Mobile devices have seen an exponential increase in the demand and its usage in recent years and this has made information access easy as well as vulnerable. Sensitive and critical information can be accessed by malicious applications using voluntary permission controls. It is necessary to develop an efficient and adaptable solution as signature-based antivirus solutions are ineffective due to high false detection rates. Android targeted malware has increased dramatically in recent years, and the focus of malware attackers towards the Android system has been much greater than other mobile operating systems. To address the problem of malware detection, we have proposed a machine learning-based malware detection system for Android platform. The system utilizes the features of collected random samples of benign and malware apps to train the classifiers

[1]. Zhou, Y., Wang, Z., Zhou, W., & Jiang, X. (2012, February). Hey, you, get off of my market: detecting malicious apps in official and alternative android markets. In NDSS (Vol. 25, No. 4, pp. 50-52).
[2]. Reina, A., Fattori, A., & Cavallaro, L. (2013). A system call-centric analysis and stimulation technique to automatically reconstruct android malware behaviors.EuroSec, April.
[3]. Arp, Daniel, et al. "DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket." NDSS. 2014. [4]. Li, Wenjia, JigangGe, and Guqian Dai. "Detecting malware for android platform: Ansvm-based approach." Cyber Security and Cloud Computing (CSCloud), 2015 IEEE 2nd International Conference on.IEEE, 2015.
[5]. Wu, Dong-Jie, et al. "Droidmat: Android malware detection through manifest and api calls tracing." Information Security (Asia JCIS), 2012 Seventh Asia Joint Conference on.IEEE, 2012.

Augmented Reality is the technology that has proved to bring revolution in the field of Education. It also have shown to be relevant, useful and valuable in encouraging children in various learning activities at an early age as visualizing things can be very laborious for children using traditional methods of learning. Other issues with the present teaching system involves complexity in stimulating children's learning interest, lack of teaching situation and poor study effectiveness. In this paper we are aiming to develop an Android based Mobile Application using Augmented Reality for kids. Our idea is to make learning interactive, simplify learning process as well as ease the burden on children. This work mainly considers Pre-School children and presents an approach with associated AR cards with a purpose of providing a playful approach towards learning of alphabets and numbers..

[1]. Chen Y, Zhou D, Wang Y, Yu J, "Application of Augmented Reality for Early Childhood English Teaching", International Symposium on Educational Technology 2017; 34: 111-115.
[2]. Al-Azawi R, Shakkah M. S., "Embedding Augmented and Virtual Reality in Educational Learning Method: Present and Future", 2018 9th International Conference on Information and Communication Systems; 218-222
[3]. Gupta N, Rohil M. K., "Exploring Possible Applications of Augmented Reality in Education", 2017 4th International Conference on Signal Processing and Integrated Networks; 437-441
[4]. Abbasi F, Waseem A, Ashraf E, "Augmented Reality Based Teaching In Classrooms", 2017 International Conference on Communication, Computing and Digital Systems 259-264;
[5]. Bratitsis T, Bardanika P, Ioannou M, "Science Education and Augmented Reality content: The case of the Water Circle", 2017 IEEE 17th International Conference on Advanced Learning Technologies; 485-489

Due to new technologies emerging in order to detect fraud and ill feedbacks and scores in online services, Trust Reputation Systems (TRS) provides robust support to parties who need to take the right decision in any e-commerce or electronic transaction. TRS has to trustfully calculate the most trustworthy score for a particular product or service. In fact, based on demonstrations, TRS gives the most trustworthy and calculates the most reputed results in the implement system. Thus, TRS must rely on a strong, reliable architecture and suitable algorithms that are able to select, save, generate and classify scores and feedbacks...........

Keywords: Analysis, Decision making, E-commerce, Rating, Textual feedbacks, Trust reputation.

[1]. A. Gutowska and A. Sloane: Modelling the B2C Marketplace: Evaluation of a Reputation Metric for e-commerce.
[2]. Proceedings of Web Information Systems and Technologies - WEBIST (2009), pp. 212-226.
[3]. A. Jøsang R. Hayward Simon Pope: Trust Network Analysis with Subjective Logic. Proceedings of the Second International Conference on Emerging Security Information, Systems and Technologies (SECURWARE 2008).
[4]. Hasnae Rahimi Information Security Research Team (ISeRT), University Mohammed V, ENSIAS, Avenue Mohamed Ben Abdellah Regragui, Rabat, Morocco (2013).
[5]. Hasnae Rahimi, El bakkali hanan: Toward a New Design of Trust Reputation System in e-commerce,. In the proceedings of ICMCS (International conference on Multimedia computing and systems) Tangier, Morocco, IEEE (2012).

