IOSR Journal of Computer Engineering (IOSR-JCE)

May. - Jun. 2017 Volume 19 - Issue 3

Version 1 Version 2 Version 3 Version 4 Version 5 Version 6

Paper Type : Research Paper
Title : E-payments: Go digital, go cashless
Country : India
Authors : Jaideep Inder Kaur
: 10.9790/0661-1903060104     logo

Abstract: Today's India is now completely different from earlier India. Now a day's India become cashless due to biggest decision ever taken of demonetization. Demonetization is a process in which .Cashless India is famous in current days which makes easier people's life. People can easily do e-payments everywhere 24*7. People don't need cash in their hands even Indian government also promote e-payments infrastructure. There is no need to carry even credit cards or debit cards when you have e-wallet. Government promotes UPI (Unified Payment Interface) and Paytm (pay through mobile)..........

Keyword: Overview, how they works, Benefits and weakness.

[1]. www.wikipedia.com
[2]. www.google.com
[3]. Dr. Karminder Ghuman1, CS Shruti Srivastava2, "Recharging: the Right Way??"
[4]. Vijay Shekhar Sharma, "The story behind Paytm's marketing"
[5]. Alpesh shah, "Digital payments 2020"


Paper Type : Research Paper
Title : Pairing High School Teachers with Historically Black College &University (HBCU) Computer Science Students to Teach Advanced Placement Computer Science Principles
Country : India
Authors : Kinnis Gosha Ph. D || Nathan Harris
: 10.9790/0661-1903060509     logo

Abstract: Reports have shown the lack of African Americans who take and pass the Advanced Placement (AP) Computer Science (CS) course. Many times, African American students are enrolled in schools that do not offer computer science courses like AP Computer Science. Interventions are needed nationally to provide African American students with equal opportunity to learn computer science. The goal of this research paper is design a study that will evaluate the effectiveness of a program to train high school teachers to teach Advance Placement Computer Science Principals using HBCU students majoring in computer science. Additionally, this program will be evaluated by its effectiveness to train teachers, its effect on the HBCU students who instruct the teachers and it feasibility to be scaled to HBCUs around the nation.

[1]. (2016). Retrieved from MIT App Inventor: http://appinventor.mit.edu/explore/hour-of-code.html
[2]. Advances in AP. (2016, December). Retrieved from Collegeboard.org: https://advancesinap.collegeboard.org/stem/computer-science-principles
[3]. AP Program Participation and Performance Data 2016. (2017). Retrieved from College Board: https://research.collegeboard.org/programs/ap/data/participation/ap-2016
[4]. Committee, K.-1. C. (2016). K-12 Computer Science Framework. ACM Digital Library, 52-157.
[5]. (2015), Computing Research News May. "Continued Booming Undergraduate CS Enrollment; Doctoral Degree Production Dips Slightly." 2015 Taulbee Survey 28.5 (2015): n. pag. The Taulbee Survey. Computing Research Association.


Paper Type : Research Paper
Title : A Competitive Intelligence framework to support decision-making based on Rough Set Theory
Country : Morocco
Authors : Fatima-Zzahra Cheffah || Mostafa Hanoune
: 10.9790/0661-1903061520    logo

Abstract: Given the increasing complexity of the economic context, it is important for each company to master information and build a robust strategic planning process. Competitive Intelligence (CI) is important for companies to manage their information. CI identifies opportunities and determinants of success, anticipates threats and prevents risks. CI becomes an imperative for any company wishing to sustain its growth and innovation sustainably. In addition, decision-makers have a key role to play when making decisions, some of which can have a significant impact and therefore justify the effort to reflect and deliberate on possible options before making a decision. Strategic decisions........

Keywords: Competitive Intelligence, Decision-making, Strategic Information System, Rough set theory.

