iosr-JCE   Volume-12 ~ Issue-2

Abstract: The present aim is the study of ferns having antimicrobial activity and commonly found around the area of district Darjeeling of West Bengal, India. Common ferns from several areas of Darjeeling district are collected and tested against Gram +ve and Gram –ve bacteria for their antimicrobial activity. Collected plant materials are dried and the soluble extracts are made using different solvents like distilled water, methanol, ethanol and acetone Antimicrobial activities are measured using agar cup diffusion method. Greater the area of inhibition zone indicates the presence of good potentiality of antimicrobial activity. A large number of common ferns are collected and among them some species are found having antimicrobial activity. Five species show antimicrobial activity against both gram +ve and gram -ve bacteria.

Key Words: antimicrobial, extract, gram positive and gram negative, inhibition zone, solvent .

[1] R.D Banerjee , S.P Sen ,Antibiotic activity of Pteridophytes. Ecol. Bot1980., 34(3): 284-298. [2] S.P Sen , P Nandi :Antibiotics from the pteridophytes. Sci. Cult 1951., 16: 328-329. [3] J.C Maruzzella :Antimicrobial substances from ferns. Nature2005,1961.,191: 518-519. [4] A.W Bauer , M.M Kirby , J.C Sherris , M Truck Antibiotic susceptibility testing by a standardized single disk method. Am J Clin Pathol 1966; 45: 493-6. [5] O.H Lowry,., N.J. Rosebrough, A.L. Farr, and R.J. Randall (1951) Protein Measurement with the Folin Phenol Reagent. J. Biol. Chem. 193:265-275
[6] V.S Manickam ,A Benniamin ,V Irudayaraj Antibacterial activity of leaf glands of Christells parasitica (L.) Lev, Indian Fern J2002., 22: 87-88
[7] L.E Alcaraz , S.E Blanco ,O.N Puig , F Tomas ,F.H Ferretti : Antibacterial activity of flavonoids against methicillin-resistant Staphylococcus aureus strains. J Theor Biol 2000., 205:231-240.
[8] T.P.T Cushnie ,A.J Lamb : Antimicrobial activity of flavonoids. Int J Antimicrob Agents 2005., 26:343-356.
[9] U.K Yusuf : Flavonoid Glycosides in the Fern Blechnum orientale Linn. AmF J 1994., 84:69-70. [10] D Natarajan ,G Perumal ,C Mohanasundari ,K Moorthy , Studies of antimicrobial activities of certain medicinal ferns against selected dermatophytes, Indian Fern J2005., 22: 191-195.

Abstract: Visual cryptography scheme is a cryptographic technique which allows visual information to be encrypted into several shares in such a way that the decryption can be performed by the human visual system, without the aid of computers. Random grid is a methodology to construct visual secret sharing (vss) scheme without pixel expansion in which an RG scheme takes an input image and transforms it into multiple cipher-grids that provide no information on the original image and the resulting decrypted image retains the size of the original image. Intent of this paper is on comparative study of visual cryptography and Random grid cryptography on the basis of analysis and correctness of simple VC schemes and RG schemes, improving contrast of the reconstructed image using various algorithms and multiple-image encryption using rotating angles.

Keywords - ideal contrast, random grid scheme, ring shadow technology, rotating random grids, visual cryptography scheme.

[1]. Moni Naor and Adi Shamir, "Visual Cryptography", advances in cryptology– Eurocrypt, pp 1-12,1995.
[2]. C.C. Wu, L.H. Chen, "A Study On Visual Cryptography", Master Thesis, Institute of Computer and Information Science, National Chiao Tung University, Taiwan, R.O.C., 1998.
[3]. H.-C. Hsu, T.-S. Chen, Y.-H. Lin, "The Ring Shadow Image Technology Of Visual Cryptography By Applying Diverse Rotating Angles To Hide The Secret Sharing", in Proceedings of the 2004 IEEE International Conference on Networking, Sensing & Control, Taipei, Taiwan, pp. 996–1001, March 2004.
[4]. O. Kafri and E. Keren. Encryption of pictures and shapes by random grids. Optics Letters, 12:377-379, 1987.
[5]. Tzung-Her Chen and Kai-Hsiang Tsao, "Visual secret sharing by random grids revisited". Pattern Recognition, 42(9):2203 - 2217, 2009. ISSN 0031-3203.
[6]. C.Blundo, A.De Santis and D. R. Stinson, "On the contrast in visual cryptography schemes", Journal Cryptology, vol.12, 1999, pp. 261- 289.
[7]. J.L.Massey, "Some applications of coding theory in cryptography", in Cryptography and Coding IV, Oxford University Press, 1995, pp.33-47.
[8]. T. H. Chen, and C. S. Wu, "Efficient Multi-secret Image Sharing based on Boolean Operations", Signal Processing, Vol. 91, No. 1, (2011), pp. 90-97.
[9]. Tzung-Her Chen, Kai-Hsiang Tsao, Kuo-Chen Wei, ""Multiple-image encryption by rotating random grids,‟‟ in: Proceedings of the 8th International Conference on Intelligent System Design and Applica- tions (ISDA 2008), Kaohsiung, Taiwan, Nov. 26–28, 2008.
[10]. R.Z. Wang, Y.K. Lee, S.Y. Huang, T.L. Chia, ""Multilevel visual secret sharing,‟‟ in: Proceedings of the Second International Conference on Innovative Computing, Information and Control, Kumamoto, Japan, 2007.

