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• Open Access   Article

  Detection of Cross Browser Inconsistency by Comparing Extracted Attributes

  C.P.Patidar, Meena Sharma, Varsha Sharda

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.1-6, Feb-2017

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  The advancement in web technology and popularity of web applications amplifies the inconsistencies between various web browsers. These inconsistencies augment cross browser incompatibilities that constitute different look on different browsers for a particular web application. In some cases, Cross-Browser Inconsistencies (XBIs) consists of acceptable difference whereas these may entirely prevent users from accessing part of a web application’s functionality in other cases. Therefore, testing process of a web application must be performed comprehensively on multiple browsers to achieve consistency. Available tools and techniques require a considerable manual effort to recognize such issues and provide limited support for fixing the cause of the issues. In this paper, we propose a technique for detecting cross-browser issues without human intervention.

  Key-Words / Index Term
  Browser, Cross Browser Inconsistency, Reliability, Web application

  References
  [1] C.P.Patidar and Meena Sharma ,”An automated approach for cross browser inconsistency(XBI) detection”, Ninth annual ACM India conference organized by ACM India, Oct 21-23,2016.
  [2] Nepal Barskar, C.P.Patidar and Meena Sharma, “Analysis and Identification of Cross Browser Inconsistency Issues in Web Application using Automation Testing”, International Journal of Computer Science and Information Technology & Security (IJCSITS), ISSN: 2249-9555Vol.6, No3, May-June 2016.
  [3] Nepal Barskar and C.P. Patidar, “A Survey on Cross Browser Inconsistencies in Web Application”, International Journal of Computer Applications (0975 – 8887) Volume 137 – No.4, March 2016.
  [4] “WebTesting”, mindlance.com, testing@mindlance.com.
  [5] Ochin and Jugnu Gaur, “Cross Browser Incompatibility: Reasons and Solutions”, International Journal of Software Engineering & Applications (IJSEA), Vol.2, No.3, July 2011.
  [6] Shauvik Roy Choudhary, Husain Versee and Alessandro Orso, “WEBDIFF: Automated Identification of Cross-browser Issues in Web Applications”, 26th IEEE International Conference on Software Maintenance in Timisoara Romania, 978-1-4244-8628-1/10, 2010.
  [7] http://www.tcs.com/assurance, 2016.
  [8] Sanjay Dahiya1, Ved Parkash1 and T.R. Mudgal2, “Comprehensive Approach for Cross Compatibility Testing of Website “, National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing (RTMC) ,Proceedings published in International Journal of Computer Applications (IJCA) ,2011 .
  [9] Jatinder Manhas,“ Comparative Study of Cross Browser Compatibility as Design Issue in Various Websites” , BIJIT - BVICAM’s International Journal of Information Technology Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi (INDIA), NOV 2014.
  [10] Charles Reis, Brian Bershad, Steven D. Gribble and Henry M. Levy, “Using Processes to Improve the Reliability of Browser-based Applications”, University of Washington Technical Report UW-CSE, DEC 2007.
  [11] Sung-Whan Woo, Omar H. Alhazmi and Yashwant K. Malaiya,“AN ANALYSIS OF THE VULNERABILITY DISCOVERY PROCESS IN WEB BROWSERS”, proceeding of the 10th IASTED International Conference Software engineering and Applications, Dallas,TX,USA,ISBN: 0-88986-642-2 / CD: 0-88986-599-X, NOVEMBER 13-15, 2006,
  [12] Ali Mesbah and Mukul R. Prasad,“ Automated Cross-Browser Compatibility Testing”, ICSE ’11,Waikiki, Honolulu, HI, USA ,ACM 978-1-4503-0445-0/11/05, May 21–28, 2011 .
  [13] Shauvik Roy Choudhary, Mukul R. Prasad and Alessandro Orso,“ X-PERT: A Web Application Testing Tool for Cross-Browser Inconsistency Detection”, ISSTA’14,San Jose, CA, USA,Copyright 2014 ACM 978-1-4503-2645-2/14/07,July 21–25, 2014.
  [14] Nadja Peters1, Sangyoung Park1, Samarjit Chakraborty1, Benedikt Meurer2, Hannes Payer2 and Daniel Clifford2, “Web Browser Workload Characterization for Power Management on HMP Platforms”, CODES/ISSS ’16 Pittsburgh, PA, USA, ACM, and ISBN: 978-1-4503-4483-8/16/10, October 01-07 2016.
  [15] Shauvik Roy Choudhary, Mukul R. Prasad and Alessandro Orso, “CROSSCHECK: Combining Crawling and Differencing to Better Detect Cross-browser Incompatibilities in Web Applications”, 2012.
  [16] Shauvik Roy Choudhary,”Detecting Cross-browser Issues in Web Applications”, ICSE ’11, Waikiki, Honolulu, HI, USA, ACM 978-1-4503-0445-0/11/05, May 21–28, 2011.
  