[1] Kislin, Philippe. 2007. Modélisation du problème informationnel du veilleur dans la démarche d'intelligence économique. doctoral diss. in information and communication sciences. Nancy 2 University, November 2007, pp 16.
[2] Z. Pawlak. Rough sets. International journal of computer and information sciences, pp. 341-356, 1982.
[3] Z. Pawlak, J. Grzymala-Busse, R. Slowinski, W. Ziarko, Rough Sets, Magazine Communications, 1995;Vol(38) Issue 11, 88-95
[4] R. Slowinski, C. Zopounidis, Application of the rough set approach to evaluation of bankruptcy risk. International Journal of Intelligent Systems in Accounting, Finance, and Management, 1995; 4(1), 27–41.
[5] Rong-Ho Lin, Yao-Tien Wang, Chih-Hung Wu, Kuan-Wei Huang, Chun-Ling Chuang Corrigendum "Developing a business failure prediction model via RST, GRA and CBR" [Experts Systems with Applications 36 (2P1) (2009) 1593–1600].


Paper Type : Research Paper
Title : A Compressed Sensing Method for Wireless Sensor Networks with Evolution Model Based on KH-SVM
Country : China
Authors : Peng Liu
: 10.9790/0661-1903062126     logo

Abstract: Wireless sensor networks are able to provide crucial and real time information in many scenarios of crisis response and management. Sensor node localization is one of research hotspots in the applications of wireless sensor networks (WSNs) field. A localization algorithm based on improved Support Vector Machine (SVM) for WSNs is proposed in this paper. SVM classification accuracy is the key to the localization accuracy. The selection of parameters is the important factor that influences the performance of SVM. Therefore, this paper proposes a parameter optimization algorithm.........

Keywords: Compressed Sensing, Wireless Sensor Networks, Evolution Model, SVM,Krill-herd.

[1] Werner-Allen G, Lorincz K and Ruiz M, Deploying a wireless sensor network on an active volcano.Internet Computing, 10(2),2006,18-25.
[2] Tuna G, Gungor V C and Gulez K,An autonomous wireless sensor network deployment system using mobile robots for human existence detection in case of disasters. Ad Hoc Networks, 13(4),2014, 54-68.
[3] Jelicic V, Magno M and Brunelli D,Benefits of wake-up radio in energy-efficient multimodal surveillance wireless sensor network. Sensors Journal, 14(9),2014, 3210-3220.
[4] Tillmann A M and Pfetsch M E. The Computational complexity of the restricted isometry property, the nullspace property, and related concepts in compressed sensing. IEEE Transactions on Information Theory, 60(2),2014, 1248-1259.
[5] Donoho D L, Elad M and Temlyakov V N. Stable recovery of sparse overcomplete representations in the presence of noise.IEEE Transactions on Information Theory,52(1),2006,6-18.


Paper Type : Research Paper
Title : Improved Students' Social Media Content Analysis Using Machine Learning Algorithm
Country : India
Authors : Bushra SarwatAra Syed || Harshali Patil || Mohammad Atique
: 10.9790/0661-1903062732     logo

Abstract: Sentimental Analysis has become most profound research areas for prediction and classification. Student's discussion on social media contains sentiwords that are a word or set of words expressing some thought or judgment or idea about something which provides us with some idea about their experiences in learning and views about the particular field [5]. Data from social media site would be raw and difficult to understand but by analyzing it through supervised learning approach we can find out the exact views of students. In this Paper MultiLabel Text Classification is done with Label Correlational Model will give us desired result which wasn't possible with conventional Single Label Classification. The proposed work is to extract the features of text in the form of labels and Correlational Model can find the relation between the labels and understanding among Labels.