In recent years, human cheating has grown quite drastically among the e-commerce websites. In today's competitive world where individuals' main aim is to earn big, trust becomes a big issue. Particularly in the field of online auctions, trust among random users is almost impossible to maintain [1]. Shill bidding is a process in which a seller increases the price of a product or introduces fake bids into the auction so as to raise the price of that particular product. The architecture for detecting the fake bidders is proposed which includes monitoring of the various patterns that these bidders follow. The algorithm called as Bid Tracking will be implemented that will help us to identify the patterns and hence a make conclusion as to whether that particular user is a fake bidder or not.

Keywords: e-commerce, fake bidders, online auction, shill bidding.

[1]. Cohen, P.: Shill Bidding on eBay: A case study. E-Commerce Bytes.Retrieved September 9, 2013, from http://www.ecommercebytes.com/forums/vbulletin/showthread.php?t=22659 (2009).
[2]. Dong, F. S., Shatz, M., & Xu, H.: Inference of Online Auction Shills Using Dempster-Shafer Theory. Proceedings of the 6th International Conference on Information Technology: New Generations (2009).
[3]. Mamum, K., &Sadaoui, S. Combating Shill Bidding in Online Auctions. Proceedings of International Conference on Information Society, Toronto, IEEE press (2013).
[4]. Trevathan, J., & Read, W. Detecting Collusive Shill Bidding. In Proceedings of the Fourth International Conference on Information Technology: New Generations (ITNG 2007), Las Vegas, Nevada, USA (2007).

Today the use of social media has been tremendously increased, but since there is no control over the social media there has been spread of fake news, messages like a drop of oil in water which has been proved hazardous to the humans. So the purpose is to develop a system which will classify the post or message either fake or genuine using Machine learning algorithm. Detecting Fake news is an important step. This work determines the use of machine learning techniques to detect Fake news.

Keywords - Fake news detection, Machine Learning, stochastic gradient descent

[1]. Granik, M., & Mesyura, V. (2017). Fake news detection using naive Bayes classifier, 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON). doi:10.1109/ukrcon.2017.8100379
[2]. Gilda, S. (2017). Evaluating machine learning algorithms for fake news detection, 2017 IEEE 15th Student Conference on Research and Development (SCOReD). doi:10.1109/scored.2017.8305411
[3]. Krishnan, S., & Chen, M. (2018). Identifying Tweets with Fake News. 2018 IEEE International Conference on Information Reuse and Integration (IRI). doi:10.1109/iri.2018.00073
[4]. Parikh, S.B., &Atrey, P. K. (2018). Media-Rich Fake News Detection: A Survey, 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR).doi: 10.1109/MIPR.2018.00093
[5]. Buntain, C.,&Golbeck, J. (2017). Automatically Identifying Fake News in Popular Twitter Thread, .2017 IEEE International Conference on Smart Cloud.doi:10.1109/SmartCloud.2017.40

Today almost all digital services like internet communication, medical and military imaging systems, the multimedia system requires reliable security in storage as well as in the transmission of digital images. There becomes a necessity for security in digital images because of the faster growth in the fields of multimedia technology, internet and cellphones. Hence, it becomes a need for image encryption techniques in order to hide images from such attacks. In this system, we use JS (Jumbling Salting) algorithm in order to hide the image. JS algorithm is being executed in .NET framework. It provides a brand new access to assure highlevel security of information as required in the fields of aerospace, military..........

Keywords : JS algorithm, Encryption, Jumbling, Key, Salting, Security

[1]. Ch. Santhosh Reddy, Ch. Sowjanya, Praveena, Prof. Shalini L, "Poly-alphabetic Symmetric Key Algorithm Using Randomized Prime Numbers", IJSR, Volume 2, Issue 9, September 2012, ISSN 22503153.
[2]. C. Pfleeger, S. Pfleeger, Security in Computing, Third Edition, Prentice Hall PTR, ISBN: 0-13-035548-8.
[3]. Kahate Atul, 2003, "Cryptography and Network Security", Third Edition, Tata McGraw Hill India.
[4]. M. Stamp, Information Security : Principles an practice, Wiley publications , ISBN-13 978-0-471-73848-0
[5]. Subramania Sudharsanan, "Shared Key Encryption of JPEG Color Images", IEEE[J], 2005, 51(4), 1204-1211.

In today's era of women empowerment most of the articles in the newspaper covers the achievements of women but we owe the responsibility to introspect that equal or more than the same number of news are the ones of rape, sexual abuse, sexual harassment etc. Where is our society heading towards? A society which strives for empowerment of women and suppresses its safety or the one which strives for both? In every developed country the maneuver for women safety arised much before women empowerment. This paper focuses on mainly three phases. The most important part of the system is the collection of data which is analysed on firebase to provide an alert message regarding the safety of a particular location before visiting the same location. The system also consist of a prototype of an IoT device which a women can trigger by pressing a button which will automate the application through Bluetooth. Various security features is provided to the victim through the application. The system takes proper care to see all possible measures taken to provide help to the victim in a distressed situation.

