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With increasing use of computers and mobile phones, malware attacks are also increased in last few years. Ransomware – one of the malware has become the biggest challenge for security experts and end users. There is urgent need to defend computers and smartphones against possible ransomware attacks. However, it may not be possible to stop such attacks, the attempt can be made to recover from such attacks. This paper discusses possibilities to recover data from encrypted files from ransomware affected android phones. The work presented in this paper was carried out to assist forensic investigators and assure end users that there are possible ways to retrieve their data without paying ransom money. It would be encouraging for end users to know that in most of the cases the data encrypted by a ransomware can be retrieved with help of forensic tools and it will be equally discouraging for attackers. The paper is focused on data recovery from ransomware affected android phones.

Ransomware, Android Ransomware, Ransomware Forensics, Data Recovery, Malware Forensics, Android Forensics

[1] A. Gazet, “Comparative analysis of various ransomware virii”, Journal in computer virology, Vol.6, Issue.1, pp. 77-90, 2010
[2] A. Kharraz, W. Robertson, D. Balzarotti, L. Bilge & E. Kirda, “Cutting the gordian knot: A look under the hood of ransomware attacks”, International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, Springer International Publishing, pp. 3-24, 2015
[3] N. Andronio, S. Zanero & F. Maggi, “HelDroid: Dissecting and detecting mobile ransomware”, International Workshop on Recent Advances in Intrusion Detection, Springer International Publishing pp. 382-404, 2015
[4] K. Cabaj, P. Gawkowski, K. Grochowski, & D. Osojca, “Network activity analysis of CryptoWall ransomware” Przegląd Elektrotechniczny, Vol.91, Issue.11, pp. 201-204, 2015
[5] N. Scaife, H. Carter, P. Traynor, & K. R. Butler, “Cryptolock (and drop it): stopping ransomware attacks on user data”, Distributed Computing Systems (ICDCS), IEEE 36th International Conference on, IEEE, pp. 303-312, 2016
[6] V. K. Gujare and P. Malviya, "Android Malicious apps and Malware Security: A Review", International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp. 43-47, 2016.
[7] V. Kapoor, "Data Encryption and Decryption Using Modified RSA Cryptography Based on Multiple Public Keys and ‘n’prime Number", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.2, pp.35-38, 2013.

P. H. Rughani, "Data Recovery from Ransom ware Affected Android Phone using Forensic Tools," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.67-70, 2017.

Today Information Technology is used in every domain of life. The traditional age-old system of intelligence and criminal record maintenance are no longer used in the current crime scenario. With the availability of spatial data related to crime can be used to integrate it with latest GPS system to highlight the location of crime and such indication can be used by people to be cautious and alert. This latest technology can be used as an aid to warn and guide people about such happening in the crime prone areas. Manual processes neither provide accurate, reliable and comprehensive data round the clock nor does it help in trend prediction and decision support. It also results in lower productivity and ineffective utilization of manpower. The solution to this ever-increasing problem lies in the effective use of Information Technology. This paper suggests methodology that combines the Geographical Information System with crime data to provide crime data mining.

Crime Mining, Geographical Information System, Hot Spots

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[4] S.V. Nath, “Crime pattern detection using data mining,” in the Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, pp. 41-44, 2006.
[5] S. Lin, D. E. Brown, “An Outlier-based Data Association Method For Linking Criminal Incidents”, Decision Support System, Vol 41, Issue 3, pp. 604-615, 2006.
[6] J. Han and M. Kamber, “Data Mining: Concepts and Techniques,” Morgan Kaufmann publications,India, pp. 1-39, 2006.
[7] M. Gupta , B. Chandra and M. P. Gupta, “Crime Data Mining for Indian Police Information System”, Computer Society of India, pp. 389-397, 2008.
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[10] K. Leong, S. Chan, V. Ng, S. Shiu, “Introduction of STEM: Space Time Event Model for Crime Pattern Analysis”, Asian Journal of Information Technology,Vol 7 Issue 12, pp.516-523, 2008.

