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• Open Access   Article

  A Differential Computational Encryption Modeling Technique on Textual Data

  Logunleko K.B., Logunleko A.M., Odufowora M.O., Gbolagade, K.A.

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.81-86, Feb-2020

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  Abstract
  Pseudo code and encryption algorithm play a vital role in information security. The existence of information technology has drastically transformed ways of communication with one another. This development has tremendously increased the usage and ways of communication leaving behind the security consideration of what is being transmitted through a communication channel. Therefore, this research produces a technical technique of the differential computation of the encryption algorithms. The aim to be considered is the security of the encrypted data against pattern recognition attack. The research will therefore fill the gap of security threat in EB64 pseudo code as compared with the newly proposed EHB64 pseudo code. In addition, this newly concept introduced generates a symmetric key by shuffling the original key with the textual data, thus making the transformation of each character of the data better each time it is shuffled. Thus the final output of the key-based pseudo code will be stronger than the pseudo code of EB64. Therefore, the developed concept secures the data more adequately than the existing one because of the designed pattern and confusion created during the process.

  Key-Words / Index Term
  Confidentiality, Integrity, PEHB64, pseudo code, Key, PEB64

  References
  [1] Isnar S, Andysah P, Sumartono U , and Arpan. “Base64 Character Encoding and Decoding Modeling” International Journal of Recent Trends in Engineering & Research, Volume 02, Issue 12; [ISSN: 2455-1457], pp. 63-68, 2016.
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  [12] Mohan H and Raji R (2011). "Performance Analysis of AES and MARS Encryption Algorithms".International Journal of Computer Science Issues (IJCSI), Vol. 8, issue 4, 2011.
  [13] Logunleko K.B, Logunleko A.M, Akinwunmi O.O. & Lawal O.O. (2019): Security Assurance Framework for Intelligible Information Using a Customized Base64 Encryption Algorithm Proceedings of the 17th iSTEAMS Multidisciplinary Research Nexus Conference, D.S. Adegbenro ICT Polytechnic, Itori-Ewekoro, Ogun State, Nigeria, 21st – 23rd, .Pp 85-93, 2019. www.istream.net - DOI Affix-https://doi.org/10.22624/AIM/iSTEAMS-2019/V17N2P10.

  Citation
  Logunleko K.B., Logunleko A.M., Odufowora M.O., Gbolagade, K.A., "A Differential Computational Encryption Modeling Technique on Textual Data," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.81-86, 2020

• Open Access   Article

  Text Summarization using Latent Semantic Analysis

  T.E. Ramya, N. Maghesh

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.87-92, Feb-2020

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  Abstract
  Text Summarization is an approach of creating compressed version of a given document using natural language processing that can help users to quickly understand the main points of a document. Text summarization aims at getting the most suggestive content in a system of condensed form from an enabled input document while it retains the semantic information of the text to a large extent. It is considered to be an effective way of handling the information which is found to be overloaded. It solves the problem of presenting information in more compact form. There are various approaches to produce well defined summaries and one of the newest methods is Latent Semantic Analysis (LSA). Though the available information about any topic is huge and unimaginable in numbers in recent years. So, there is a need for quick view of those articles to decide relatedness of the article to the user’s need. In this paper, the efficient way of summarizing the text document by involving the combination of the techniques and then evaluating it with the rouge scores was implemented. The Singular value decomposition plays major role in extracting important sentences from the input document. Every sentence is assigned with rank based on its importance in the original document. Sentence selection is done according to the ranks and the summary is generated. The rouge will produce three scores namely, Recall, Precision and the F-score. F-score is considered for evaluating the correctness of a summary. The comparison of three different summaries by reducing input document as 1/2nd, 1/3rd, 1/4th rouge scores and f-score are found to be obtain the effective results towards summarizing the text document.