Keywords: Correlational model, Machine Learning, Multi Label Classification, Multinomial Naïve Bayes, sentimental Analysis

[1]. Han van der Veen "Composing a more relevant and complete twitter dataset" Master Thesis [online].Available: http://essay.utwente.nl/67800/1/vanderveen_MA_EEMCS.pdf
[2]. Andrea Esuli∗ and Fabrizio Sebastiani "SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining"[online]. Available: http://nmis.isti.cnr.it/sebastiani/Publications/LREC06.pdf
[3]. Prof. Dan Jurafsky "Text Classification and Naïve Bayes"[online]. Available: https://web.stanford.edu/class/cs124/lec/naivebayes.pdf
[4]. Andrew McCallum and Kamal Nigam" A Comparison of Event Models for Naive Bayes Text Classification"[online]. Available: http://www.cs.cmu.edu/~knigam/papers/multinomial-aaaiws98.pdf
[5]. "sentiword public"[online].Available: https://www.npmjs.com/package/sentiword


Paper Type : Research Paper
Title : Speech Compression Using Wavelet Transform
Country : India
Authors : Harshalata Petkar
: 10.9790/0661-1903063341     logo

Abstract: This paper applies wavelet analysis to speech compression. A mother or basis wavelet is first chosen for the compression. The signal is then decomposed to a set of scaled and translated versions of the mother wavelet. The resulting wavelet coefficients that are insignificant or close to zero are truncated achieving signal compression. Analysis of the compression process was performed by comparing the compressed-decompressed signal against the original. This was conducted to determine the effect of the choice of mother wavelet on the speech compression. The results however showed that regardless of bases wavelet used the compression ratio is relatively close to one another.

Keywords: Compression, Filter Bank, Lossless &Lossy Compression, Wavelet Transform, 1-D DWT

[1]. Graps, A. "An Introduction to Wavelets", 1997. http://www.amara.com/current/wavelet.html
[2]. Polikar, R. "The Wavelet Tutorial" 1996. http://engineering.rowan.edu/~polikar/WAVELETS/WTpart4.html
[3]. Misiti, M., Misiti, Y., Oppenheim G. and Poggi, J. "Wavelet Toolbox User's Guide", Mathworks, 1997.
[4]. Strang, G. and Nguyen, T. "Wavelets and Filter Banks", Weslley-Cambridge Press, USA, 1996.
[5]. Bomers, F. "Wavelets in real time digital audio processing", 2000 http://www.daimi.au.dk/~fungus/DSP/Litteratur/Wavelets


Paper Type : Research Paper
Title : Low Power Wireless Sensor Networks Algorithm: EASRP
Country : India
Authors : Smt. Sheetalrani R Kawale || Prof. G. Mahadevan || Samartha G.
: 10.9790/0661-1903064246     logo

Abstract: Wireless Sensor Networks comprises of a huge number of communicating devices called as, sensor node. These nodes are powered by a limited battery source. Moreover, the sensor nodes will be instigated in harsh and hostile environment, after which, battery replacement become very difficult. Hence energy conservation and power saving is very crucial. The LEACH provides good energy conservation, but there is still scope for some improvement, which is addressed by the proposed ENERGY AWARE SECURE ROUTING PROTOCOL (EASRP) scheme.

Keywords: Wireless Sensor Networks, Clustering, AES, DES, Clusters, Network Lifetime, LEACH, Encryption.

[1]. W. Su Y. Sankarasubramaniam E. Cayirci Akyildiz, I.F. A survey on sensor networks. IEEE Communications Magazine, pages 102{114, 2002.
[2]. Kumar.S.P. Chee-Yee Chong. Sensor networks: Evolution, opportunities, and challenges. Proc IEEE, August 2003.
[3]. Ismail H. Kasimoglui Ian .F. Akyildiz. Wireless sensor and actor :research challenges. (Elsevier) Journal, 2(38):351{367, 2004.
[4]. Jonathan Jen-Rong Chen Prasan Kumar Sahoo and Ping-Tai Sun. E±cient security mechanisms for the distributed wireless sensor networks. Proceedings of the IEEE Third International Conference on Information Technology and Applications (ICITA'05), pages 0{7695{2316{1, 2005.
[5]. Sajid Hussain and Abdul W. Matin Jodrey. Energy e±cient hierarchical cluster-based routing for wireless sensor networks. Technical Report - TR- 2005-011, 2005. 073720m@acadiau.ca.