Abstract: Cloud computing is generally recognized as a technology which will have a significant impact on Information Technology in the future. The cloud computing data security has certain drawbacks in its implementation making it insecure. To avoid this problem in this research we propose enhanced security architecture for cloud computing using encryption and decryption system with double key cryptography based on Artificial Neural Network. The objective of the proposed scheme is to protect the information even if the hackers break the cipher text they can't convert cipher text to original text. In our proposed algorithms we have (training algorithm) adopted high data security authorized person can retrieve the data, including key generation, encryption and decryption that are provided in cloud computing system.

Keywords: Artificial Neural Network (ANN), cloud data storage Cloud data retrieval, decryption, encryption.

[1] Abhishek Mohta, Ravi Kant Sahu and Lalit Kumar Aswasthi, "Robust Data Security for Cloud while using Third party Auditor", IGARCSSE, Vol 2, Issue 2 , February 2012.

[2] Annamaneni Samatha,Nimmala Jeevan Reddy and Pradeep Kumar "Data Storage Collateral In Cloud Computing",IJERA(International Journal of Engineering Research and Applications),Vol 2,Issue 5, pp1050-1055 Sep-Oct 2012.

[4] Arti Sharmaand Pawanesh Abrol, "Cloud Computing Environment Problems Implementation",International Journal of Computers and Distributed System,Vol 1,Issues 3,pp 64-68,October 2012.

[5] Chittarajan Hota ,Sunil Sanka,Muttukrishnan Rajarajan and Srijith K Nair, "Capability based cryptography data access in cloud computing", International Journal Advance Networking and Applications, Vol 3, Issues 3, pp 1152 – 1161,November 2011.

[6] Christian Henrich,"Brief Announcement:Towards secure cloud computing" Springer,LNCS 5873,pp 785-786,2009.

[7] Dinesh C Verma,A.K Mohapatra and Kaleem Usmani, "Light Weight Encryption Technique for Group Communication in Cloud Computing Environment",IJCA,Vol 49,No 8,pp 35-41,July 2012.

[8] Eva Volna , Martin Kotyrba,Vaclav Kocian and Michal Janosek,"Cryptography Based on neural Network", Proc 26th European on modelling and simulation ,ISBN:978-0-9564944-4-3, 2012.

[9] Khaled Alallayah,Mahamed Amin,Waiel AhdElwahed and Alaa Alhamami, "Applying Neural Network for simplified Data Encryption Standard (SDES) Cipher System cryptanalysis", The International Arab Journal of Information Technology , Vol 9, No 2, PP 163-169, March 2012.

[10] L.M Kaufman, "Data Security in the world of Cloud computing, Security & Privacy", IEEE ,vol 7, pp 61-64, 2009.

Abstract: An attempt is made in this paper to develop an Enhanced Support Vector Regression (ESVR ) model with more un-interpretable kernel functions in the domain of forecasting the weather conditions. Every predicate model takes input data set parameters, processing with in specified levels of classification into variable sets and countered with a variable set reduction to reach the decision of prediction in a more confirm levels. This paper also provides a critical modeling design using the non linear regression namely support vector machines which is very non interpretable neural network designed as a two stage activity in prediction with more than three kernel functions for improving the performance of the SVMs experts in predicting the future weather happenings. Recording the input data set parameters of weather like temperature, water vapor, atmospheric pressure, dew point, wind speed, wind direction, rainfall, etc. compared with a MLP (Multi Layer preceptron) classification, SVM got much more esteemed performance in forecasting any one parameter with respect to others in a two stage procedure initial with self organizing maps and with best practice of more kernel functions investigation in weather forecasting.

Key Words: SVM, SOM, Kernel Functions, Classification and prediction, MLP.