  Key-Words / Index Term
  Information retrieval; Latent Semantic Analysis (LSA); Singular Value Decomposition (SVD); text summarization component

  References
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  [7] Murray, G., Renals, S. and Carletta, J. 2005. Extractive summarization of meeting recordings. Proceedings of the 9th European Conference on Speech Communication and Technology.
  [8] R. A. García-Hernández and Y. Ledeneva, “Single Extractive Text Summarization Based on a Genetic Algorithm,” In Pattern Recognition, Springer Berlin Heidelberg, 2013, pp. 374-383.
  [9] R. Mihalcea and P. Tarau, “A language independent algorithm for single and multiple document summarizations,” Proceedings of the Second International Joint Conference Natural Language Processing (IJCNLP’05), Korea, pp. 602– 607, 11–13 October 2005.
  [10] Radev D, Blair-Goldstein S, Zang Z. Experiments in single and multi-document summarization using MEAD. In: Proceedings of the document understanding conference 2001.
  [11] Wang R, Dunnion J, Carthy J. Machine learning approach to augmenting news head-line generation. In: Proceedings of the international joint conference on natural language processing 2005.
  [12] Y. Gong and X. Liu, “Generic text summarization using relevance measure and latent semantic analysis,” in: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, USA, pp. 19–25, 9–12 September, 2001.

  Citation
  T.E. Ramya, N. Maghesh, "Text Summarization using Latent Semantic Analysis," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.87-92, 2020

• Open Access   Article

  Reasoning with Certainty Factor for Prediction of Diabetes Disease on Machine Learning Platform

  M.M. Mastoli, U.R. Pol, Rahul D. Patil

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.93-97, Feb-2020

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  Abstract
  Diabetes Mellitus commonly called as diabetes, is one of the common and growing endocrine diseases. AI provides ability to prevent these type of disease at an early stage by predicting the symptoms using several methods. Two areas which may benefit from the application of Machine Learning techniques in the medical field are diagnosis and outcome prediction. Expert systems as a branch of AI can incorporate with machine learning tools, this technology can be used as a solve the problem where there is a shortage of physician in the field of healthcare. The researcher has designed and developed a machine learning model for predicting the diabetes and its types like expert systems. This present reasoning with certainty factor and considered when designed the knowledge base with the patient`s level of belief. The main purpose of this paper is to study certainty factor for prediction of diabetes disease for more accurate prediction and diagnosis of diseases and application of machine learning for heath care systems.

  Key-Words / Index Term
  Artificial intelligence, Machine Learning Model,Certainty Factor, Expert System,Diabetes Mellitus

  References
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  Citation
  M.M. Mastoli, U.R. Pol, Rahul D. Patil, "Reasoning with Certainty Factor for Prediction of Diabetes Disease on Machine Learning Platform," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.93-97, 2020

• Open Access   Article

  Resolution of E-Commerce Market Trend Using Text Mining

  Rajeev Tripathi, Santosh Dwievdi

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.98-104, Feb-2020

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  In the present mechanical complex world a few web based business sites like Amazon, Jabong.com, Myntra.com and Flipkart, and other web based shopping locales shelter gather item audits from clients to determine the fulfillment level on exact items. Information examination are down to earth on item surveys so as to realize useful investigative data as measurements that can bolster individuals working in an association for business examination in settling on very good quality choices so as to look for out the interest of client against their current business rivals. Enormous organizations around the globe understand that online business isn`t simply purchasing and selling over Internet, rather it improves the fitness to contend with different monsters in the market. For this aim information mining in some cases called as information disclosure is utilized. We accomplish this by managing various patterns in the content information like content representation, content mining methods in this way examining the topic on which a book has been created by perusing a couple of html records from a nearby organizer. In Product Ranking System, audits assumes basic job in deciding client satisfaction just as market tendency for that fastidious item, state on the off chance that regarding electronic items to get pertinent information in less time.