  Citation
  C.P.Patidar, Meena Sharma, Varsha Sharda, "Detection of Cross Browser Inconsistency by Comparing Extracted Attributes," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.1-6, 2017

• Open Access   Article

  Hybrid DWT, FFT and SVD based Watermarking Technique for Different wavelet Transforms

  Kanchan Thakur

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.7-12, Feb-2017

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  imperceptibility and robustness requirements. Digital watermarking seems as an effective process of protecting multimedia contents such as copyright safeguard and authentication. In this paper, we endorse SVD founded digital watermarking procedure for powerful watermarking of digital pictures for copyright safety. In proposed research, a novel and robust digital watermarking method is introduced in which a mixture of DWT (Discrete Wavelet Transform) and FFT (Fast Fourier Transform) along with SVD (Singular Value Decomposition) is applied. Due to the usage of this combination of 3 techniques in our proposed work, it increases the robustness and imperceptibility of extracted image. One of the vital essential benefits of the proposed idea is the robustness of the system on extensive set of attacks. Analysis and experimental outcome show a lot accelerated effectiveness of the proposed method in evaluation with the pure SVD-established watermarking and the procedure without making use of some wavelet perform. The results are compared with Base Work in which single level DWT-SVD combination is taken for watermarking for copy right security. It is shown through PSNR (Peak signal-to-noise ratio) that it provided a very high imperceptibility. Experimental outcome verify that the proposed system given good quality picture value of watermarked pictures.

  Key-Words / Index Term
  Watermarking; embedding; extraction; PSNR

  References
  [1] Naved Alam, “A Robust Video Watermarking Technique using DWT, DCT, and FFT”. 2016, IJARCSSE
  [2] Manjinder Kaur and Varinder Kaur Attri “A Survey on Digital Image Watermarking and Its Techniques” International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 8, No. 5 (2015), pp. 145-150
  [3] Mei Jiansheng, Li Sukang, “A Digital Watermarking Algorithm Based On DCT and DWT”, Proceedings of the 2009 International Symposium on Web Information Systems and Applications (WISA‟09) Nanchang, P. R. China, May 22-24, 2009, pp. 104-107
  [4] Prabhishek Singh, R S Chadha “A Survey of Digital Watermarking Techniques, Applications and Attacks”International Journal of Engineering and Innovative Technology (IJEIT) Volume 2, Issue 9, March 2013.
  [5] Ashminder Kaur, Ms. Lofty, "A Review of Colour Image Watermarking Scheme Based Image Normalized", International Journal of Computer Sciences and Engineering, Volume-04, Issue-07, Page No (183-185), Jul -2016
  [6] Rupali Nayyar, Randhir Singh, Ritika, “Improved Audio Watermarking Using Arnold Transform, DWT and Modified SVD”. IJIRSET.2016
  [7] Priya Chandrakar and Shahana Gajala Qureshi, "A Review on Video Watermarking", International Journal of Computer Sciences and Engineering, Volume-03, Issue-04, Page No (48-52), Apr -2015.
  [8] Shaikh Shoaib, Prof. R. C. Mahajan “Authenticating Using Secret Key in Digital Video Watermarking Using 3- Level DWT” International Conference on Communication, Information & Computing Technology (ICCICT), Jan. 16-17,IEEE 2015.
  [9] Baiying Lei, Ing Yann Soon, and Ee-Leng Tan “Robust SVD-Based Audio Watermarking Scheme With Differential Evolution Optimization” IEEE Transactions On Audio, Speech, And Language Processing, Vol. 21, No. 11, November 2013.
  [10] Y. Shantikumar Singh, B. Pushpa Devi, and Kh. Manglem Singh, “A Review of Different Techniques on Digital Image Watermarking Scheme”, International Journal of Engineering Research, ISSN:2319- 6890, Volume No.2, Issue No.3, pp:193-199, 01 July 2013.
  [11] Chen Li, Cheng Yang, Wei Li, “Wavelet Bases and Decomposition Series in the Digital Image Watermarking”. Advances in Intelligent and Soft Computing, Advances in Multimedia, Software Engineering and Computing Vol.2 , s.l. : Springer, 2012.
  [12] A.Kala and K.Thaiyalnayaki, "Chaos based Image Watermarking using IWT and SVD", International Journal of Computer Sciences and Engineering, Volume-03, Issue-01, Page No (72-75), Jan -2015
  

  Citation
  Kanchan Thakur, "Hybrid DWT, FFT and SVD based Watermarking Technique for Different wavelet Transforms," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.7-12, 2017

• Open Access   Article

  Zero day Attacks Defense Technique for Protecting System against Unknown Vulnerabilities

  Umesh Kumar Singh, Chanchala Joshi, Suyash Kumar Singh

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.13-18, Feb-2017

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  Every organization connected to the internet has one common threat of zero-day attacks. Zero-day exploits are unnoticed until a specific vulnerability is actually identified and reported. Zero-day attacks are difficult to defend against because it is mostly detected only after it has completed its course of action. Protecting networks, applications and systems from zero-day attacks is the daunting task for organization’s security persons. This paper analyzed the research efforts in relation to detection of zero-day attacks. The fundamental limitations of existing approaches are the signature generation of unknown activities and the false alarming rate of anomalous behavior. To overcome these issues, this paper proposes a new approach for zero-day attacks analysis and detection, which senses the organization’s network and monitors the behavioral activity of zero-day exploit at each and every stage of their life cycle. The proposed approach in this paper provides a machine learning based framework to sense network traffic that detects anomalous behavior of network in order to identify the presence of zero-day exploit. The proposed framework uses supervised classification schemes for assessment of known classes with the adaptability of unsupervised classification in order to detect the new dimension of classification.

