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The possibility of introduction of a change in software cannot be denied as the request for upgrades and improved functionality keeps coming on. Implementing these changes require a systematic Change Impact Analysis (CIA) which is a step by step process under software maintenance. However, the most difficult phase in this systematic CIA process is the identification of an initial location of initiating the proposed change. Various techniques have been proposed to identify this initial location which comes under Feature Location Techniques. These techniques are aimed at finding areas in the software code and other software artifacts that implement a feature. The paper attempts to organize and structure existing work in the field of feature location by presenting a literature survey of recent feature location techniques whereby the techniques have been categorized according to the methodology followed, the tools proposed and their impact. The paper also discusses open issues and defines future directions in the field of feature location.

change impact analysis, feature location, software maintenance,concept location

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Ankit Dhamija, Sunil Sikka, "A Systematic Review of Feature Location Techniques under Software Change Impact Analysis," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.184-192, 2019.

In the era of internet-connected devices, the amount of unstructured data is multiplying in many different types of file formats. In particular, a great deal of knowledge is hidden in the vast amounts of textual data such as emails, blogs, tweets, and log files. The primary issue in this kind of textual data is to classify its content into predefined classes expeditiously in real time. Hence this research paper investigates the deployment of the state-of-the-art Machine Learning (ML) algorithms such as decision tree, k-nearest neighbourhood, Rocchio, ridge, passive-aggressive, multinomial naïve Bayes, Bernoulli naïve Bayes, support vector machine, artificial neural network including perceptron, stochastic gradient descent, back-propagation neural network in automatic classification of text documents on benchmark datasets such as 20Newsgroup, BBC news, BBC sports and IMDB. Finally, the performance of all the aforementioned built-in classifiers is compared and empirically evaluated using the well-defined metrics such as accuracy, error rate, precision, recall, f-measure and Kappa statistics.

Text mining, Machine learning, Documents classification, Information Retrieval, Comparative study

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Bichitrananda Behera, G. Kumaravelan, "Towards the Deployment of Machine Learning Solutions for Document Classification," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.193-201, 2019.

An image encryption is a traditional way to hide original image to an adversary in the case of secure image transmission. In this regard, the Artificial Neural Network (ANN) can be used in digital communication systems (digital image transmission) to achieve a secure and reliable data transmission. However, we have designed a new scheme that encrypts a color image, which can be used in secure image transmission. This proposed scheme is divided into three steps, (a) we subdivide the color image into R (red), G (green) and B (blue) factors, and using the chaotic map, we randomly shuffle these RGB factors to get first encrypted image; (b) we process the first encrypted image through the single-layer artificial neural network to get the second encrypted image; and (c) pixels of the second encrypted image are shuffled using exclusive-or (XOR) operation to get the final encrypted image, which can be transmitted over insecure channel. Furthermore, we have examined the proposed scheme on some standard color images each of size 512 × 512. The several security study and experimental outcomes indicate that the proposed scheme can protect from several statistical attacks like Plaintext Attack, Cipher text Attacks, Brute Force Attack, and Birthday Attack etc.

