iosr-JCE   Volume-22 ~ Issue-6 ~Nov. - Dec. 2020

Abstract: With the prosperous development of the Internet, cyber-attacks against web application vulnerability have also emerged. At the same time, different scanners have grown rapidly to make web service more secure, such as NMAP, Hydra, etc. Most of them only achieve few specific functions without information collection. This brings inconvenience to vulnerability detection, because the frequent switching of tools may be time-consuming and error-prone. To assist developers in better vulnerability detecting. In this paper, an automatic vulnerability scanner based on port service information is proposed. Through the experimental results, the tool presents satisfying effects by implementing the combination of port scanning, weak password blasting and directory detection, also indicates great potential for the extensibility.

Key Word: Web Security, Information Collection, Port Scanning, Password detection, Directory scanning

[1]. Vugrin, Eric D., et al. "Cyber threat modeling and validation: port scanning and detection." Proceedings of the 7th Symposium on Hot Topics in the Science of Security. 2020.
[2]. Calzavara, Stefano., et al. "Machine Learning for Web Vulnerability Detection: The Case of Cross-Site Request Forgery." IEEE Security and Privacy Magazine 18(3) (2020): 8-16.
[3]. Qin, Jiawei., et al. "Vulnerability Detection on Android Apps–Inspired by Case Study on Vulnerability Related with Web Functions." IEEE Access 8 (2020): 106437-106451.
[4]. Makino, Yuma., and V. Klyuev. "Evaluation of web vulnerability scanners." IEEE International Conference on Intelligent Data Acquisition & Advanced Computing Systems: Technology & Applications. IEEE, 1 (2015): 399-402.
[5]. Chen, Chung Kuan., et al. "Penetration Testing in the IoT Age." Computer 51(4) (2018):82-85.

Abstract: The Level Generation Competition, Mario AI Championship, was to the knowledge of the world's first procedural content generation competition. Competitors participated by submitting level generators — software that generates new levels for a version of Super Mario Bros tailored to individual players' playing style. This paper presents the principles of the competition, the scoring procedure, the submitted level generators, and therefore the results of the competition. Here also discuss what are often learned from this competition, both about organizing procedural content generation competitions and about automatically generating levels for platform games..

Key Word: Mario, game AI, reinforcement learning, competitions

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Abstract: The manual document summarization of any document is very tedious job and such summarized documents may differ and lead to diverse results. To avoid this problem, automatic text summarization plays very vital role. An Automatic Text Summarization (ATS) System gives the summary of any document without changing it's meaning and with less sentences. There are a lot of ATS systems available for various languages. In India, variety of regional languages are spoken and people do prefer to read the books, news articles, journals, magazines in their regional language only. Here emanates the summarization of regional language of Maharashtra i.e. Marathi. The Marathi text summarization is now imperative task and it is equally significant for the young one's too. The System is developed according to the need of students, who are willing to give competitive exams and they do need the awareness of current affairs in terms of daily news articles. This system summarizes Marathi news articles using machine learning algorithm.

Keywords : ATS (Automatic Text Summarization), Gensim, Unsupervised Extractive Text Summarization.

[1]. Apurva D. Dhawale, Sonali B. Kulkarni, and Vaishali Kumbhakarna, "Survey of Progressive Era of Text Summarization for Indian and Foreign Languages Using Natural Language Processing", ICIDCA 2019, LNDECT 46, pp. 654–662, Springer Nature Switzerland AG, 2020.
[2]. Apurva D. Dhawale, Sonali B. Kulkarni, and Vaishali Kumbhakarna, "A Survey of Distinctive prominence of Automatic Text Summarization Techniques Using Natural Language Processing", International conference on mobile computing and sustainable informatics, (ICMCSI), Springer conference, Tribhuvan university, Nepal, 2020.
[3]. Apurva D. Dhawale, Sonali B. Kulkarni, Vaishali M. Kumbhakarna, "Automatic Pre-Processing of Marathi Text for Summarization", International Journal of Engineering and Advanced Technology (IJEAT), ISSN: 2249-8958, Volume-10 Issue-1, October 2020.
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Abstract: The reality is that, the population of every city along with numbers of vehicles on roads are increasing rapidly. With increasing urban population and hence the number of vehicles, the need of controlling streets, highways with small roads is major issue. The main reason for increasing trafficproblem is the techniques that are used for traffic management. The traffic management system used in todays has no emphasis on live traffic scenario, which leads to inefficient traffic management systems. This project has beenimplemented by using Matlabsoftware and it aims to prevent heavy traffic congestion. For implementing this project, we have used Image processing technique. Firstly, the.....

Keywords : Population of city, Traffic congestion, Image processing, Trafficdensity, Adaptive Signal Controlling

[1]. Digital image processing by Rafael C. Gonzalez and Richard E. Woods.
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[3]. B. Fazed, H. Atmoko, F. Gu, L. Guan1 and A. Ball" Acoustic Based Safety Emergency Vehicle Detection for Intelligent Transport Systems" ICCAS-SICE, Fukuoka, Aug 2009, pp.4250-4255.
[4]. Z. Jinglei, L. Zhengguang, and T. University, "A vision-based road surveillance system using improved background subtraction and region growing approach," Eighth ACIS Int. Conf. on
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Abstract: We are living in a digital world now. The emergence of web and social networks has led to massive amounts of data being generated every single second, which presents both opportunities and challenges for the data field. The sheer volume of data calls for a change in our understanding of the data and how to extract usable information from this data. While traditional areas of computer science remain important, crunching through the massive volumes of data require new age tools and technologies such as Data Science, Data Mining and Data Analytics. Big data is undeniably a big deal, but it needs to be put in context. Data alone has no value, but the hidden patterns and insights in the data sets are an extremely valuable asset. Data Science, data mining and data analytics are often regarded as a subset of Business Intelligence. In this paper we discuss the overall comparatives of techniques used in the field of data science, data mining and data analytics.

Keywords : Big Data, Data Science, Data Analytics, Data Mining

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