[1]. Tk.Rama Krishna Rao, R,Usha Rani Content Based Image Retrieval Through Feed Forward Neural Networks 2012 IEEE 8th International Colloquium on Signal Processing and its Applications, Malek, Malaysia 23-25 March.
[2]. Classification and Prediction of Future Weather by using Back Propagation Algorithm-An Approach. Sanjay D. Sawaitul1, Prof. K. P. Wagh2, Dr. P. N. Chatur3, www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 1, January 2012)
[3]. Amit Jain, B. Satish, Clustering Based Short TermLoad Forecasting using Support Vector Machines, 2009 IEEE Bucharest Power Tech Conference, June 28th -July 2nd, Bucharest, Romania.
[4]. Y.Radhika and M.Shashi, Atmospheric Temperature Prediction using Support Vector Machines, International Journal of Computer Theory and Engineering, Vol. 1, No.1, April 2009, 1793-8201.
[5]. Amit Jain, B. Satish, Integrated Approach for ShortTerm Load Forecasting using SVM and ANN, TENCON 2008. IEEE Region 10 Conference 19-21 Nov. 2008 Page(s): 1 - 6 Digital Object Identifier
[6]. Guhathakurtha, P.,―Long-Range monsoon rainfall prediction of 2005 for the districts and sub-division kerala with artificial neural network.‖Current Science,Vol.90, No.6,25. 2006
[7]. Lijuan Cao. Support vector machines experts for time series forecasting. www.elsevier.com/locate/neucom, Neurocomputing 51 (2003) 321 – 339.
[8]. Tung A.K.H., ―Efficient mining of intertransaction associationrules‖, IEEE Trans. on Knowledge and Data Engineering,vol.15(1), 43-56p, Jan./ Feb. 2003.
[9]. Denis Riordan, and Bjarne K Hansen, ―A fuzzy case-based system for weather prediction.‖ Engineering Intelligent Systems, Vol .10, No.3. 2002.
[10]. Ronan Collobert and Samy Benegio, SVM Torch: Support Vector Machines for Large-Scale Regression Problems, Journal of Machine Learning Research, 1, pp.143- 160. 2001,3] Haykin, S., ‖Neural Networks- A Comprehensive Foundation.‖Prentice Hall. 1999.

Abstract: Many high speed protocols of transport layer have been comes into existence and proposed in the literature to improve the performance of Traditional TCP on high bandwidth delay links. All high speed protocols are distinguished on the basis of their incremented and decremented formulas of their respective congestion control algorithm. Many of these high speed protocols consider every packet lost as denotion of congestion in the network and cut their congestion window size. Such an approach will usually result in under utilization of available bandwidth in case of noisy channel conditions. For this reason we take a CUBIC protocol as a test case and compare its performance in noisy channel conditions and normal network conditions. The congestion window and Link utilization of the CUBIC protocol was suddenly decremented, when we incorporate a random packet drops. When the probability of packet lost incremented then both congestion window and link utilization decreases. Thus we need an intelligent technique that distinguish whether a certain packet lost is due to the congestion or any noisy conditions to recover from unnecessary cutting in the window. We have proposed a k-NN based module differentiates whether the packet drop is congestion or any other noisy error. After incorporating this technique in CUBIC protocol, we found better performance improvement.

Keywords: Congestion, Congestion window, High-speed Networks, k-NN, Link utilization and TCP.

[1]. W. R. Stevens, TCP/IP Illustrated, Volume 1, Addison-Wesley, Reading, MA, November 1994.

[2]. Tomoya Hatano, Hiroshi Shigeno and Kenichi Okada, "TCP friendly congestion control for high-speed network", IEEE, 2007.

[3]. M. Allman and V. Paxson, "TCP Congestion Control", Internet Engineering Task Force, RFC 2581, April 1999.

[4]. Y.-T. Li, "Evaluation of tcp congestion control algorithms on the windows vista platform," Tech. Report SLAC-TN-06-005, Stanford University, Tech. Rep., June 2006.

[5]. L. Xu, K. Harfoush, and I. Rhee, "Binary increase congestion control for fast long distance networks," in INFOCOM, 2004.

[6]. I. Rhee, L. Xu. CUBIC: A New TCP-Friendly High-Speed TCP Variant. In Proc. PFLDnet, 2005.

[7]. Tomoya Hatano, Hiroshi Shigeno, Kenichi Okada, "TCP-friendly Congestion Control for High Speed Network", International Symposium on Applications and the Internet- SAINT'07, pp.10, 2007.

[8]. Habibullah Jamal, Kiran Sultan" Performance Analysis of TCP Congestion Control Algorithms". INTERNATIONAL JOURNAL OF COM- PUTERS AND COMMUNICATIONS, Issue 1, Volume 2, 2008.

[9]. K. Tan, J. Song, Q. Zhang, and M. Sridharan, "A compound tcp approach for high-speed and long distance networks," in INFOCOM, 2006.

[10]. T. Kelly, "Scalable TCP: Improving Performance in High-Speed Wide Area Networks," ACM SIGCOMM Computer Communication Review, Volume 33, Issue 2, pp. 83-91, April 2003.

Abstract: Automated video surveillance systems plays vital role in the business areas , military system and etc . Many research areas in video surveillance system is mainly focuses on algorithms to evaluate background subtraction system and alert to the system, to repeatedly detect major actions For example, our proposed technique stores, for each pixel, a set of values taken in the past at the same location or in the neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the background model. This approach differs from those based upon the classical belief that the oldest values should be replaced first. In background comparison if the difference in the values reaches the threshold value then user can get alert message. So whenever user getting SMS from server system and the background image is updated whenever the system is detecting a motion.

Key words : Video surveillance system, Fuzzy Color Histograms, GSM system.