  Key-Words / Index Term
  zero day attacks, unknown vulnerabilities, detection system, malware analysis, network security

  References
  detecting zero-day polymorphic worms," Advance Computing Conference (IACC), 2014 IEEE International, pp.95-100, 21-22 Feb. 2014.
  [2] “Internet Security Threat Report”, Internet Report Volume 21, APRIL 2016.
  [3] Kaur, R.; Singh, M., “Automatic Evaluation and Signature Generation Technique for Thwarting Zero-Day Attacks”, Second International Conference, SNDS 2014, India, pp 298-309, March 13-14, 2014.
  [4] K. Ren, C. Wang, and Q. Wang, “Security challenges for the public cloud,” IEEE Internet Computing, vol. 16, no. 1, pp. 69–73, 2012.
  [5] Y. Yang, S. Zhu, and G. Cao, “Improving sensor network immunity under worm attacks: a software diversity approach,” in Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing. ACM, 2008, pp. 149–158.
  [6] J. Caballero, T. Kampouris, D. Song, and J. Wang, “Would diversity really increase the robustness of the routing infrastructure against software defects?” in Proceedings of the Network and Distributed System Security Symposium, 2008.
  [7] White Paper, “ZERO-DAY DANGER: A Survey of Zero-Day Attacks and What They Say About the Traditional Security Model”, FireEye Security Raimagined, 2015.
  [8] L. Wang, M. Zhang, S. Jajodia, A. Singhal, and M. Albanese, “Modeling network diversity for evaluating the robustness of networks against zeroday attacks,” in Proceedings of ESORICS’14, 2014, pp. 494–511.
  [9] A. AlEroud, G. Karabatis, “Toward Zero-day Attack Identification Using Linear Data Transformation Techniques”, IEEE 7th International Conference on Software Security and Reliability, pp 161-168, 18 - 20 Jun 2013.
  [10] T. Leinster and C. Cobbold, “Measuring diversity: the importance of species similarity,” Ecology, vol. 93, no. 3, pp. 477–489, 2012.
  [11] L. Bilge, T. Dumitras, “Before we knew it: an empirical study of zero-day attacks in the real world”, CCS `12 Proceedings of the 2012 ACM conference on Computer and communications security, pp 833-844, Raleigh, North Carolina, USA — October 16 - 18, 2012.
  [12] M. Rathor, D. M. Dakhane, “Predicting Unknown Vulnerabilies in Network Using K- zero Day Safety Technique”, International Journal of Advanced Research in Computer Science and Software Engineering 5 (4), pp. 221-224, April- 2015.
  [13] C. Joshi, U.K. Singh, “A Review on Taxonomies of Attacks and Vulnerability in Computer and Network System”. International Journal of Advanced Research in Computer Science and Software Engineering (IJRCSSE) Volume 5, Issue 1, January 2015, pp 742-747.
  [14] C. Joshi, U.K. Singh, “ADMIT- A Five Dimensional Approach towards Standardization of Network and Computer Attack Taxonomies”. International Journal of Computer Application (IJCA, 0975 – 8887), Volume 100, Issue 5, August 2014, pp 30-36
  [15] C. Joshi and U. Singh, “Analysis of Vulnerability Scanners in Quest of Current Information Security Landscape” International Journal of Computer Application (IJCA, 0975 – 8887), Volume 145 No 2, pp. 1-7, July 2016.
  [16] C. Joshi, and U. K Singh, “Performance Evaluation of Web Application Security Scanners for More Effective Defense” International Journal of Scientific and Research Publications (IJSRP), Volume 6, Issue 6, pp 660-667, June 2016, ISSN 2250-3153.
  [17] Z. Li, M. Sanghi, Y. Chen, “Hamsa∗: Fast Signature Generation for Zero-day Polymorphic Worms with Provable Attack Resilience”, Proceedings of the 2006 IEEE Symposium on Security and Privacy (S&P’06).
  [18] M. Frigault, L. Wang, A. Singhal, and S. Jajodia, “Measuring network security using dynamic bayesian network,” in Proceedings of 4th ACM QoP, 2008.
  [19] A. Lelli. (2010, Jan.) The trojan. hydraq incident: Analysis of the aurora 0-day exploit, Available: http://www.symantec.com/connect/blogs/trojanhydraq-incidentanalysis-aurora-0-day-exploit
  [20] N. Falliere, L. O. Murchu, and E. Chien.(2011, Feb.) W32.stuxnet dossier, Available:
  http://www.h4ckr.us/library/Documents/ICSEvents/Stuxnet%20Dossier%20(Symantec)%20v1.4.pdf
  [21] Symantec. (2011, Nov.) W32.duqu the precursor to the next stuxnet, Available:
  http://www.symantec.com/content/en/us/enterprise/media/s ecurity response/whitepapers/w32
  duqu the precursor to the next stuxnet.pdf
  [22] R. Goyal and P. Watters, “Obfuscation of stuxnet and flame malware,” in Proc. 3rd Int. Conf. on Applied Informatics and Computing Theory, pp. 150–154, Barcelona, Oct. 2012.
  [23] “McAfee Labs 2017 Threats Predictions”, Intel Security, November 2016.
  [24] P. Ammann, D. Wijesekera, and S. Kaushik, “Scalable, graph-based network vulnerability analysis,” in Proceedings of ACM CCS’02, 2002.
  [25] D. Hammarberg, “The Best Defenses against Zero-day Exploits for Various-sized Organizations”, SANS Institute InfoSec Reading Room, September 21st 2014.
  [26] M. Albanese, S. Jajodia, and S. Noel, “A time-efficient approach to cost-effective network hardening using attack graphs,” in Proceedings of DSN’12, 2012, pp. 1–12.
  [27] Y. Alosefer, O.F. Rana, "Predicting client-side attacks via behavior analysis using honeypot data", Next Generation Web Services Practices (NWeSP), 2011 7th International Conference on Next Generation Web Services Practices, pp.31,36, 19-21 Oct. 2011.
  [28] I. Kim, K. Kim, “A Case Study of Unknown Attack Detection against Zero-day Worm in the HoneyNet Environment”, 11th International Conference on Advanced Communication Technology (ICACT), pp 1715-1720, 15 - 18 Feb 2009.
  