Encryption, RGB buffer shuffle, Artificial Neural Network, Attacks

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[15] C. Li, S. Li, M. Asim, J. Nunez, G. Alvarez and G. Chen “On the security defects of an image encryption scheme”, Science Direct, Vol. 27, pp. 1371-1381, 2009.
[16] W. Chen and X. Chen “Optical color image encryption based on an asymmetric cryptosystem in the Fresnel domain”, Science Direct, Vol. 284, pp. 3913-3917, 2011.
[17] N. R. Kumar , G. Manikandan , R. B. Krishnan , N. R. Raajan and N. Sairam “A reversible visual cryptography technique for color images using Galois field arithmetic”, Biomedical Research, Vol. 28 (5), pp. 2036-2039, 2017.
[18] S. N. Lagmiri , N. E. Alami and J. E. Alami “Color and gray images encryption algorithm using chaotic systems of different dimensions ”, IJC-SNS International Journal of Computer Science and Network Security, Vol. 18, pp. 1, 2018.
[19] S. Banerjee, L. Rondoni, S. Mukhopadhyay and A. P. Misra “Synchronization of spatiotemporal semiconductor lasers and its application in color image encryption ”, Optics Communications, Vol. 284, pp. 2278-2291, 2011.
[20] M. Joshi, C. Shakher and K. Singh “Fractional Fourier transform based image multiplexing and encryption technique for four-color images using input images as keys ”, Optics Communications, Vol. 283, pp. 2496-2505, 2001.
[21] Y. Tang, Z. Wanga and J. A. Fang, “Image encryption using chaotic coupled map lattices with time-varying delays”, Commun Nonlinear Sci Nu-mer Simulat, Vol. 15, pp. 2456-2468, 2010.
[22] L. Hongjun and W. Xingyuan, “Color image encryption based on one-time keys and robust chaotic maps”, Computers and Mathematics with Applications, Vol. 59, pp. 3320-3327, 2010.
[23] W. Chen and X. Chen, “Optical color image encryption based on an asymmetric cryptosystem in the Fresnel domain”, Optics Communications, Vol. 284, pp. 3913-3917, 2011.
[24] Jyotsna, A. Papola, “An Image Encryption Using Chaos Algorithm Based on GLCM and PCA”, International Journal of Computer Sciences and Engineering, Vol. 6(3), pp. 76-81, 2018.
[25] M. Dasgupta, J. K. Mandal, “Bit-plane Oriented Image Encryption through Prime-Nonprime based Positional Substitution (BPIEPNPS)”, International Journal of Computer Sciences and Engineering, Vol. 4(6), pp. 65-70, 2016.

Dipankar Dey, Soumen Paul, "Color Image Encryption using Single Layer Artificial Neural Network and Buffer Shuffling," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.202-211, 2019.

Electricity is the need of every day’s life both at home and on industry. But sometimes it causes very dangerous incident called an arc flash hazard in industry which damages the equipment and harm the workers to a greater extent. For knowing the level of arc flash hazard and providing better protection to working personnel, analysis of it is very important. This paper presents an arc flash analysis of medium voltage level power system based on standard IEEE 1584. IEEE 30 bus network is considered for analysis purpose. Electrical Transient and Analysis Program (ETAP) Software is used for Arc Flash Hazard (AFH) analysis of medium voltage level system. Comparative analysis is carried out based on result of software and hand calculation. These results are then used to determine Personnel Protective Equipment (PPE) to protect personnel and Labels are also generated for equipment to alert operators about hazard level.

AFH analysis, PPE, FPB, AFIE, ETAP

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S.N. Chauhan, S.M. Pujara, P.K. Makhijani, C.D. Kotwal, "Arc Flash Analysis of Medium Voltage Level Power System using ETAP," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.212-219, 2019.

Web server normally produces log files. A weblog is a group of connected web pages that consists of a log or daily record of information, particular fields or views which is altered, every now and then, by owner of site, other websites or by website users. This is used to convert the unstructured data of web server log which will be coming from Apache flume into structured format using Pig. An enterprise weblog analysis system based on Hadoop architecture with Hadoop Distributed File System (HDFS), Hadoop MapReduce Software Framework and Pig Latin Language aids the business decision-making process of the system administrators and helps them to collect and identify the potential value which is hidden within such huge data generated by the websites. Such a weblog analysis includes the analysis of an Internet site’s entry log as well as provides information about the amount of visitors, days of week and rush hours, views, hits, very often accessed pages, application server traffic trends, performance reports at varying intervals and statistical reports which indicate the performance of program. Web log file is a log file created and stored by a web server automatically. Analyzing such web server access logs files will provide us various insights about website usage. Due to high usage of web, the log files are growing at much faster rate with increase in size. Processing this fast growing log files using relational database technology has been a challenging task these days. Hadoop runs the big data where a massive quantity of information is processed via cluster of commodity hardware. In this paper we present the methodology used in pre-processing of high volume web log files, studying the statics of website and learning the user behaviour using the architecture of Hadoop MapReduce framework, Hadoop Distributed File System, and HiveQL query language Pig. 