N. Narwal, "Crime Data Mining an Indian Perspective," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.71-78, 2017.

OpenStreetMap (OSM) is a cumulative effort to create a free presentable map of the world that can be accessed by anyone. OSM is one the most prevalent instance of Volunteered Geographic Information (VGI). Since OSM is generating large amount of spatial data that has been contributed by users with the different level of mapping experiences and different backgrounds, hence the quality of OSM data can vary strongly. For this different studies have been done in which different aspects have been investigated. In most of the studies, ground truth reference datasets have been used for comparison of the data which is called the extrinsic analysis. But extrinsic analysis is not always possible because of lack of availability of ground truth reference datasets. Hence, intrinsic analysis can serve as prominent basis for making the approximate statements on the quality of OSM. The investigation analyses the existing intrinsic frameworks and its limitations and then proposed the new six quality parameters for assessing the completeness of the OSM data effectively. A framework has been developed on the basis of proposed parameters. The results obtained from execution helps in doing the statistical analysis and interpretation by providing the visualizations in the form of bar charts, graphs, tables and maps to assess the completeness of data without the help of any ground truth reference datasets. This enables arbitrarily OSM completeness assessment for any part of the world.

OpenStreetMap; Data Quality; Volunteered Geographic Ingormation ; Completeness

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[3] T. Hayakawa, Y. Imi, and T. Ito, “Analysis of quality of data in openstreetmap”, in Seventh IEEE International Conference on E-Commerce Technology (CEC’05) (2012), Hangzhou, China China, pp. 131–134, 2012.
[4] M. Haklay, “How good is volunteered geographical information A comparative study of openstreetmap and ordnance survey datasets”, Environment and Planning B: Planning and Design, vol. 37, no. 4, pp. 682–703, 2010.
[5] C. Barron, P. Neis, and A. Zipf, “A comprehensive framework for intrinsic openstreetmap quality analysis”, Transactions in GIS, vol. 18, no. 6, pp. 877–895, 2014.
[6] P. Mooney and P. Corcoran, “Analysis of interaction and co-editing patterns amongst openstreetmap contributors”, Transactions in GIS, vol. 18, no. 5, pp. 633–659, 2014.
[7] C. Westrope, R. Banick, and M. Levine, “Groundtruthing openstreetmap building damage assessment”, Procedia Engineering, vol. 78, pp. 29 – 39, 2014.
[8] H. Fan, A. Zipf, Qing Fu and Pascal Neis, “Quality assessment for building footprints data on OpenStreetMap”, International Journal of Geographical Information Science, vol. 28, Issue 4, pp. 700-719, 2014.
[9] S. S. Sehra, J. Singh, and H. S. Rai, “A systematic study of openstreetmap data quality assessment”, in Information Technology: New Generations (ITNG), 2014 11th International Conference, Las Vegas, NV, USA, pp. 377–381, 2014.
[10] V. Antoniou and A. Skopeliti, “Measures and indicators of vgi quality: An overview”, ISPRS Internationa Society for Photogrammetry and Remote Sensing, vol. II-3/W5, pp.345–351, 2015.
[11] P. Neis, M. Goetz, and A. Zipf, “Towards automatic vandalism detection in openstreetmap”, ISPRS International Journal of Geo-Information, vol. 1, no. 3, p.315, 2012.
[12] M. S. Fox and C. J. Pettit, “On the completeness of open city data for measuring city indicators”, in Smart Cities Conference (ISC2). Guadalajara, Mexico: IEEE, pp. 1-6 , 2015.
[13] J. Vuurstaek, G. Cich, L. Knapen, A.-U.-H. Yasar, T. Bellemans, and D. Janssens, “Gtfsbus stop mapping to the osm network”, Procedia Computer Science, vol. 109, pp. 50–58, 2017.
[14] J.F. Girres and G. Touya, “Quality assessment of the french openstreetmap dataset”, Transactions in GIS, vol. 14, Issue 4, pp. 435–459, 2010.
[15] B.A. Johnson and K. Iizuka, “Integrating openstreetmap crowdsourced data and landsat time- series imagery for rapid land use/land cover (lulc) mapping: Case study of the laguna de bay area of the philippines”, Applied Geography, vol. 67, pp. 140–149, 2016.
[16] C. Heipke, “Crowdsourcing geospatial data”, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 65, pp. 550–557, 2010.
[17] M. Over, A. Schilling, S. Neubauer, and A. Zipf, “Generating web-based 3d city models from openstreetmap: The current situation in germany”, Computers, Environment and Urban Systems, vol. 34, no. 6, pp. 496 – 507, 2010.
[18] M. Ruta, F. Scioscia, D. D. Filippis, S. Ieva, M. Binetti, and E. D. Sciascio, “A semanticenhanced augmented reality tool for openstreetmap poi discovery”, Transportation Research Procedia, vol. 3, pp. 479–488, 2014.
[19] F. Scioscia, M. Binetti, M. Ruta, S. Ieva, and E. D. Sciascio, “A framework and a tool for semantic annotation of fPOIsg in openstreetmap”, Procedia - Social and Behavioral Sciences, vol. 111, pp. 1092 – 1101, 2014.
[20] C. Bittner, “Openstreetmap in israel and palestine game changer or reproducer of contested cartographies?”, Political Geography, vol. 57, pp. 3448, 2017.
[21] J. J. Arsanjani, “An assessment of a collaborative mapping approach for exploring land use patterns for several european metropolises”, International Journal of Applied Earth Observation and Geoinformation, vol. 35, pp. 329–337, 2015.
[22] J. Schellekens, R. Brolsma, R. Dahm, G. Donchyts, and H. Winsemius, “Rapid setup of hydrological and hydraulic models using openstreetmap and the srtm derived digital elevation model”, Environmental Modelling & Software, vol. 61, pp. 98–105, 2014.
[23] P. Zhao, T. Jia, K. Qin, J. Shan, and C. Jiao, “Statistical analysis on the evolution of openstreetmap road networks in beijing”, Physica A: Statistical Mechanics and its Applications, vol. 420, pp. 59 – 72, 2015.
[24] M F Goodchild 2007 “Citizens as sensors: The world of volunteered geography”, GeoJournal , vol. 69, pp. 211–21, 2007.
[25] G. Sivaiah, PK. Rao, "Providing Efficient Driving Directions Using GPS and Driver`s Ability", International Journal of Computer Sciences and Engineering, Vol.2, Issue.9, pp.18-21, 2014.