[1]. CUCCHIARA, R.: "Multimedia Surveillance systems", Proc. ACM Workshop on Video Surveillance and Sensor Networks, pp. 3–10, 2005.
[2]. ELGAMMAL, A. – HARWOOD, D. – DAVIS, L. A.: "Non-Parametric Model for Background Subtraction", ICCV'99, 1999
[3]. HORPRASERT, T. – HARWOOD, D. – DAVIS, L. A.: "A Statistical Approach for Real-Time Robust Background Subtraction and Shadow Detection", ICCV'99 Frame Rate Workshop, 1999.
[4]. ARAKI, A. – MATSUOKA, T. – YOKOYA, N. – TAKEMURA, H.: "Real-Time Tracking of Multiple Moving Object Contours in a Moving Camera Image Sequence", IEICE Trans. Inf. &Syst., vol. E83-D, no. 7, pp. 1583–1591, July 2001.
[5]. HARITAOGLU, H.: "Hartwood and Devis, W4: Real Time Surveillance of People and their Activities", IEEE Trans. Pattern Anal. Machine Intell., vol. 22, no. 8, pp. 809–830, Aug. 2000.

Abstract: In this project, a graphical password system with a supportive sound signature to increase the remembrance of the password is discussed. In proposed work a click-based graphical password scheme called Cued Click Points (CCP) is presented. In this system a password consists of sequence of some images in which user can select one click-point per image. In addition user is asked to select a sound signature corresponding to each click point this sound signature will be used to help the user in recalling the click point on an image. System showed very good Performance in terms of speed, accuracy, and ease of use. Users preferred CCP to Pass Points, saying that selecting and remembering only one point per image was easier and sound signature helps considerably in recalling the click points. Keywords - Security, Graphical password, Persuasive Cued Click Points.

[1] Sonia Chiasson, Persuasive Cued Click-Points: Design, Implementation, and Evaluation of a Knowledge-Based Authentication Mechanism VOL. 9, NO. 2, MARCH/APRIL 2012

Books: [2] A. Salehi-Abari, J. Thorpe, and P. van Oorschot, "on purely automated attacks and click-based graphical passwords" (Proc.Ann. Computer Security Applications Conf. (ACSAC), 2008).

Chapters in Books: [3] Image Pointers: A. Baddeley and R. Turner, "Spatstat: An R Package for Analyzing Spatial Point Patterns," (J. Statistical Software vol. 12, no. 6, pp. 142, 2005).

[4] Graphical Password Security :" Exploring Usability Effects of Increasing Security in Click-Based Graphical Passwords," (E. Stobert, A. Forget, S. Chiasson, P. van Oorschot, and R. Biddle"Proc. Ann. Computer Security Applications Conf. (ACSAC), 2010). Theses: [5] Implementation of Knowledge based Authentication System Using Persuasive Cued Click Points, JNTU Hyderabad, India. Proceedings Papers:

[6] S. Chiasson, R. Biddle, and P. van Oorschot, "A Second Look at the Usability of Click-Based Graphical Passwords," Proc. ACM Symp.Usable Privacy and Security (SOUPS), July 2007.

Abstract: The advancements in the field of networking, network infrastructures and the growing size for processing, storage/data and communication, the demand for Virtualization and Data Center flexible resource management has become significantly important. Virtualization is the single most effective way to reduce IT expenses while boosting efficiency and agility. And with time, the advancements in the field of Virtualization, increasing demands of datacenters and increasing network infrastructure development and maintenance cost lead to the development of Virtual Machines and their migrations across datacenters at large scale now. Though Virtual Machines in datacenter decouples physical machines with Virtual ones for their processing but they are still coupled with hosts for their virtual resources sharing and thereby exerting load on servers further. This paper focuses on balancing the load of the servers with the help of efficient VM migrations and proposes an algorithm that adapts to the dynamic business needs in a better way for datacenter access and request processing.

Keywords – Virtualization, Virtual Machine, Migration, Hypervisor, Load Balancing

[1] Kento Sato, Hitoshi Sato, Satoshi Matsuoka, A Model-Based Algorithm for Optimizing I/O Intensive Applications in Clouds using VM-Based Migration, Proc. ISCCG, IEEE, 2009.
[2] Sumit Kumar Bose, Srikanth Sundarrajan, Optimizing Migration of Virtual Machines across Data-Centers, Proc. ICPPW, IEEE 2009.
[3] Ryousei Takano, Hidemoto Nakada, Takahiro Hirofuchi, Yoshio Tanaka, Tomohiro Kudoh, Cooperative VM Migration for a Virtualized HPC Cluster with VMM-Bypass I/O devices, IEEE, 2012
[4] Vivek Shrivastava, Petros Zerfos, Kang-won Lee et. al., Application-aware Virtual Machine Migration in Data Centers, IEEE Infocom 2011
[5] VMware vSphere Storage Distributed Resource Scheduler, VMware White Paper, 2011 http://www.vmware.com/products/datacenter-virtualization/vsphere/vsphere-storage-drs/features.html
[6] Vijay Mann, Anil Kumar V., Aakash I., Parantapa B., VMPatrol: Dynamic and Automated QoS for Virtual Machine Migrations, IFIP, CNSM, 2012
[7] Weining Liu, Tao Fan, Live Migration of Virtual Machine Based on Recovery System and CPU scheduling, IEEE, 2011
[8] Stefan Groesbrink, Basics of virtual machine migration on heterogeneous architectures for self-optimizing mechatronic systems, Springer, Oct. 2012
[9] Zhenzhong Zhang, Limin Xiao, Mingfa Zhu, Li Ruan, Mvmotion: a metadata based virtual machine migration in cloud, Springer, Jan. 2013
[10] Xiujie Feng, Jianxiong Tang, Xuan Luo, Yaohui Jin, A performance study of live VM migration technologies: VMotion vs XenMotion, IEEE, 2011