  Key-Words / Index Term
  Electronic commerce, Data Mining, Text Mining, Business intelligence and analytics, Big data analytics

  References
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  Citation
  Rajeev Tripathi, Santosh Dwievdi, "Resolution of E-Commerce Market Trend Using Text Mining," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.98-104, 2020

• Open Access   Article

  Deep Learning Techniques: A Review

  Smita D. Raut, S. A. Thorat

  Review Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.105-109, Feb-2020

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  Abstract
  Deep Learning models are effective due to their automatic learning capability. This review paper highlights latest studies regarding the implementation of deep learning models such as deep neural networks, convolutional neural networks and many more for solving different problems of sentiment analysis such as sentiment classification, cross lingual problems, textual and visual analysis and product review analysis.

  Key-Words / Index Term
  Deep Learning, sentiment analysis, recurrent neural network, deep neural network, convolutional neural network, recursive neural network, deep belief network

  References
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  Citation
  Smita D. Raut, S. A. Thorat, "Deep Learning Techniques: A Review," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.105-109, 2020

• Open Access   Article

  An Review on HTTP, TCP Flood, DDOS Attack in Cloud Environment & Their Solutions

  Ashutosh Kumar

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.110-116, Feb-2020

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  Abstract
  Improvement of utilizing cloud computing in the field of Statistics Tools to manage giving available and adaptable capacities to the customers according to demand is starting nowadays. Cloud computing decreased advantages in three levels understood as base, advance and programming to deal with the requesting of assortment of customers. The direct cloud characteristics encase with multi use, region and device self-governance, adaptability, resource pooling and evaluated esteem. As the use of suggestions advantage constructs the more there is security worry considering the way that the more number of IT capacities gave as an organization in cloud, the more the peril in security is concern. From the various Attacks that can deal with the cloud condition, TCP Flood, distributed denial of service Attacks can reason a significant partition in security. For taking care of distributed denial of service Attacks there are various frameworks and systems which rely upon related condition of the condition that can be also delegated expectation, discovery and answer that is extreme impacts. Even more appropriately this leads from avoiding occasion of distributed denial of Service, legitimate responses for perceive when it occurred and explicit procedure to contract with this distinction of officials Attack`s shy of accomplishment outline administrators difficult to reach through customer.

  Key-Words / Index Term
  Domain Name System, Distributed Denial of Service, HTTP, Cloud Service, TCP, IP

  References
  [1] Saman Taghavi Zargar, “A Survey of Defense Mechanisms Against Distributed Denial of Service (DDoS) Flooding Attacks”, IEEE Communications Surveys & Tutorials, published online Feb. 2013.
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  [3] Aqeel Sahi, David Lai, Yan Li, “An Efficient DDoS TCP Flood Attack Detection and Prevention System in a Cloud Environment”, date of publication April 6, 2017, date of current version May 17, 2017. Numberal Object Identifier 10.1109/ACCESS.2017.2688460, 2017 IEEE.
  [4] Qiao Yan and F. Richard Yu, “Distributed Denial of Service Attacks in Software-Defined Networking with Cloud Computing”, Security And Privacy In Emerging Networks, 0163-6804/15/$25.00 © 2015 IEEE.
  [5] Rashmi V. Deshmukh, Kailas K. Devadkar, “Understanding DDoS Attack & Its Effect In Cloud Environment”, Procedia Computer Science 49 ( 2015 ) 202– 210, 2015 Published by Elsevier.
  [6] K.Santhi Sri1, PRSM Lakshmi, “DDoS Attacks, Detection Parameters and Mitigation in Cloud Environment”, Proceedings of National Conference on Recent Advances in Computer Science & Engineering (NCRACSE-2017), Volume 3 | Special Issue 01 | February 2017.
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  [14] S.N.Shiaeles and M. Papadaki, “FHSD: an improved IP spoof detection method for web DDoS Attacks,” Computer Journal, vol. 58, no. 4, pp. 892–903, 2014.
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  [20] S. Y. Nam and S. Djuraev, “Defending HTTP web servers against DDoS Attacks through busy period-based Attack flow detection,” KSII Transactions on Internet and Information Systems, vol. 8, no. 7, pp. 2512–2531, 2014.