  Citation
  Umesh Kumar Singh, Chanchala Joshi, Suyash Kumar Singh, "Zero day Attacks Defense Technique for Protecting System against Unknown Vulnerabilities," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.13-18, 2017

• Open Access   Article

  Data Mining: A Comparative Study of its Various Techniques and its Process

  Marie Fernandes

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.19-23, Feb-2017

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  Abstract
  Data Mining also called as Information Mining or certainty finding is the term which is utilized for removing or finding helpful data from the information that are available in vast databases. It likewise investigates covered up or prescient examples of content that can be said as predictive patterns of text, from databases. This term showed up in 1990`s. It is a procedure that examines or analyses information from alternate points of view and compresses it into helpful data. This data can then be utilized for different business purposes by various undertakings. Information mining from that point forward has turned into an essential piece of Knowledge Discovery in Databases (KDD), data Digging, data fishing, and Data Collecting as appropriately termed as Data Dredging, Data Fishing, and Information Harvesting. It turns a large collection of data into knowledge that can fulfill current global challenge because computerization has lead to explosively growing, widely available and gigantic body of data floating through WWW. Data mining methods are expected to change this information into sorted out learning. Keeping in mind the end goal to do as such; capable and flexible tools are required which would reveal important data from the huge measures of information. This need has prompted to numerous strategies, for example, Classical Techniques which incorporates Statistics which provides measurements, Neighborhoods and Clustering which works through grouping and the Cutting edge Procedures incorporates Trees, Networks and Rules. The dominant part of information mining methods manages distinctive information sorts. The scope, purpose and motivation behind this paper is to do a relative investigation of the different procedures accessible in information mining with their preferences, burdens and the field where they can be properly utilized. This paper presents overview of data mining, the different strategies of data or information mining.

  Key-Words / Index Term
  Data mining, Data Dredging, Statistics, Nearest Neighbor, Decision Trees and Neural Networks

  References
  [1] Lee, S and Siau, K. “A review of data mining techniques”, Journal of Industrial Management & Data Systems, Volume-101, Issue-01, pp (41-46), 2001.
  [2] Berson, A, Smith, S, and Thearling, K., “Building Data Mining Applications for CRM”, McGraw-Hill Professional, First(1st) edition, 1999.
  [3] S Mahajan, "Convergence of IT and Data Mining with other technologies ", International Journal of Scientific Research in Computer Science and Engineering, Volume-01, Issue-04, pp (31-37), Aug 2013
  [4] Jain, A.K., Murty, M.N., and Flynn, P.J. “Data Clustering: A Review, Journal ACM Computing Surveys (CSUR)”, Volume-31, Issue-0 3, pp (264-323), 1999.
  [5] Jaskaranjit Kaur and Gurpreet Kaur , "Clustering Algorithms in Data Mining: A Comprehensive Study", International Journal of Computer Sciences and Engineering, Volume-03, Issue-07, Page No (57-61), Jul -2015.
  [6] B Khalid, N Abdelwahab. “A Comparative Study of Various Data Mining Techniques: Statistics, Decision Trees and Neural Networks”, International Journal of Computer Applications Technology and Research, Volume-5, Issue-03, pp (172 – 175), 2016.
  [7] J.Sheela Jasmine, "Application of Fuzzy Logic in Neural Network Using Data Mining Techniques: A Survey", International Journal of Computer Sciences and Engineering, Volume-04, Issue-04, Page No (333-341), Apr -2016.
  [8] C Kaur, P Kapoor, M Bala , “Role of Neural network in data mining”, International Journal for Science and Emerging Technologies with Latest Trends, Volume – 02, Issue -01, pp (20-28), 2012
  [9] P Gaur, “Neural Networks in Data mining”, International Journal of Electronics and Computer Science Engineering”, Volume -01, Issue -03, pp (1449-1453), 2012
  

  Citation
  Marie Fernandes , "Data Mining: A Comparative Study of its Various Techniques and its Process," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.19-23, 2017

• Open Access   Article

  Information and Communication Technologies in State affairs: Challenges of E-Governance

  Stephen John Beaumont

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.24-26, Feb-2017

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  Abstract
  The mainstream conclusion about the purpose of implementing e-governance procedures is that these enhance good governance. This good governance is generally characterised by participation, transparency and accountability. This has proven to be a major problem in many developing countries. But the recent advances in information and communication technologies provide opportunities to transform the relationship between governments and citizens so as to enhance the achievement of good governance goals. In this paper we analyze the benefits than can be achieved by implementing E-Governance programs, and also the challenges these changes associated with these innovations.