Abstract: Mobile Ad-hoc Networks (MANETs) are special kind of wireless networks with no centralized control. They are ideal candidate for several real world applications where network need to be established on the fly e.g. disaster hit areas, hospitals, military surveillance etc. Researchers have been actively working in this area for a decade or so to make this concept a reality. MANETs differ from conventional fixed networks and therefore pose several challenges to the researchers working in the area. Among many others, access to shared medium is the major problem in MANETs. In such networks MAC layer protocol plays an important role in efficient utilization of shared media in distributed fashion. At the MAC layer we have three contradicting requirements, Maximize channel utilization, Minimize Control overhead and Fairness. Multi-Channel MAC protocols are considered is the most suitable solution to achieve the desired objectives but channel assignment and reservation in a distributed fashion is still a big challenge. In this paper, we have proposed a Multi-Channel scheme to address the problem of channel assignment the proposed scheme is Nodeid based. The proposed Scheme has been compared with conventional single channel scheme using ns-2 simulation and results shows that the proposed technique gives better performance.

Keywords- BEB algorithm, Clear to send, Control channels, Dedicated Channels, MAC, Overhead, and request to send.

[1] Blerta Bishaj, MAC protocols, contention-based with reservation and scheduling, Helsinki University of Technology 2008.

[2] C.Siva Ram Murthy and B.S Manjo, Ad hoc Wireless Network Architecture and protocols, 2nd Edition, Published by Dorling Kindersley (India).

[3] V. Bharghavan, A. Demers, S. Shenker, and L. Zhang,"MACAW: A media access protocol for wireless LAN's", In SIGCOMM '94, pages 212-225. ACM, 1994.

[4] N.Abramson,"TheALOHA system-another alternative for computer communication," Proc.of AFIPS FJCC, pp-281-285, 1970.

[5] Mariam Kaynia, Geir E.ien, Nihar Jindal, David Gesbert," Comparative Performance Evaluation of MAC Protocols in Ad Hoc Networks with Bandwidth Partitioning", Dept. of Electrical and Computer Engineering, University of Minnesota, USA, 2009.

[6] WenHwa Liao and WenChin Chung," An Efficient Multi-Channel MAC Protocol for Mobile Ad Hoc Networks", Department of Information Management Tatung University, Taiwan, 2009 International Conference on Communications and Mobile Computing.

[7] ChihMin Chao1, HsienChen Tsai, and Kuan-Ju Huang," A New Channel Hopping MAC Protocol for Mobile Ad Hoc Networks", Department of Computer Science and Engineering National Taiwan Ocean University, Taiwan, IEEE 2009.

[8] Zygmunt J. Haas and Jing Deng,"Dual Busy Tone Multiple Access (DBTMA)-a Multiple Access Control Scheme for Ad Hoc Networks" IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 6, JUNE 2002.

[9] C. L. Fullmer and J. Garcia-Luna-Aceves,"FAMA-PJ: A channel access protocol for wireless LANs. In Mobile computing and Networking", Berkley, CA (USA), pages 76-85. ACM, November 1995.

[10] Shengming Jiang, Jianqiang Rao, Dajiang He and Xinhua Ling,"A Simple Distributed PRMA for MANETs, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 51, NO. 2 MARCH 2002.

Abstract: In this paper a semi-blind algorithm is been developed using DWT-DCT and SVD technique which is robust against several attacks like cropping, noise, rotation, filtering, translation, etc. Trigonometric function is used to closely relate the singular values of the original image and the watermarked image. In this algorithm, firstly DWT is applied on the host image which results in four frequency bands LL, LH, HL and HH. As it is found that middle frequency band is less prone to attacks so the singular values of the DCT Transformed coefficients of the LH band of the image is been modified using the singular values of the DCT transformed coefficients of the watermark and the scaling factor with the help of inverse-trigonometric function. And then this modified singular values are used to reconstruct the watermarked Host Image. Now to validate the content authentication, the extraction technique is applied on the watermarked image. It consists of applying DWT on the watermarked image to get all the four frequency bands and then by using the singular values of the DCT coefficients of the middle frequency band and the scaling factor using trigonometric function, the singular values of the watermark are extracted to reconstruct the watermark using inverse SVD.