  Citation
  Ashutosh Kumar, "An Review on HTTP, TCP Flood, DDOS Attack in Cloud Environment & Their Solutions," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.110-116, 2020

• Open Access   Article

  A 1.8V 10 bits ADC with a 8- stage pipeline and a 2 bits flash ADC with background calibration and digital correction

  Sushil Bakhtar, S. S. Dalu

  Survey Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.117-119, Feb-2020

  Abstract

  Full-Text HTML

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  Citation

  Abstract
  This paper describes 10 bits low power pipeline analog to digital convertor with background calibration and digital correction. The 10-bit pipelined ADC is designed in a 45nm CMOS process consumes 2.350 mW with a 1.8V supply. The proposed ADC achieves low power, high resolution and high speed operation which consists of 8-stage-pipelined low resolution ADCs and a 2-bit flash ADC. Several critical technologies are used to guarantee the resolution and high sampling rate such as 1.5 bits per stage conversion, digital correction logic, folded-cascode amplifiers.

  Key-Words / Index Term
  Pipeline ADC, 10 bit, low power

  References
  [1] Y. H. Chung, “Perturbation-based digital background calibration technique for pipelined ADCs,” In the Proceedings of 2014 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1316–1319, Jun. 2014
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  Citation
  Sushil Bakhtar, S. S. Dalu, "A 1.8V 10 bits ADC with a 8- stage pipeline and a 2 bits flash ADC with background calibration and digital correction," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.117-119, 2020

• Open Access   Article

  Improving Database Security in Cloud Computing

  Ashutosh Kumar

  Survey Paper | Journal-Paper (IJSRCSE)

  Vol.8 , Issue.1 , pp.120-122, Feb-2020

  Abstract

  Full-Text HTML

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  Citation

  Abstract
  Cloud computing is an age that advances different configurable assets wherein the records is saved and directed in a decentralized way. Regardless, considering the way that the information is out of the proprietor`s control, concerns show up as for information characterization. Encryption systems have in the past been proposed to outfit customers with mystery to the extent re-appropriated limit; in any case, stores of these encryption counts are vulnerable, enabling records security to be constrained unquestionably by a course of action of rules. We bolster a mix of encryption computations and a distribution system to impact database confidentiality. This arrangement separates a database over the cloud in a general sense subject to the level of prosperity gave by the encryption count applied. We survey the benefits of our arrangement with other present counts and assurance that our arrangement gives a noticeably agreeable system that offers customers with data confidentiality and adequate execution.

  Key-Words / Index Term
  Cloud Computing, DD-PLAC (Distributed Database-Proxy Less Architecture), encryption, data privacy, decryption algorithm

  References
  [1] Luca Ferretti, Michele Colajaani, and Micro Marchetti, “ Distributed, Concurrent, and Independent Access to Distributed Database,” 2015.
  [2] Amjad Alsirhani, Peter Bodorik, Srinivas Sampalli, “Improving Database Security in Cloud Computing by Fragmentation of Data,” 2017.
  [3] Sajjan R.S., Vijay Ghorpade, Vishvajit Dalimbkar, “A Survey Paper on Data security in Cloud Computing,” 2016.
  [4] Parneet Kaur and Sachin Majithia, "Various Aspects for Data Migration in Cloud Computing and Related Reviews," 2014.
  [5] A. Hudic, S. Islam, P. Kieseberg, S. Rennert, and E. R. Weippl, “Data Confidentiality using Fragmentation in Cloud Computing,” 2013.
  [6] J. Daemen, “The design of Rijndael : AES - the Advanced Encryption Standard with 17 Tables,” 2002.
  [7] Tim Mather, Subra Kumaraswamy, and Shahed Latif ”Cloud Security and Privacy” Published by O’Reilly Media, Inc.
  [8] V. Ganapathy, D. Thomas, T. Feder, H. Garcia-Molina, and R. Motawani, “Distributing Data for Secure Database Services,” 2011.
  [9] Danie J. Abadi, “Data Management in the Cloud:Limitations and Opportunities,” 2009.

  Citation
  Ashutosh Kumar, "Improving Database Security in Cloud Computing," International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.120-122, 2020