HDFS, Apache Flume, Pig , Hbase, web log server

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A.S. Nagdive, R.M. Tugnayat, G.B Regulwar, D.Petkar, "Web Server log Analysis for Unstructured data Using Apache Flume and Pig," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.220-225, 2019.

Network attacks pose as grievous threat to the stability of the Internet and are a major security concern as they can breach the security of the network or even make the victim unavailable. The network attack packets can intercepted by using Iptables before they can reach the victim machine. Iptables is the standard firewall included in Linux distributions for handling the kernel Netfilter modules. The effectiveness of the defense provided by the Iptables firewall mainly depends on its rules. In this paper, we have proposed a novel framework with new customized Iptables rules for mitigating fifteen types of network attacks which include port scanning; denial of service attacks, TCP, UDP, and ICMP based attacks etc. The performance of Iptables with these rules is evaluated with the real experiments for examining the competence of firewall in managing the network traffic and security when subjected to attack flow along with the normal traffic. The performance of Iptables is recorded in the terms of CPU utilization for processing and Logs generation, Frame Loss Ratio and Efficiency. The attack traffic is generated using Scapy for execution of the attacks whereas the normal traffic is generated using a traffic generator called D-ITG. It was found that Iptables could successfully detect the network attack and performed really well during the mitigation of such attacks.

Iptables, Netfilter, Scapy, DITG, network-attacks

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[20] S. Mishra, S. Sonavane and A. Gupta, "Study of Traffic Generation Tools," International Journal of Advanced Research in Computer and Communication Engineering, (IJARCCE) Vol. 4, Issue 6, June 2015.
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Nikita Gandotra, Lalit Sen Sharma, "A novel framework for combating network attacks using Iptables," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.226-237, 2019.

In this paper, optimal power flow (OPF) using grass hopper optimization algorithm (GOA) is addressed. OPF is a basic tool for economical and secure operation of power system. Here, the generator fuel cost and voltage profile are considered as main objectives with constraints. The GOA is a metaheuristic swarm based optimization algorithm. It mimics the natural behaviour of grass hopper. The GOA is implemented on IEEE-30 bus system to solve OPF problem. Results show the ability of GOA to reduce the voltage deviation. It demonstrates that the GOA is capable to improve the voltage profile of system buses.

optimal power flow, grass hopper optimization algorithm, generator fuel cost and voltage profile, IEEE-30 bus system

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A.I. Modi, T.V. Rabari, "Optimal Power Flow Using Grass Hopper Optimization Algorithm for Generator Fuel Cost and Voltage Profile," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.238-241, 2019.

In this paper, an effective method for copy-move-rotation forgery detection is proposed which uses Zernike moments and local binary pattern (LBP) as feature extractors. First image is divided into overlapped blocks in which Zernike moments are calculated by rotating block pixels into different directions. Then rotated block with minimum value of Zernike moments is evaluated for which LBP features are extracted. Similar procedure is followed for all blocks. For matching process, mean value of block pixels is used after sorting them in an array. For similar mean value blocks, matching process is carried out by taking the variance difference of LBP features. Blocks with similar variance values are marked as forged pixels in the image. For decreasing the time complexity, edge detector is used which gives edge binary image for high gradient pixels in the image. First matching is carried out for edge pixel blocks only. In post processing, morphological operations are used and matching procedure is followed to get the forged pixels in the image. Experiment results are carried out on a standard dataset in which detection accuracy (DA) and false positive rate (FPR) are used for performance evaluation.