Keywords- DCT, DWT, Robust, Semi Blind Watermarking

[1] Emir Ganic and Ahmet M. Eskicioglu,"Robust DWT-SVD Domain Image Watermarking: Embedding Data in all frequencies",MM&SEC‟04,September 20-21,2004,Magdeburg,Germany,unpublished
[2] Ms. Kapre Bhagyashri S and Mrs. Joshi M.Y.,"Robust Image Watermarking based on Singular Value Decomposition abd Discrete Wavelet Transform",978-1-4-4244-5540-9/10/$26.00©2010 IEEE,pp.337-341 ,unpublished.
[3] Nidhi H. Divecha and N.N.Jani,"Image Watermarkin Algorithm using DCT-DWT-SVD",NCIPET-2012,Proceedings published by International Journal Of Computer Applications® (IJCA),pp.13-16 .
[4] Satyanaryana Murty,M.Uday Bhaskar,P.Rajesh Kumar,"A Semi-Blind Reference Watermarking Scheme Usind DWT-DCT-SVD For Copyright Protection",International Journal Of Computer Science and Information Technology(IJCSIT),Vol 4,No 2,April 2012,pp. 69-82.
[5] Chaw-Seng _Woo_ Thesis,"Digital Image Watermarking Methods For Copyright Protection and Authentication",Faculty Of Information Technology,Queensland University Of Technology,March 2007.
[6] Pooya Monshizadeh Naini,"In-Tech Digital_Watermarking_Using Matlab",University of Tehran,Iran(www.intechopen.com)
[7] M.Thaler, H.Hochreutener,"Image Processing Basics Using Matlab",February 2008,© ZHAW.

Abstract: :Cyber security is the activity of protecting information and information systems (networks, computers, data bases, data centres and applications) with appropriate procedural and technological security measures. Firewalls, antivirus software, and other technological solutions for safeguarding personal data and computer networks are essential but not sufficient to ensure security. As our nation rapidly building its Cyber-Infrastructure, it is equally important that we educate our population to work properly with this infrastructure. Cyber-Ethics, Cyber-Safety, and Cyber-Security issues need to be integrated in the educational process beginning at an early age. Security counter measures help ensure the confidentiality, availability, and integrity of information systems by preventing or mitigating asset losses from Cyber security attacks. Recently cyber security has emerged as an established discipline for computer systems andinfrastructures with a focus on protection of valuable information stored on those systems fromadversaries who want to obtain, corrupt, damage, destroy or prohibit access to it. An Intrusion Detection System (IDS) is a program that analyses what happens or has happened during an execution and tries to find indications that the computer has been misused. A wide range of metaphors was considered, including those relating to: military and other types of conflict, biological, health care, markets, three-dimensional space, and physical asset protection. These in turn led to consideration of a variety of possible approaches for improving cyber security in the future. These approaches were labelled "Heterogeneity" ,"Motivating Secure Behaviour" and "Cyber Wellness" .

[1] Ravi Sharma, Study of Latest Emerging Trends on Cyber Security and its challenges to Society, International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June-2012 1 ISSN 2229-5518 IJSER © 2012

[2] Abraham D. Sofaer, David Clark, Whitfield Diffie ,Proceedings of a Workshop on Deterring Cyber Attacks: Informing Strategies and Developing Options for U.S. Policy http://www.nap.edu/catalog/12997.htmlCyber Security and International Agreements ,Internet Corporation for Assigned Names and Numbers pg185-205
[3] ThillaRajaretnam Associate Lecturer, School of Law, University of Western Sydney, The Society of Digital Information and Wireless Communications (SDIWC),International Journal of Cyber-Security and Digital Forensics (IJCSDF) 1(3): 232-240 2012 (ISSN: 2305-0012)

[4] Thomas H. Karas and Lori K. Parrott , Judy H. Moore , Metaphors for Cyber Security ,Sandia National Laboratories P.O. Box 5800 Albuquerque, NM 87185-0839

[5] BinaKotiyal, R H Goudar, and Senior Member, A Cyber Era Approach for Building Awareness in Cyber Security for Educational System in India PritiSaxena, IACSIT International Journal of Information and Education Technology, Vol. 2, No. 2, April 2012

[6] Loren Paul Rees, Jason K. Deane , Terry R. Rakes , Wade H. Baker, Decision support for Cyber security risk planning, Department of Business Information Technology, Pamplin College of Business, Virginia Tech., Blacksburg, VA 24061, United States b Verizon Business Security Solutions, Ashburn, VA 20147, United States

[7] S. Bistarelli, F. Fioravanti, P. Peretti, Using CP-nets as a guide for countermeasure selection, Proceedings of the 2007 ACM Symposium on Applied Computing (Seoul, Korea, 2007), 2007, pp. 300–304

. [8] Admiral Dennis C. Blair, Annual Threat Assessment, House Permanent Select Committee on Intelligence, 111th Congress, 1st sess., 2009.

[9] Mike McConnell, ―Mike McConnell on How to Win the Cyber-war We're Losing,‖ February 28, 2010, (accessed on July 19 2010).

Abstract: A method for detecting buildings from satellite/aerial images is proposed in this paper. The aim is to extract rectilinear buildings by using hypothesis. Hypothesis generation is accomplished by using edge detection and line generation methods. Hypothesis verification is carried out by using information obtained both from the color segmentation of HSV representation of the image. Satellite images is firstly filtered to sharpen the edges. The edges are extracted using Canny edge detection algorithm. These edges are the input for the Hough Transform stage which will produce line segments according to these extracted edges. Then, extracted line segments are used to generate building hypothesis. Verification of these hypotheses makes use of the outputs of the HSV color segmentation. In this study, color segmentation is processed on the HSV representation of the satellite/aerial images which are less sensitive to the illumination. Finally, Buildings are extracted from the urban areas.