  Key-Words / Index Term
  E-Government, Governance, Transparency

  References
  [1] UNESCO. 2011. E-Governance. http://portal.unesco.org/ci/en/ev.php-URL_ID=3038&URL_DO=DO_TOPIC&URL_SECTION=201.html
  [2] Panda, Bibhu Prasad, & Swain, Dillip K. 2009. Effective communications through e-governance and e-learning. Chinese Librarianship: an International Electronic Journal, 27. URL: http://www.iclc.us/cliej/cl27PS.pdf
  [3] Saxena, K. 2005. Towards excellence in e-governance. International Journal of Public Sector Management, 18(6).
  [4] Bannister, Frank and Connolly, Regina. 2011. “New Problems for OLD? Defining e-Governance.” Proceedings of the 44th Hawaii International Conference on System Sciences
  [5] UNESCO. 2005. http://portal.unesco.org/ci/en/ev.php-URL_ID=2179&URL_DO=DO_TOPIC&URL_SECTION=201.html
  [6] UNESCO. 2005 (2). http://portal.unesco.org/ci/en/ev.php-URL_ID=4404&URL_DO=DO_TOPIC&URL_SECTION=201.html
  [7] Kashem, Mohammad Abul , Nasim Akhtar and Anisur Rahman. 2014. “An Information System Model for e-Government of Digital Bangladesh.” IJCSNS International Journal of Computer Science and Network Security, VOL.14 No.11, November 2014.
  [8] Ojo, John. 2014. “E-governance: An imperative for sustainable grass root development in Nigeria.” School of Politics and International Studies, University of Leeds, United Kingdom.
  [9] Kumar, Puneet, Kumar, Dharminder &Kumar, Narendra. 2014. “E-Governance in India: Definitions, Challenges and Solutions.” International Journal of Computer Applications (0975 – 8887) Volume 101– No.16, September 2014
  [10] Signore, Oreste; Chesi, Franco and Pallotti, Maurizio. 2005. “E-Government: Challenges and Opportunities.” CMG Italy – XIX Annual Conference. Florence, Italy.
  [11] Pardeep Mittal & Amandeep Kaur. 2013. “E-Governance - A challenge for India.” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET). Volume 2, Issue 3, March.
  [12] Fang, Zhiyuan. E-Government in Digital Era: Concept, Practice, and Development. International Journal of The Computer, The Internet and Management, Vol. 10, No.2, 2002, p 1-22
  [13] Freeman, Julie. 2012. “E-Government Engagement and the Digital Divide.” Conference Paper. CeDEM Asia 2012. Conference for E-Democracy & Open Government: Social & Mobile Media for Governance. Singapore.
  

  Citation
  Stephen John Beaumont, "Information and Communication Technologies in State affairs: Challenges of E-Governance," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.24-26, 2017

• Open Access   Article

  Comparative Study and Analysis of Unique Identification Number and Social Security Number

  Sarita Sharma, Rakesh Gaherwal

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.27-30, Feb-2017

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  Abstract
  As we study the detailed information and use of Unique Identification number provided by Indian Government and Social Security Number provided by U.S., an idea came in our mind to merge the concept of UID and SSN so that these two can be used not only to identify the identity of a person but also for inspecting the account information of the person which may be helpful to know about the black money hold by the person if needed. The use of the Social Security number (SSN) has extended significantly for tracking the earnings details of U.S. workers for Social Security entitlement and which is beneficial to compute the universal identification of the workers. We need a Social Security number to get a job, collect Social Security benefits and get some other government services. But we don`t often need to show our Social Security card..Unique Identification Aadhar Card is provided to identify the personal identity of a citizen on the basis of some biometric hand and eye impression with his or her personal address. Today in India to recover the money problem Modiji has started the scheme of renewable the currency running from several years to come in front the black money holders. If we apply the concept of SSN card with Aadhar card then this problem can be resolved very easily. In our paper we have just try to show the details holding through UID and SSN so that one can easily think that how the merging of UID and SSN may be possible.