forgery detection, Rotation invariant, LBP, Zernike moments etc

[1] I. Amerini, L. Ballan, R.Caldelli, A. D. Bimbo, L.D. Tongo, G.Serra, “Copy-move forgery detection and localization by means of robust clustering with J-Linkage”, Signal Processing: Image Communication, Vol. 28, Issue. 6, pp.659-669, 2013
[2] R. Dixit, R. Naskar and A. Sahoo, "Copy-move forgery detection exploiting statistical image features," International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, pp. 2277-2281, 2017
[3] D. Cozzolino , G. Poggi , L. Verdoliva, “Efficient dense-field copy–move forgery detection”, IEEE Transactions on Information Forensics and Security, vol. 10, issue 11, pp. 2284-2297, 2015
[4] D. Tralic, I. Zupancic, S. Grgic, and M. Grgic, “CoMoFoD-New database for copy–move forgery detection,” 55th IEEE International Symposium ELMAR, 2013.
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[6] D. Chauhan, D. Kasat, S. Jain, V. Thakare, “Survey on Keypoint Based Copy-move Forgery Detection Methods on Image”, Procedia Computer Science, Vol. 85, pp. 206-212, 2016
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[10] D. Vaishnavi, T.S. Subashini, “Application of local invariant symmetry features to detect and localize image copy move forgeries”, Journal of Information Security and Applications, Vol. 44, pp. 23-3, 2019
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[16] Amey Samant, Sushma Kadge, "Classification of a Retinal Disease based on Different Supervised Learning Techniques", International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.9-13, 2017

Gurpreet Kaur, Rajan Manro, "Rotation Invariant ZLBP Features for Copy-Move-Rotation Based Image Forgery Detection System," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.242-247, 2019.

Most of the common problems encounter by the today’s world is traffic congestion. As populations as well as number of vehicles are increasing in the cities and towns, traffic congestion has become a major problem for the time being. Delays, fuel consumption and air pollutions are some of the problems arise from traffic congestion. There are many reasons for traffic congestion like narrow roads, lack of alternate route, slow traffic speed, improper uses of traffic signals etc. In this paper, we proposed a system to overcome some these problems by providing an alternate route for the vehicles by predicting a possible congestion ahead of that road.

Traffic congestion, Traffic density, vehicle count, vehicle speed, background subtraction, frame, Artificial neural network (ANN), Epoch

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[2] S. S. Harsha, Ch. Sandeep, “Real Time Traffic Density and Vehicle Count Using Image Processing Techniques”. International Journal of Research in Computer and Communication Technology. Vol 4, Issue 8 , 2015, pages 594-598
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Mirzanur Rahman, Surojit Dey, "Application of Image Processing and Data Mining Techniques for Traffic Density Estimation and Prediction," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.248-253, 2019.

Online social network (OSN) has become an important aspect of everyone’s life. Social networking involves connecting users with their friends, relatives, family and companions. This is internet and development of other social media technologies which allow people to communicate through social media. The very well-known social sites such as Skype, Facebook, Twitter, Instagram and LinkedIn etc. enable their users for performing various activities like sharing photos, videos and information, organize events, chat, and playing online games. In this paper, a comparison study is done on various existing trust analysis techniques which will help to identify the problems need to be focused.

Online Social Networks, Trust analysis, Privacy

[1] Sunil Sexena, “http://www.easymedia.in/8-key-characteristics-social-networking-sites”, December, 2013.
[2] Wanita Sherchan, Surya Nepal, Cecile Paris, “ A survey on Trust in Scoial Network” in ACM Computing Surveys, Vol. 45, no. 4, pp. 47:1-47:33 August 2013.
[3] Si Shi, Dawei Jin, “Real-time Public Mood Tracking of Chinese Microblog Streams with Complex Event Processing”, in Institute of Electrical and Electronics Engineers, Vol. 5, no. 2, pp. 421-431, December 2016.
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[5] Poornima Singh , “Opinion Mining on Social Media: Based on Unstructured Data” in International Journal of Computer Science and Mobile Computing, Vol. 4, no. 6, pp. 768-777, June 2015.
[6] Xiu li, Jiangou MA, “A Service Mode of Expert Finding in Social Network” in IEEE Control System Society, IEEE Xlpore, http://ieeexplore.ieee.org/document/6519794, pp. 220 – 223, May 2013.
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[15] Wenjun Jiang and Guojun Wang, “ SWTrust: Generating trusted graph for trust evaluation in online social networks”, in IEEE Xplore, http://ieeexplore.ieee.org/document/6120835, pp. 320–327, November 2011.
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Mohit Gambhir, Sapna Gambhir, "Trust Analysis Techniques in Online Social Networks: A Review," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.254-258, 2019.