Keywords: Building Extraction, Satellite images, Edge detection, Segmentation.

[1] T. Guo and Y. Yasuoka, "Snake-based approach for building extraction from high-resolution satellite images and height data in urban areas", Proceedings of 23rdAsian Conference on Remote Sensing, 2002.
[2] H. Rüther, H. M. Martine and E.G. Mtalo "Application of snakes and dynamic programming optimization technique in modeling of buildings in informal settlement areas" ISPRS Journal of Photogrammetric & Remote Sensing, Vol. 56, 2002.
[3] J. Peng D. Zhang and Y. Liu "An improved snake model for building detection from urban aerial images" Pattern Recognition Letters, Vol. 26, 2005.
[4] S. Levitt and F. Aghdasi. "An investigation into the use of wavelets and scaling for the extraction of buildings in aerial images", Proceedings of South African Symposium on Communications and Signal Processing, 1998.
[5] S. Noronha and R. Nevatia "Detection and modeling of buildings from multiple aerial images" IEEE Transactions on pattern analysis and machine intelligence, vol.23, no.5, 2001
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[7] ]M. Fradkin, H. maitre and M. Roux "Building detection from multiple aerial images in dense urban areas" Computer vision and image understanding, Vol 82, 2001.
[8] M. Cord, M. Jordan and J. Cocquerez "Accurate building structure recovery from high resolution aerial imagery" Computer vision and image understanding, Vol 82, 2001.
[9] J.Hu, S. You and U. Neumann "Integrating LiDAR, aerial image and ground images for complete urban building modeling" Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission, 2006.
[10] F.O. Chikomo, J.P. Mills and S.L. Barr "An integrated approach to level of detail building extraction using airborne lidar and optical imagery" Photogrammetric Image Analysis, Munich, Germany, 2007

Abstract: Handwriting recognition is the ability of a computer to receive and interpret intelligible handwritten input from sources such as photographs, touch-screens, paper documents and other devices. Written text image may be sensed "off line" from a piece of paper by optical scanning (optical character recognition). Devnagari script has 14 vowels and 33 consonants. Vowels occur either in isolation or in combination with consonants. Apart from vowels and consonants characters called basic characters, compound characters are there in Devnagari script, which are formed by joining two or more basic characters. Coupled to this in Devnagari script there is a practice of having twelve forms of modifiers with each for 33 consonants, giving rise to modified shapes which, depends on whether the modifier is placed to the left, right, top or bottom of the character. The net result is that there are several thousand different shapes or patterns, which makes Devnagari OCR more difficult to develop. Here focus is on the recognition of offline handwritten Hindi characters that can be used in common applications like commercial forms , bill processing systems ,bank cheques, , government records, , Signature Verification ,Postcode Recognition, , passport readers, offline document recognition generated by the expanding technological society .In this project , by the use of templet matching algorithm devnagari script characters are OCR from document images.

Keywords- Handwriting recognition, Devnagri script, OCR, Template Matching.

[1] I.K. Sethi and B. Chatterjee, "Machine Recognition of constrained Hand printed Devnagari", Pattern Recognition, Vol. 9, pp. 69-75, 1977.

[2] M. Hanmandlu, O.V. Ramana Murthy, Vamsi Krishna Madasu, "Fuzzy Model based recognition of Handwritten Hindi characters", IEEE Computer society, Digital Image Computing Techniques and Applications , 2007.

[3] M. Hanmandlu and O.V. Ramana Murthy, "Fuzzy Model Based Recognition of Handwritten Hindi Numerals", Intl.Conf. on Cognition and Recognition, pp. 490-496, 2005.

[4] Reena Bajaj, Lipika Dey, and S. Chaudhury, "Devnagari numeral recognition by combining decision of multiple connectionist classifiers", Sadhana, Vol.27, part. 1, pp.-59-72, 2002.

[5] Satish Kumar and Chandan Singh, "A Study of Zernike Moments and its use in Devnagari Handwritten Character Recognition", Intl.Conf. on Cognition and Recognition, pp. 514- 520, 2005.

Abstract: With the passing years, many advanced technologies have come into existence for efficientimage retrieval. Research in content-based image retrieval (CBIR) in the past has been focused on image processing, low-level feature extraction. The accuracy of retrieval has subsequently increased with the use of low level features such as color, texture, shape etc. But still image retrieval using low level features has been restricted to a specific efficiency. Extensive experiments on CBIR systems demonstrate that low-level image features cannot always describe high-level semantic concepts in the users‟ mind. Because, using low level features only does not include human perception. If human intervention is allowed in the image retrievalsystem the efficiency boosts up. Therefore, in this research my aim is to reduce the semantic Gap between the low level and high level features because the CBIR systems should provide Maximum support in bridging the "semantic gap‟ between low-level visual features and the Richness of human semantics.