Paper Type : Review paper
Title : A Survey: Searching Techniques
Country : India
Authors : Miss Mangala S. Teli || Asst. Prof. Priti S. Subramanium
: 10.9790/0661-1903064748     logo

Abstract: In day to day life as we are using internet mostly for to search every one want answer within short time. Any user who doesn't know how to search can get result by simply typing related words in search engine. They even know which technics are used to search similar data on web. There are many searching technics like Instant search, Type-Ahead Search, Text Proximity Search, Fuzzy Keyword Search Auto-Completion and many more are also available. This paper is about how all mentioned technics works to retrieves results quick and accurate.

Keywords: Instant search, Type-Ahead Search, Text Proximity Search, Fuzzy Keyword Search, Auto-Completion.

[1]. Cetindil, J. Esmaelnezhad, C. Li, and D. Newman, "Analysis of instant search query logs," in WebDB, 2012, pp. 7–12.
[2]. G. Li, J. Wang, C. Li, and J. Feng, "Supporting efficient top-k queries in type-ahead search," in SIGIR, 2012, pp. 355–364.
[3]. R. Schenkel, A. Broschart, S. won Hwang, M. Theobald, and G. Weikum, "Efficient text proximity search," in SPIRE, 2007, pp. 287–299.
[4]. A. Nandi and H. V. Jagadish, "Effective phrase prediction," in VLDB, 2007, pp. 219–230.
[5]. S. Ji, G. Li, C. Li, and J. Feng, "Efficient interactive fuzzy keyword search," in WWW, 2009, pp. 371–380..


Paper Type : Research Paper
Title : Intrusion Detection and Defense Implementation (IDDI) in Cuckoo Hashing
Country : India
Authors : D.Seethalakshmi || Dr.G.M.Nasira
: 10.9790/0661-1903064952     logo

Abstract: The cuckoo hashing methodology completely avoids hash collisions. An insertion of a new item causes a failure and an endless loop when there are collisions in all probed positions till achieving the timeout status. To interrupt the countless loops, an intuitive manner is to carry out a complete rehash if this uncommon incident takes place. In practice, the high priced overhead of acting a rehashing operation can be dramatically decreased by using taking benefit of a very small extra regular-size space. In our proposed paper hashing involve collisions in which the stored buckets with one item will be reduced to probe the hash collision and query about the buckets. The enumerator that allocates each hash bucket will reduce the endless loops. As an accession we include intrusion detection and defense implementation........

Keywords: Cloud computing Data, cuckoo hashing, Intrusion Detection and Defense Implementation (IDDI), enumerator

[1] W.-C. Chen and J. S. Vitter, "Analysis of new variants of coalesced hashing," Proc. TODS, vol. 9, no. 4, pp. 616–645, 1984.
[2] J. S. Vitter and W.-C. Chen, "The design and analysis of coalesced hashing". Oxford University Press, Inc., 1987.
[3] R. Pagh and F. F. Rodler, Cuckoo hashing. Springer Berlin Heidelberg, 2001.
[4] M. Zukowski, S. H´eman, and P. Boncz, "Architecture-conscious hashing," workshop on Data management on new hardware, 2006.
[5] M. M. Michael, "High performance dynamic lock-free hash tables and list-based sets," Parallel algorithms and architectures, pp. 73–82, 2002.


Paper Type : Research Paper
Title : A New Approach for the Betterment in Energy-Aware VM Scheduling
Country : India
Authors : Alekhya Orugonda || Dr. V. Kiran Kumar
: 10.9790/0661-1903065360     logo

Abstract: Cloud Computing is dealing with an growing interest nowadays as it is present in many purchaser home equipment through advertising the illusion of countless resources in the direction of its clients. Nevertheless it increases intense problems with electricity intake: the better degrees of nice and availability require irrational strength expenses. A digital machine scheduling technique for decreasing strength consumption of IaaS datacenters is required. We need to design a CloudSim-based simulation environment, and implemented actual-international lines for the experiments. We need to show that enormous savings can be accomplished in strength intake with brand new proposed algorithms. Cloud computing is a digital pool of resources which might be supplied to customers through Internet.........