  Key-Words / Index Term
  Demographic Data, Biometric Data , STQC, Numident, IRS

  References
  [1] Law Resource India the National Identification Authority of India Bill, 2010 Posted in constitution, governance, uid identity by nnlrj india on June 19, 2011
  [2] Carolyn Puckett, "The Story of the Social Security Number", Social Security Bulletin, vol. 69, No. 2, 2009
  [3] Kouri, Jim ,"Social Security Cards: De Facto National Identification", American Chronicle, March 9, 2005
  [4] https://www.ssa.gov/history/ssn/geocard.html
  [5] Social Security Administration. "The SSN Numbering Scheme". Retrieved 12/01/2017
  [6] Elisabeth Ilie- Zudora,Zsolt Keménya,Fred van Blommesteinb,László Monostoria, André van der Meulenb ,“A survey of applications and requirements of unique identification systems and RFID techniques”, vol. 62, Issue 3, pp. 227–252, April 2011
  [7] "Social Security Number Randomization". Socialsecurity.gov. Retrieved 13/01/2017
  [8] Swati Chauhan, Chetanshi Sharma, Geetanjali, Akshita Verma, Jaya Gupta.” Survey Paper on UID System Management”
  [9] International Journal of IT, Engineering and Applied Sciences Research (IJIEASR) ISSN: 2319-4413 ,vol. 3, No. 2, 2014
  [10] James E. Duggan Robert Gillingham John S. Greenlees, “Distributional Effects of Social Security: The Notch Issue Revisited”, Public Finance Quarterly, pp. 349-370, July 1996
  [11] Shraddha Thorat and Vikrant Bhilare , “Comparative Study of Indian UID Aadhar and other Biometric Identification Techniques in Different Countries”, International Journal of Current Trends in Engineering & Research (IJCTER) e-ISSN 2455–1392 ,vol. 2, Issue 6, pp. 62 – 72, June 2016
  “Aadhaar Number vs
  

  Citation
  Sarita Sharma, Rakesh Gaherwal, "Comparative Study and Analysis of Unique Identification Number and Social Security Number," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.27-30, 2017

• Open Access   Article

  A proposed Method for Mining High Utility Itemset with Transactional Weighted Utility using Genetic Algorithm Technique (MHUI_TWU-GA)

  Pradeep K.Sharma, Vaibhav Sharma and Jagrati Nagdiya

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.31-35, Feb-2017

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  Abstract
  Utility mining is a technique to prune high utility itemset from the given transactional database on the basis of user-defined minimum utility threshold. Frequent itemset mining, only focus on itemset appear most frequently in the database while in utility mining we concern about utility i.e. importance or profit of itemset according to the user preference. In this paper we are proposing a two-phase algorithm, in the first phase, we are using weighted transaction utility concept to calculate and compare the utility of itemset with minimum utility threshold and then in the second phase, we are proposing genetic algorithm technique to search high utility itemset from the recognized transactional database obtain after the first phase.

  Key-Words / Index Term
  Data Mining, Weighted Transaction Utility, Utility Mining, Genetic Algorithm

  References
  [1]. S. Kannimuthu, Dr. K .Premalatha, Discovery of High Utility Itemsets Using Genetic Algorithm, International Journal of Engineering and Technology (IJET), Vol 5 No 6 Dec 2013-Jan 2014.
  [2]. VincentS. Tseng, Cheng-Wei Wu, Bai-En Shie, and PhilipS.Yu.UP-Growth: An Efficient Algorithm for High Utility Itemset Mining. InKDD’10, July25–28, 2010, Washington, DC, USA.2010ACM.
  [3]. Pradeepk. Sharma, Abhishe k Raghuvanshi, An Efficient Methodfor Mining High Utility Data fromaDataSet, in International Journal of Advanced Research in Computer Science and Software Engineering, Volume3, Issue11, November2013.
  [4]. R.Agrawal and R.Srikant.Fast algorithms for mining association rules.InProc.ofthe20thInt`lConf.onVery Large Data Bases, pp.487-499, 1994.
  [5]. J.Han,J.Pei,andY.Yin .Mining frequent patterns without candidate generation.InProc.of the ACM-SIGMOD Int`l Conf. on Management of Data, pp.1-12,2000.
  [6]. H.Yao,H.J.Hamilton,L.Geng, A unified framework for utility-based measures for mining itemsets. In Proc.of ACM SIGKDD 2nd Workshop on Utility-Based Data Mining, pp.28-37, USA,Aug., 2006.
  [7]. Y.Liu, W.Liao, and A.Choudhary.A fast high utility itemsets mining algorithm. InProc. ofthe Utility-Based Data Mining Workshop,2005.
  [8]. Y.-C.Li,J.-S.Yeh,andC.-C.Chang.isolated items discarding strategy for discovering high utility itemsets, In Data &Knowledge Engineering, Vol. 64,Issue1, pp.198-217, Jan., 2008.
  [9]. C.F.Ahmed,S.K.Tanbeer,B.-S.Jeong,andY.-K.Lee.Efficient tree structures for high utility pattern mining in incremental databases.In IEEE Transactionson Knowledge and Data Engineering,Vol.21,Issue12,pp.1708-1721,2009.
  [10]. Yu-Chiang Li, Jieh-Shan Yeh and Chin-Chen Chang, "Isolated items discarding strategy for discovering high utility itemsets", Data and Knowledge Engineering, Elsevier Journal, Vol. 64, pp. 198-217, 2008.
  