Keywords- CPW, CST, FR4, LAN, WiMAX

[1]. SagarSoman, MitaliGhorpade, VrushaliSonone, SatishChavan, (2011), "Content Based Image Retrieval Using Advanced Colour and Texture Features", International Conference in Computational Intelligence (ICCIA).
[2]. Masato Yonekawa and Hiroaki Kurokawa,School of Computer Science, Tokyo University Of Technology, 2012, "The Content-Based Image Retrieval using the Pulse Coupled Neural Network", WCCI 2012 IEEE World Congress on Computational Intelligence
[3]. Hatice Cinar Akakin and Metin N. Gurcan , Senior Member, IEEE, 2012, "Content-Based Microscopic Image Retrieval System for Multi-Image Queries", IEEE transactions on information Technology in biomedicine, vol. 16, no. 4.
[4]. Steven C.H. Hoi, Student Member, IEEE , Michael R. Lyu, Fellow , IEEE , and Rong Jin, Member, IEEE, 2006, "A Unified Log-Based Relevance Feedback Scheme for Image Retrieval", IEEE Transactions on knowledge and data engineering, vol. 18, no.4.
[5]. GauravAggarwal, Ashwin T. V., and SugataGhosal, 2002, "An Image Retrieval System with Automatic Query Modification", IEEE Transaction on multimedia, vol. 4, no. 2.
[6]. Dr.Fuhui Long, Dr.Hongjiang Zhang and Prof. David Dagan Feng" Fundamentals of content based image retrieval".
[7]. M. Yonekawa, and H. Kurokawa, "The parameter optimization of the pulse coupled neural network for the pattern recognition," LNCS, vol.6254, pp.110–113, 2010

Abstract: Along with the development of network technology, web information are rapidly growing, and the way of information storage is gradually changed from the html to the database, thus web information can be divided into the surface web and deep web. Deep web is a concept corresponding to the surface web. It means from ordinary search engine that is difficult to discover the information content of a web page. The traditional crawler only crawl the content on the surface of a web, which makes the current traditional search engine, did not retrieve deep web data. Deep web compared with surface web has the advantage of large volume, high quality, theme single-minded, good structured. In view of several advantages, the establishment of deep web data integration system is becoming a research hotspot. The deep web query interface is the only entrance of the background database, so how to determine which web form is the query interface is important to the deep web information access. However, because the page proportion on the internet which contains querying interface is very small, using the traditional breadth-first strategy and keyword filtering method to crawl, it will download a lot of unrelated pages, spend a lot of resources, we need a way to efficiently find and collect the query interfaces through deep web crawling strategy. We proposed novel query planning approach, for executing different types of complex attribute through queries over multiple inter-dependent deep web data sources. increase accelerate query searching based on attribute selection, execution and propose optimization techniques, including query plan merging and grouping optimization

Keywords: Novel query planning approach, Deep web, Semantic Deep Web, Ontologies, attribute.

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[3.] Chelsea Hicks, Matthew Scheffer, Anne H.H. Ngu, Quan Z. Sheng," Discovery and Cataloging of Deep Web Sources" IEEE IRI 2012, August 8-10, 2012, Las Vegas, Nevada, USA.
[4.] Fajar Ardian, Sourav S Bhowmick," Efficient Maintenance of Common Keys in Archives of Continuous Query Results from Deep Websites" ICDE Conference 2011.
[5.] Yoo jung an, James geller, Yi-ta wu, Soon ae chun," semantic deep web: automatic attribute extraction from the deep web data sources" SAC'07, March 11-15, 2007, Seoul, Korea.
[6.] Ritu Khare Yuan An Il-Yeol Song," Understanding Deep Web Search Interfaces: A Survey" SIGMOD Record, March 2010 (Vol. 39, No. 1).
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Abstract: Outlier detection is one of the most important issues in recent years. Outlier detection is the process of detecting errors in data. The recent methods are mostly based on Numerical data, but these methods are not suitable for real time data such as web pages, business transactions etc., which are known as Categorical data. It is difficult to find outliers in categorical data. In this paper, we propose an approach to find outliers those are Comparison of Deviations. In Comparison of deviation method, we use hyper graph to calculate the deviations of each object in the database, and we measure the similarity between attributes in database.

Key words: Categorical data,Hyper graph, Deviation, Outliers, Hot algorithm, Similarity objects.

[1]. Aoying Zhou,LiWei,Weining Qian,Wenjin .HOT:Hypergraph-baesd Outlier for Categorical Data.
[2]. Hung-LengChen,Kung-TaChunag,Member IEEEandMing-Syan Chen, Fellow,IEEE,On Data Labeling for Clustering Categorical Data,November 2008
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Abstract: In sensor network a large amount of data need to be collected for future information retrieval. The data centric storage has become an important issue in sensor network. Storage nodes are used in this paper to store and process the collected data. This paper considers the storage node placement problem aiming to place limited storage nodes in sensor network to minimize the total energy cost for collecting the raw data and replying queries at the storage nodes. In this paper a strong data access model for placing storage nodes in sensor network is presented. We consider an application in which sensor networks provide real time data services to user. The main aim of this paper is to reduce the cost for raw data transfer, query diffusion, query reply by defining the best location of storage nodes in sensor network.

Keywords – Wireless sensor network, data query, data storage, data reply

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[2]. C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann, and F. Silva. Directed diffusion for wireless sensor networking. IEEE/ACM Trans. Netw., 11(1):2–16, 2003.
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