Keywords: Virtual machines, Scheduling, and Migration, Energy aware

[1]. Anthony T.Velte, Toby J.Velte, Robert Elsenpeter, "Cloud Computing Practical Approach". Xun Xu. "From Cloud Computing to cloud".
[2]. Jeongseob Ahn Changdae Kim, Jaeung Han, Young-ri Choit, And Jaehyuk Huh, "Dynamic Virtual Machine Scheduling In clouds For Architectural Shared Resources", 2011 IEEE manufacturing",2011 Elesevier Ltd.
[3]. Zheng Hu, Kaijun Wu, Jinsong Huang,"An Utility-Based Job Scheduling Algorithm for Current Computing Cloud Considering Reliability Factor",2012 IEEE.
[4]. Masaya Yamada Yuki Watanabe, Saneyasu Yamaguchi,"AN Integrated 1/0 Analyzing System for Virtualized Environment, 2011.
[5]. AshutoshIngole ,SumitChavan , UtkarshPawde "An Optimized Algorithm for Task Scheduling based on Activity based Costing in Cloud Computing", 2nd National Conference on Information and Communication Technology (NCICT) 2011 Proceedings published in International Journal of Computer Applications® (IJCA).


Paper Type : Research Paper
Title : GA Analysis of Switchability of Ferrite Rectangular Patch Antenna
Country : India
Authors : Naveen Kumar Saxena || Raj Kumar Verma || P.K.S. Pourush || Nitendar Kumar
: 10.9790/0661-1903066165     logo

Abstract: The application of Genetic Algorithm (GA) to analyze / optimize the switching behavior of magnetically biased switchable microstrip antenna, fabricated on ferrite substrate, is reported. In this work, GA has been applied to optimize extraordinary wave propagation constant (Ke) which is mainly responsible for the switchability of antenna. The wave propagation constant becomes zero or negative under proper magnetic biasing which resist the antenna as radiator without a mechanical maneuvering. The fitness functions for the GA program have been developed using mathematical formulation based on nonreciprocal approach of ferrite substrate under external magnetic field. The computed results are in good agreement with the results obtained experimentally and trained artificial neural network analysis. In this ANN training Radial Basis Function (RBF) networks is used. All programming related to genetic algorithm and ANN analysis performed by MatLab 7.1........

Keywords: Microstrip rectangular patch antenna, genetic algorithm, fitness function, ferrite substrate, magnetic biasing, ANN analysis training, etc.

[1] Haupt R. L., (1995), "An Introduction to Genetic Algorithms for Electromagnetics", IEEE Trans. Antennas Propagation Magazine, Vol. 37, pp. 7-15.
[2] Chattoraj N. and Roy J. S., (2006), "The Optimization of Gain of Patch Antennas Using Genetic Algorithm", ACTA Tech CSAV Journal.
[3] Villegas F. J., Cwik T., Rahamat-Samii Y. and Manteghi M., (2004), "A Parallel Electromagnetic Genetic- Algorithm Optimization (EGO) Application for Patch Antenna Design", IEEE Trans. Antennas Propagation, Vol. 52, pp. 2424-2435.
[4] Wyant A. M., (2007), "Genetic Algorithm Optimization Applied to Planar and Wire Antennas", Thesis submitted to Rochester Institute of Technology, Rochester, New York.
[5] Akdagli A. and Guney K., (2000), "Effective Patch Radius Expression Obtained Using a Genetic Algorithm for the Resonant Frequency of Electrically Thin and Thick Circular Microstrip Antennas", IEE Proc. Microwave and Antennas, Propagation, Vol. 147, No.2, pp.-156-159.