  Citation
  Pradeep K.Sharma, Vaibhav Sharma and Jagrati Nagdiya, "A proposed Method for Mining High Utility Itemset with Transactional Weighted Utility using Genetic Algorithm Technique (MHUI_TWU-GA)," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.31-35, 2017

• Open Access   Article

  Analysis of Security in Cloud-Learning Systems

  Sangeetha Rajesh

  Survey Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.36-40, Feb-2017

  Abstract

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  Abstract
  Developments in computing are influencing many aspects of education. ELearning introduced a new learning environment. The e-learning systems need to cope its processes with the progressive technologies like cloud computing. Cloud computing is highly scalable virtualized resources that users can access. Cloud computing made a significant influence in the educational environment. Throughout paper elearning system using cloud technology is referred as cloud-learning systems. This paper mainly emphases on the impact of cloud computing in e-learning system with respect to security. In this paper architecture for cloud learning system is proposed which has security as a service model. The responsibilities of each participant in the system and the services provided by security as a service model are also studied.

  Key-Words / Index Term
  Cloud Computing, cloud-learning, eLearning, IaaS, PaaS, SaaS, SCaaS

  References
  REFERENCES
  [1] SOM NAIDU,” E-Learning A Guidebook of Principles, Procedures and Practices” 2 Revised Edition, CEMCA, 2006.
  [2] Xiang Tana, Bo Aib, “The Issues of Cloud Computing Security in High-speed Railway”, International Conference on Electronic & Mechanical Engineering and Information Technology 2011.
  [3] H. Takabi, J. B. D. Joshi, G.Ahn., “Security and Privacy Challenges in Cloud Computing Environments”, IEEE Security Privacy Magazine, Vol. 8, IEEE Computer Society, 2010, pp.24-31.
  [4] Shivlal Mewada, Umesh Kumar Singh and Pradeep Sharma, "Security Enhancement in Cloud Computing (CC)", ISROSET-International Journal of Scientific Research in Computer Science and Engineering, Vol-01, Issue-01, Page No (31-37), Feb 2013.
  [5] Surabhi Shukla and Dharamjeet kumar, "Cloud’s Software- Security as a Service(S-SaaS) via Biometrics", International Journal of Computer Sciences and Engineering, Vol-02, Issue-03, Page No (119-124), Mar -2014.
  [6] Shaheen Ayyub and Devshree Roy, "Cloud Computing Characteristics and Security Issues", International Journal of Computer Sciences and Engineering, Vol-01, Issue-04, Page No (18-22), Dec -2013.
  [7]Sajjad Hashemi, Sayyed Yasser Hashemi, “ Cloud Computing for Elearning with more emphasis on security issues” International Journal of Computer, Control and Quantum and information engineering, Vol 7,No. 9, pp.607-612, 2013
  [8] Rajesh Piplode, Pradeep Sharma and Umesh Kumar Singh, "Study of Threats, Risk and Challenges in Cloud Computing", ISROSET-International Journal of Scientific Research in Computer Science and Engineering, Vol-01, Issue-01, Page No (26-30), Feb 2013.
  [9] A.A. Elusoji, L.N. Onyejegbu & O.S. Ayodele (2013). “An Effective Measurement of Data Security in a Cloud Computing Environment”. Afr J. Of Comp & ICTs. Vol 6, No. 2. pp 67-76
  [10] cloud-basedlms-etec522. Weebly (2015, September 16). (Online). Available.http://cloud-basedlms-tec522. weebly.com/ security.html.
  [11] Vishal Kadam, Makhan Kumbhkar , "Security in Cloud Environment", ISROSET-International Journal of Scientific Research in Computer Science and Engineering, Volume-02, Issue-03, Page No (6-10), Jun 2014.
  [12] D. Kasi Viswanath, S. Kusuma & Saroj Kumar Gupta “Cloud Computing Issues and Benefits Modern Education” Vol XII, Issue X Version I, pp. 15-19, July 2012.
  [12] Vishnu Patidar, Makhan Kumbhkar, “Analysis of Cloud Computing Security Issues in Software as a Service”, International Journal of Scientific Research in Computer Science and Engineering, Vol-02, Issue -03, PP (1-5) Jun 2014.
  [13] Cloudcomputingadmin.com, 2016, May 26, (online). Available: http://www.cloudcomputingadmin.com/articles-tutorials/security/security-service-cloud-based-rise-part1.html
  

  Citation
  Sangeetha Rajesh, "Analysis of Security in Cloud-Learning Systems," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.36-40, 2017

• Open Access   Article

  Security Issues on Online Transaction of Digital Banking

  Wakil Ghori

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.41-44, Feb-2017

  Abstract

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  Citation

  Abstract
  Digital banking system has a broad range of benefits that add value to customer’s fulfillment in term of superior service quality, and at the same time it enables banks to add a competitive benefit over other financial competitors. Presently, Digital banking customers only require a smart gadget with access to the Internet to use digital banking services. Customers can access their digital banking accounts from anywhere in the world. However, more attention towards digital banking security is required and needed against fake behavior because the lack of control over security policies makes digital banking still untrusted for many customers till now. This paper presents challenges and security issues related to digital banking. Various types of cyber attacks, fraud strategies, and prevention methods used by digital banks, are also presented in this paper. This research work studies security and safety issues of online banking.