Sonali Arora, Sukhjit Singh Sehra, Sumeet Kaur Sehra, "Design and Development of tool for assessing OpenStreetMap Completeness," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.79-87, 2017.

Opinion mining is accepting more attention because of the development of blogs, e-commerce, news, reports, forums and additional web sources where individuals tend to express their opinions. Different people have different opinions. People`s thought may vary according to the domain and opinion may contain both positive and negative words. For a product, user may like or dislike some of its features. Filtering this review and extract domain related features is the important task of this paper. In this paper, ontology is used to extract the features and adjectives are used as the sentiment word. Sentiment Analysis is used to obtain positive or negative feature of the review.

Ontology,Natural-language-Processing,SentimentAnalysis

[1] B. Liu,”Sentiment analysis and opinion mining”, Synthesis lectures on human language technologies, vol.5, no.1, pp.1-167, 2012.
[2] T.Ahmad and M.N.Doja,”Opinion mining using frequent pattern growth method from unstructured text”, pp. 92-95, 2013.
[3] S.Mishra, D.Mishra, and S.K.Satapathy,”Fuzzy pattern tree approach for mining frequent patterns from gene expression data”, vol.2, pp.359-363,2011.
[4] H.Wang and J.Chen,”Extracting two-noun phrases from customer reviews”, pp.1-4, 2009.
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[8] H.Hamdan, P.Bellot, and F.Bechet,”Supervised methods for aspect-based sentiment analysis”, pp. 596-600, 2014.
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[10] H.S.Le, T.Van Le, and T.V.Pham,”Aspect analysis for opinion mining of Vietnamese text”, pp. 118-123, 2015.
[11] S.Thirumaran and M.Sangeetha, "Ontology Founded Mesh Flatterer Aimed at Removal Facilities info Result", International Journal of Computer Sciences and Engineering, Vol.3, Issue.1, pp.224-227, 2015.
[12] Yaakub, R.M, Li and Feng Y,”Integration of Opinion into Customer Analysis Model”, IEEE International Conference on e-Business Engineering, pp. 90-95, 2011.
[13] Priyanka Sharma, R.K. Gupta, "A Novel Web Usage Mining Technique Analyzing Users Behaviour Using Dynamic Web log", International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.106-111, 2017.
[14] Shein, Khin Phyu Phyu and Thi Thi Soe Nyunt,”Sentiment classification based on Ontology and SVM Classifier”, IEEE Communication Software and Networks, pp. 169-172 ,2010.
[15] Freitas, Larissa A, and Renata Vieira,”Ontology based feature level opinion mining for portuguese reviews”, 22nd International Conference on World Wide Web. ACM, pp. 367-370 ,2013.
[16] Hazman, Maryam, Samhaa R.El-Beltagy and Ahmed Rafea,”A survey of ontology learning approaches”, vol. 22, No. 9,2011.
[17] Penalver-Martinez, Isidro, et al,”Feature-based opinion mining through ontologies”, Expert Systems with Application, pp.5995-6008 ,2014.
[18] Ali, Farman, Kyung-Sup Kwak and Yong-Gi Kim,”Opinion mining based on fuzzy domain ontology and Support Vector Machine: A proposal to automate online review classification”, Applied Soft Computing, pp. 235- 250, 2016.
[19] Kontopoulos, Efstratios, et al,”Ontology-based sentiment analysis of twitter posts”, Expert systems with applications, pp.4065-4074, 2013.