Paper Type : Research Paper
Title : Document Clustering Using Divisive Hierarchical Bisecting Min Max Clustering Algorithm
Country : India
Authors : Prof. Vaishnavi Kamat || Prof. Terence Johnson || Rudresh Chodankar || Rama Harmalkar || Gauresh Naik || Prajyot Narulkar
: 10.9790/0661-1903066670     logo

Abstract: Document clustering is a process of grouping data object having similar properties. Bisecting k-means is a top down clustering approach wherein all the documents are considered as single cluster. That cluster is then partitioned into two sub-clusters using k-means clustering algorithm, so k is considered as 2. Sum of square errors (SSE) of both the clusters are calculated. The cluster which has SSE greater, that cluster is split. This process is repeated until the desired number of clusters are obtained. Divisive Hierarchical Bisecting Min–Max Clustering Algorithm is similar to bisecting k-means clustering algorithm with a slight modification. To obtain a certain number of clusters. The main cluster is divided into two clusters using Min-Max algorithm. A cluster is selected in order to split it furthers........

Keywords: Agglomerative clustering, Bisecting K-means, Bisecting min-max clustering, Clustering, Hierarchical clustering..

[1]. Michael Steinbach George Karypis Vipin Kumar, "A Comparison of Document Clustering Techniques" Department of Computer Science / Army HPC Research Center, University of Minnesota.
[2]. Nikita P. Katariya, Prof. M. S. Chaudhari(2015), "Bisecting K-means Algorithm for Text Clustering", International Journal of Advanced Research in Computer Science and Software Engineering, ISSN: 2277 128X, Volume 5, Issue 2 February (2015)
[3]. Terence Johnson and Santosh Kumar Singh(2016), "Divisive Hierarchical Bisecting Min–Max Clustering Algorithm", Advances in Intelligent Systems and Computing Series Volume – 468, Series ISSN 2194-5357,Online ISBN 978-981-10-1675-2, DOI 10.1007/978-981-10-1675-2_57, 2016 International Conference on Data Engineering and Communication Technology-ICDECT 2016, March 10-11, lAVASA Pune, Springer Singapore, copyright 2017, copyright holder Springer Science + Business Media Singapore, pp 576-592. Clustering Algorithm"
[4]. Dr. S. Vijayarani, Ms. J. Ilamathi, Ms. Nithya3 Assistant Professor, M. Phil Research Scholar, " Preprocessing Techniques for Text Mining - An Overview ", Dr.S.Vijayarani et al , International Journal of Computer Science & Communication Networks, ISSN:2249-5789 Vol 5(1),7-16
[5]. Giridhar N S, Assistant Professor, 2Prema K.V, Professor, 3N .V Subba Reddy, Professor, Department of CSE, M.I.T., Manipal University, Manipal, Karnataka, India."A Prospective Study of Stemming Algorithms for Web Text Mining"


Paper Type : Research Paper
Title : Cryptanalysis and Further Improvement of a Certificate less Aggregate Signature Scheme
Country : India
Authors : Pankaj Kumar || Vishnu Sharma || Vinod Kumar || Ankush Kumar
: 10.9790/0661-1903067175     logo

Abstract: Certificateless aggregate signature reduces n signatures on n distinct messages from n distinct users into a compact single length signature. Recently Deng et al proposed CLAS Scheme which is an improvement of Hou et al scheme and claims that their scheme is secure against type I type II adversary but unfortunately it is found insecure by against the "Honest but Curious" attack by adversary II. In this paper, we demonstrate that Deng et al proposed CLAS scheme is insecure against type II adversary and suggest an improved CLAS scheme.

