773, 2010.
[16] Y. Han, J. Fan, S. Zhang, J. Yang, P. Qian, Embedding meshes into locally twisted cubes, Information Sciences, Vol. 180, no. 19, 3794 - 3805, 2010.
[17] R. Caha, V. Koubek, Optimal embeddings of generalized ladders into hypercubes, Discrete Mathematics, Vol. 233, 65 - 83, 2001.

[18] M. Rottger, U.P. Schroeder, Efficient embeddings of grids into grids, Discrete Applied Math-ematics, Vol. 108, no. 1-2, 143 - 173, 2001.
[19] J. Opatrny, D. Sotteau, Embeddings of complete binary trees into grids and extended grids with total vertex-congestion 1, Discrete Applied Mathematics, Vol. 98, 237 - 254, 2000.
[20] J.D. Chavez, R. Trapp, The cyclic cutwidth of trees, Discrete Applied Mathematics, Vol. 87, 25 - 32, 1998.
[21] C.-J. Guu, The Circular Wirelength Problem for Hypercubes, Ph.D. dissertation, University of California, Riverside, 1997.
[22] M.-C. Yang, Path embedding in star graphs, Applied Mathematics and Computation, Vol. 207, no. 2, 283 - 291, 2009.
[23] A. Vodopivec, On embeddings of snarks in the torus, Discrete Mathematics, Vol. 308, no. 10, 1847 - 1849, 2008.
[24] I.Rajasingh, J.Quadras, P.Manuel, A.William, Embedding of cycles and wheels into arbitrary trees, Networks, Vol. 44, 173 - 178, 2004.
[25] P.Manuel, I.Rajasingh, B.Rajan, H. Mercy, Exact wirelength of hypercube on a grid, Discrete Appl Math, Vol. 157, no. 7, 1486 - 1495, 2009.
[26] I. Rajasingh, B. Rajan, R.S. Rajan, On embedding of m-sequencial k-ary trees into hyper-cubes, Applied Mathematics, Vol. 1, no. 6, 499 - 503, 2010.
[27] C.-H. Tsai, Embedding of meshes in Mobius cubes, Theoretical Computer Science, Vol. 401, no. 1-3, 181 - 190, 2008.
[28] A.K. Gupta, D. Nelson, H. Wang, Efficient embeddings of ternary trees into hypercubes, Journal of Parallel and Distributed Computing, Vol. 63, no. 6, 619 - 629, 2003.
[29] P. Manuel, Minimum average congestion of enhanced and augmented hypercube into complete binary tree, Discrete Applied Mathematics, Vol. 159, no. 5, 360 - 366, 2010.
[30] I. Rajasingh, P. Manuel, M. Arockiaraj, B. Rajan, Embeddings of circulant networks, Journal of Combinatorial Optimization, Vol. 26(1), 135 - 151, 2013.
[31] P. Manuel, M. Arockiaraj, I. Rajasingh, B. Rajan, Embedding hypercubes into cylinders, snakes and caterpillars for minimizing wirelength, Discrete Applied Mathematics, Vol. 159, no. 17, 2109 - 2116, 2011.
[32] I. Rajasingh, B. Rajan, R.S. Rajan, Embedding of hypercubes into necklace, windmill and snake graphs, Information Processing Letters, Vol. 112, 509 - 515, 2012.
[33] I. Rajasingh, B. Rajan, R.S. Rajan, Embedding of special classes of circulant networks, hypercubes and generalized Petersen graphs, International Journal of ComputerMathematics, Vol. 89, no. 15, 1970 - 1978, 2012.
[34] S.L. Bezrukov, J.D. Chavez, L.H. Harper, M. R¨ottger, U.P. Schroeder, Embedding of hyper-cubes into grids, Mortar Fine Control System, 693 - 701, 1998.


[35] Jywe-Fei Fang, The bipancycle-connectivity of the hypercube, Information Sciences, Vol. 178, 4679 - 4687, 2008.
[36] S.L. Bezrukov, J.D. Chavez, L.H. Harper, M. R¨ottger, U.P. Schroeder, The congestion of n-cube layout on a rectangular grid, Discrete Mathematics,Vol. 213, 13 - 19, 2000.
[37] S.L. Bezrukov, S.K. Das, R. Els¨asser, An edge-isoperimetric problem for powers of the Pe-tersen graph, Annals of Combinatorics, Vol. 4, 153 - 169, 2000.
[38] L.H. Harper, Global Methods for Combinatorial Isoperimetric Problems, Cambridge Univer-sity Press, 2004.
[39] G.K. Wong, D.A. Coppersmith, A combinatorial problem related to multimodule memory organization,J. Assoc. Comput. Machin, Vol. 21, no. 3, 392 - 401, 1974.
[40] M.R. Garey, D.S. Johnson, Computers and Intractability, A Guide to the Theory of NP-Completeness, Freeman, San Francisco 1979.

L. Packiaraj, K. Manoj, "Embedding of Circulant Networks into Cycle-of-butterfly", International Journal of Computer Sciences and Engineering, Vol.06, Issue.11, pp.264-274, 2018.