Drashti Naik, Jitali Patel, "Feature Extraction From Product Review Using Ontology," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.88-93, 2017.

the accreditation process conducted by National Board of Accreditation (NBA) in India is a quality assurance process to determine whether educational institutes are meeting the program objectives. The process involves measuring the attainment of program objectives in terms of Program Outcomes attainment and Course Outcome attainment levels. In this paper we describe the methodology for computation of Course Outcomes attainment we have designed and implemented in Information Technology department as part of the accreditation process. A running example of how the method is shown for one of the core courses in engineering program. Also, a discussion on the utilization of Course Outcome attainment values is done.

Course Outcome, Internal Assessment, Attainment calculation, NBA

[1]. H. R. Bhagyalakshmi D., Seshachalam, S. Lalitha, “Program Outcome Attainment Through Course Outcomes: A Comprehensive Approach”, Proc of the Intl Conference on Transformations in Engineering Education, pp 279-287, 2014.
[2]. Ramchandra, S., Maitra, S, MallikarjunaBabu.K, “Method for estimation of attainment of program outcome through course outcome for outcome based education”, 2014 IEEE International Conference on MOOC, Innovation and Technology in Education (MITE),pp 7 – 12, 2014.
[3]. Makinda J.,Bolong N., Mirasa A.K and Ayog J.L.,“Assessing the Achievement of Program Outcome on Environment and Sustainability: A Case Study in Engineering Education”, 2nd Regional conference on Campus sustainability: Capacity building in Enhancing Campus sustainability. University Malaysia Sabah, Malaysia, 7th-8th April 2015.
[4]. Norain Farhana Ahmad Fuaad, Ruhizan Bt. Mohammad Yasin and Norngainy MohdTawil, “Achievement of the Program Outcomes in Outcomes Based Education Implementation - A Meta Analysis”, Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia, January 7 – 9, 2014.

Lakshmi H.N, G. Bhagya Sri, Yashasree. J, S. Bhargav, B. Satheesh Kumar, K. Anusha, "Assessment method for Course Outcome attainment: A case study in engineering education," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.94-100, 2017.

Genetic Algorithms are earning respect in different fields of Operation Research like Transportation and Traveling Salesman Problem, etc. However, the best solution they produce needs several iterations to obtain. This paper develops a new hybrid method for Travelling Salesman Problem. The proposed hybrid method delivers same solution each time unlike genetic algorithms. The efficiency is compared against following existing crossover operators; namely, Order Crossover, Modified Order Crossover, Sequential Constructive Crossover, Modified Sequential Constructive Crossover. Experimental results show that the proposed hybrid method is better than the compared methods.

Travelling salesman problem, NP-hard, Hybrid method, Genetic algorithm, Hungarian method

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A.K. Prasad, Pankaj, "A Hybrid Method for Solving Traveling Salesman Problem using Hungarian Method," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.101-105, 2017.

The fuzzy model is a limited arrangement of fuzzy relations that frame a calculation for deciding the yields of a procedure from some limited number of past data sources and yields. Fuzzy model can be utilized as a part of connected mathematics, to contemplate social and mental issue and furthermore utilized by specialists, design, researchers, industrialists and analysts. There are different sorts of fuzzy models. In this paper we utilize two fuzzy models and give their application to a genuine issue. In this paper two methodologies of fuzzy capacity have been researched: the first distinguishes a fuzzy capacity with a special fuzzy relation (we call it an (E − F)- fuzzy capacity), and the second one characterizes a fuzzy capacity as a conventional mapping between fuzzy spaces. In our exchange the components of the area space are taken from the genuine vector space of measurement n and that of the range space are genuine vectors from the vector space of measurement (m when all is said in done need not be equivalent to n). We mean by R the arrangement of hubs R1, … , Rm of the range space, where Ri = {(x1, x2, … , xm)/xj = 0 or 1} for i = 1, … ,m. In the event that xi = 1 it implies that the hub Ri is in the ON state and if xi = 0 it implies that the hub Ri is in the OFF state. Additionally D signifies the hubs D1,… ,Dn of the area space where Di = {(x1,… , xn)/xj = 0 or 1} for I = 1, … , n. In the event that xi = 1, it implies that the hub Di is in the on state and if xi = 0 it implies that the hub Di is in the off state. A FRM is a directed graph or a guide from D to R with ideas like arrangements or occasions and so forth as hubs and causalities as edges. It speaks to easygoing relations between spaces D and R. Give Di and Rj a chance to signify the two hubs of a FRM.