Keywords: Keywords: Digital Signature, Cryptography, Cryptanalysis, Security attacks

[1]. D. Boneh, C. Gentry, B. Lynn, H. Shacham, "Aggregate and Verifiably Encrypted Signatures from Bilinear Maps", E. Biham (Ed.),
EUROCRYPT 2003, LNCS 2656, Springer-Verlag, Warsaw, Poland, 2003, pp. 416–432.
[2]. Al-Riyami, S., Paterson, K. "Certificateless Public Key Cryptography", Asiacrypt' 03, LNCS 2894, Springer-Verlag. (2003) pp.
452-473.
[3]. A. Shamir, "Identity Based Cryptosystems and Signature Schemes",G.R. Blakley, D. Chaum (Eds.), Crypto'84, LNCS 196,
Springer-Verlag, Santa Barbara, California, USA, 1984, pp. 47–53.
[4]. Jiang Deng, Chunxiang Xu, Huai Wu, Guangyuan Yang, "An Improved Certificateless Aggregate Signature", 2014 IEEE
Internatational Conference on Computer and Information Technology pp 919-922.
[5]. Xinyi Huang, Yi Mu, Willy Susilo, Duncan S. Wong, Wei Wu, "Certificateless Signatures: New Scheme and Security Models" The
Computer Journal, Vol. 55 No.4, 2012 pp 457-474..


Paper Type : Research Paper
Title : Real Time Video Surveillance System
Country : India.
Authors : Sangeeta Oswa || CV Ritu Ramesh
: 10.9790/0661-1903067679     logo

Abstract: The embedded system and RTOS are reaching beyond the norms of innovations, the prospects of security and demanding protection against various threats has been widened immensely. This paper represents the most integrated and customized advanced Android based Real time Video Surveillance System in order to secure and protect what matter the most to the user. The main objective of this system is to monitor the area where the webcam is set up. The user will receive live notification if a motion is detected, if any unusual activity is identified, the user will be directly redirected to the emergency service number. The notification is done through Google Cloud Messaging. Our research focuses on the entire processing of the system

Keywords: Webcam, Android, Real time monitoring, Surveillance, Cloud Storage, Alert notification

[1]. WCSA440C Home Page. http://www.webcamsoft .com/tw/wcsa440c.html; 2009.

[2]. Wen-Tsuen Chen, Po-Yu Chen, Wei-Shun Lee and Chi-Fu Huang, 2014. Design and Implementation of Real Time Video Surveillance System with Wireless Sensor Networks, IEEE

[3]. https://msdn.microsoft.com/en-us/library/gg145045(v=vs.110).aspx

[4]. https://www.sitepoint.com/database-as-a-service-mysql-in-the-cloud/

[5]. Heming Pang, Linying Jiang, Liu Yang, Kun Yue. Research of Android Smart Phone Surveillance System. 201O International Conference On Computer Design And Appliations (ICCDA 2010). V2 373-376.


Paper Type : Research Paper
Title : Security Issues in Hadoop Associated With Big Data
Country : India.
Authors : Dr. M Praveen Kumar || Sampurnima Pattem
: 10.9790/0661-1903068085     logo

Abstract: Due to the advent of new technologies, devices, Now-a-days the amount of data produced by mankind is growing rapidly every year. Big data includes huge volume, high velocity, and extensible variety of data. The Big data is in the form of Structured data (Ex: Relational data), unstructured data (Ex: Text, PDF, Word) and Semi Structured data (Ex: XML data). It is really a tedious task to process such data through a traditional database server. Google solved this problem using an algorithm called Map Reduce, used in the technology Hadoop. In this paper we discuss some security issues in Hadoop associated with Big data. Big data applications are very much useful to Organizations, all type of Companies may be small or large scale companies and to the Industries etc.

Keywords: Big data, Hadoop, Map Reduce, HDFS (Hadoop Distributed File System).

[1]. Prof. Dr. Philippe Cudré-Mauroux, "An Introduction to BIG DATA", June 6, 2013
[2]. Fremont Rider, "The future of the Research Library",
[3]. http://www.gartner.com/newsroom/id/2 848718, STAMFORD, Conn., September 17, 2014.
[4]. "Leveraging Massively parallel Processing in an Oracle Environment for White Paper, November Big Data", an Oracle.
[5]. Jeffrey Dean and Sanjay Ghemawat,"Map Reduce: Simplified Data.
[6]. Datguise protect, http://www.dataguise.com/?q=dataguise- dgsecure-platform..