  Key-Words / Index Term
  Digital Banking, Hacking, Rootkits, Phishing, encryption, OTP, QR code

  References
  [1] Rajpreet Kaur Jassal and Ravinder Kumar Sehgal, “Online Banking Security Flaws: A Study”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume-03, Issue-08, ISSN-2277 128X , August 2013.
  [2] Elbek Musaev and Muhammed Yousoof, “A Review on Internet Banking Security and Privacy Issues in Oman”, ICIT 2015- The 7th International Conference on Information Technology, January 2015.
  [3] Mr. Shakir Shaik and Dr. S.A. Sameera, “Security Issues in E-Banking Services in Indian Scenario”, Asian Journal of Management Sciences, Volume-02, Issue-03, pp.(28-30). ISSN: 2348-0351, March 29, 2014.
  [4] ‘Security features in Internet Banking’, newagebanking.com/finsec/modernizing-digital-security-to-protect-banks-from-fraud/, Jan 16, 2017
  [5] Kenneth Edge, “The Use of Attack and Protection Trees to Analyze Security for an Online Banking System”, HICSS 2007-40th Annual Hawaii International Conference on System Science, Online ISSN: 1530-1605
  [6] Emeka Nwogu and McChester Odoh, “Security Issues Analysis on Online Banking Implementations in Nigeria”, International Journal of Computer Science and Telecommunications, Volume-06, Issue-01, ISSN 2047-3338, January 2015,
  [7] Tejinder Pal Singh Brar, Dr. Dhiraj Sharma, Dr. Sawtantar Singh Khurmi, “Vulnerabilities in e-banking: A study of various security aspects in e-banking”, International Journal of Computing & Business Research, ISSN (Online): 2229-6166
  [8] Panida Subsorn and Sunsern Limwiriyakul, “An Analysis of Internet Banking Security of Foreign Subsidiary Banks in Australia: A Customer Perspective”, IJCSI International Journal of Computer Science Issues, Vol. 09, Issue 02, ISSN (Online): 1694-0814, March 2012.
  

  Citation
  Wakil Ghori, "Security Issues on Online Transaction of Digital Banking," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.41-44, 2017

• Open Access   Article

  A Security Key Management Model for Cloud Environment

  Nitesh Jain, Pradeep Sharma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.1 , pp.45-48, Feb-2017

  Abstract

  Full-Text HTML

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  Citation

  Abstract
  Security is the most important factor in cloud computing for ensuring client data is placed on secure mode in the cloud. For any organization, Data is very valuable assets but as number of users and quantity of data is increasing day by day, which cause the need of data security on cloud. For cloud computing there should be various security and privacy measures like identity management, physical personal security, availability, application processing authentication, atomic transaction etc. Security is mostly broken when any one doesn’t follow certain security measure or not being attentive for threat and vulnerabilities. Dealing with “One Cloud” providers is predicted to become minor popular with customers due to risks of service availability failure and the possibility of malicious insiders in the one cloud. In this research paper we have also dealing with a security key management model for cloud environment or cloud of cloud.

  Key-Words / Index Term
  Cloud Computing, Security Model, Data Security, Cloud Environment

  References
  [1]. S.L. Mewada, U.K. Singh, P. Sharma, "Security Enhancement in Cloud Computing (CC)", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.1, pp.31-37, 2013.
  [2]. R. Piplode, P. Sharma and U.K. Singh, "Study of Threats, Risk and Challenges in Cloud Computing", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.1, pp.26-30, 2013.
  [3]. S. Ayyub, D. Roy, "Cloud Computing Characteristics and Security Issues", International Journal of Computer Sciences and Engineering, Vol.1, Issue.4, pp.18-22, 2013.
  [4]. G.Malini and A.Immaculate Mercy , "Evaluating Synchronized Determination Assembly in Multi-Cloud Atmosphere", International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.277-281, 2015.
  [5]. S.Sujitha and S. J. Mohana, "Secure Data Storage and Retrieval Using Adaptive Integrity Protocol Model in Cloud Environment", International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.181-184, 2015.
  [6]. Md Kausar Alam, Sharmila Banu K, “An Approach Secret Sharing Algorithm in Cloud Computing Security over Single to Multi Clouds”, International Journal of Scientific and Research Publications, vol. 3, issue 4, pp.23-28, 2013.
  [7]. A. Juels, B.S. Kaliski Jr, "PORs: Proofs of retrievability for large files", CCS `07: Proc. 14th ACM Conf. on Computer and communications security, 2007, pp. 584-597.
  [8]. C. Cachin, I. Keidar, A. Shraer, "Trusting the cloud", ACM SIGACT News, 40, 2009, pp. 81-86.
  [9]. H. Abu-Libdeh, L. Princehouse, H. Weatherspoon, "RACS: a case for cloud storage diversity", SoCC`10: Proc. 1st
  [10]. Rakesh Prasad Sarang and Rajesh Kumar Bunkar, "Study of Services and Privacy Usage in Cloud Computing", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.6, pp.7-12, 2013.
  [11] R. Sood, R. Sharma, "Cloud Security Threats and Issues-A Review", International Journal of Computer Sciences and Engineering, Vol.5, Issue.4, pp.115-119, 2017.
  [12]. F. Rocha and M. Correia, "Lucy in the Sky without Diamonds: Stealing Confidential Data in the Cloud", Proc. 1stIntl. Workshop of Dependability of Clouds, Data Centers and Virtual Computing Environments, China, pp.129-134, 2011.
  

  Citation
  Nitesh Jain, Pradeep Sharma, "A Security Key Management Model for Cloud Environment," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.45-48, 2017