FRM, Fuzzy Logic, Binary Algorithm, Fuzzy Optimization

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M. Abinaya, V. Ramadass, "A Study on Fuzzy Relational Mapping (FRM)," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.106-109, 2017.

Today Publish-subscribe model is used as communication backbone for various application domains such as IoT, Social networking, Intrusion detection system and Financial trading. Content-based flavor of Pub-Sub system enables routing of information from producers to consumers based on contents of the query or depends on subscriptions entered by the user. In this model, information is disseminated from producers to consumers through a network of brokers. The significant challenge in content-based Pub-Sub system lies in an efficient matching of an event against a large number of subscribers on a single message broker. To provide high throughput service guarantee to the subscriber of Pub-Sub system we propose a novel hybrid model for parallel event processing using MPI-CUDA approach. This approach combines message passing interface (MPI) and CUDA, a parallel computing platform and programming model, invented by NVIDIA. Results are compared with CCM (Cuda Content Matching Algorithm), a high performance, and parallel content matching algorithm. Approximately 1.77X speedup is observed in matching latency. This approach is suitable for use in event processing of large data intensive applications where the rate of arrival of the event is high.

Matching Latency, MPI-CUDA, High performance, parallel event processing.

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M.A. Shah, D.B. Kulkarni, "Design of High Performance, Scalable Content-based Publish-Subscribe System using MPI-CUDA Approach," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.110-115, 2017.

Data aggregation in wireless sensor networks is utilized to decrease the correspondence overhead and draw out the system lifetime. In any case, an enemy may bargain some sensor hubs, and utilize them to fashion false esteems as the aggregation result. Past secure data aggregation plans have handled this issue from various edges. The objective of those calculations is to guarantee that the Base Station (BS) does not acknowledge any fashioned aggregation comes about. However, none of them have attempted to identify the hubs that infuse into the system fake aggregation comes about. Additionally, a large portion of them for the most part have a correspondence overhead that is, (best case scenario) logarithmic per hub. In this theory, they propose a safe and vitality proficient data aggregation conspire that can recognize the malevolent hubs with a consistent per hub correspondence overhead. In our answer, all aggregation comes about are marked with the private keys of the aggregators so they can`t be changed by others. Hubs on each connection also utilize their Level Based shared key for secure correspondences. Every hub gets the aggregation comes about because of its parent (sent by the parent of its parent) and its kin (by means of its parent hub), and checks the aggregation consequence of the parent hub. Hypothetical investigation on Security, vitality utilization and correspondence overhead accords with our examination based recreation contemplate over arbitrary data aggregation trees.

Cloud computing, Infrastructure-as-a-Service, Load balancing, Parallel Mining

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V. Uthaman, "Energy Aware Load-Balancing of Parallel Mining of Frequent Sequences Using LB Scheme," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.115-120, 2017.

GIS data can be divided into two formats, raster and vector. Raster format can represent the values which give quantitative information such as temperature, vegetation intensity, land use/cover etc. Vector format can represent the value which give qualitative data which consists of point, lines and polygons and these representing the location, distance or area of landscape features in graphical forms. For extracting the data we can register the image for the initial processing. For register the image we can select the control points. This control point selection can convert the quantity data into quality data. This process of transforming information (quantity) into knowledge (quality) is called appropriation. To overcome the limitations of relational databases and provide a greater knowledge in terms of knowledge we use the spatio-temporal database.

Database , Quality database, Rotation,Scaling, SURF-Algorithm , Spatio-temporal model , Translation

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Sonia Rathee, Rahul Rishi, "Using Quality Database Convert the Quantity data into Quality data and Automate the Control Points using SURF Algorithm in Spatio-Temporal data," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.121-125, 2017.