[1]. https://www.washingtonpost.com/news/worldviews/wp/2018/06/27/india-ranked-worlds-most-dangerous-place-for-womenreigniting- debate-about-womens-safety/?noredirect=on&utm_term=.10302532b2fc
[2]. https://www.financialexpress.com/india-news/crimes-in-india-rise-in-2018-as-compared-to-last-year-murder-rapes-see-a-spikesays- this-report/1080222/
[3]. https://www.indiegogo.com/projects/invisawear-smart-jewelry-that-could-save-your-life#/
[4]. https://revolar.com/
[5]. http://www.tanyamunshi.com/lifestyle/vithu-app-an-app-to-keep-you-safe/

An Esteemed organization has thousands of Employees working in different departments and every department has different teams separated based on their work categories(eg: In IT department we have designing team, developing team, etc) All these employees record their daily basis work data in excel sheets,mails,laptop,notepads,etc. Additionally, the Managers may be contacting with the employees under them on a range of different platforms – phone, email and social media. Asking for reports, following up on projects . It is a dynamic and useful web application that provides an automated and centralized method of tracking and monitoring daily work time for active projects by enabling managers to track employees work time and efforts spent while working on various projects performing tasks assigned to them, also leave can be recorded. This system helps in completing projects on-time by providing real-time project status............

Keywords: Daily work Record, Time analysis, Resource utilization,Report generation, Leave records.

[1]. TSheets. (2018). Employee Time Tracking & Timesheet Software - Free Trial - TSheets. [online] Available at: https://www.tsheets.com/ [Accessed 12 August. 2018].
[2]. Sling. (2018). Sling: Employee Scheduling And Shift Planning Made Easy and Free. [online] Available at: https://getsling.com/ [Accessed 12 August.. 2018].
[3]. Shiftboard. (2018). The Leader in Enterprise Workforce Scheduling Software | Shiftboard. [online] Available at: https://www.shiftboard.com/ [Accessed 17 August. 2018].
[4]. Deputy. (2018). Deputy | Workforce management. [online] Available at: https://www.deputy.com/ [Accessed 18 August. 2018].
[5]. Getharvest.com. (2018). Simple Online Time Tracking Software - Harvest. [online] Available at: https://www.getharvest.com/ [Accessed 19 August. 2018]

Digital identity is one of the important aspect of digital economy. However, proving one's identity remotely is not that much easy. Centralized models of Identity Management are currently facing various challenges due to increasing number of data breaches which is causing loss of users data and privacy. Use of Blockchain Technology can help us to solve these issues. Blockchain Technology has revolutionized the entire mechanism of storing and maintaining the digital identity online. Also it helps to use digital identity globally as a legal identity proof or document. The main objective of this research is to find out solutions for current centralized identity management systems by the help of Blockchain Technology. The paper also includes a study of currently used systems for a better understanding of the technology.

Keywords- Blockchain Technology, Ethereum, Identity Management, IPFS, PKI

[1]. C. Ellison; B. Schneier, A "Ten risks of pki: What you're not being told about public key infrastructure," ComputSecurJ, vol 16, no.1, pp, 1-7,2000
[2]. Makoto Takemiya, Bohdan Vanieiev IEEE 2018 Sora Identity: Secure, Digital Identity on the Blockchain
[3]. S. Nakamoto, Bitcoin: A peer-to-peer electronic cash system, 2008
[4]. D. Baars, "Towards self-sovereign identity using blockchain technology," University of Twente, 2016
[5]. IBM, "Blockchain Technology for Recordkeeping", https://x9.org/wpcontent/uploads/2016/02/Blockchain-Explained-v2.09.pdf

In India, elections are conducted using EVMs and VVPAT machines requiring a high amount of manpower. A public election system constitutes the foundation of a democracy where people elect their leader. Remote Voting System for India, based on biometrics with the help of AADHAAR is proposed for the first time in this paper. The proposed model is a good attempt to eradicate false votes. This will help to manage the elections easily and more securely. In this model, it requires less physical infrastructure and human efforts. Remote Voting System is a way that assists the voter to vote for his/her favorite candidate from any of the polling booths irrespective of the allotted booth. The additional feature is that it reduces paperwork for the electoral roll. The tallying and the counting of the votes are done automatically, thus saving a huge amount of time for the Election Commission to declare the results.

[1]. Himanshu Agarwal, G.N. Pandey , "Online Voting System for India Based on AADHAAR ID" Indian Institute of Information Technology, Allahabad-211012, India, November 20, 2013.
[2]. Sayali Shinde, Nikita Sherla, Sampada Zadgoankar, Sapna Hulsurkar, S. P. Mone, International Journal of Innovative Research in Computer and Communication Engineering, India, March 2018.
[3]. Kanchan Avhad, Kalyani Avhad, Gayatri Bhosale, Kamini Kamale, International Research Journal of Engineering and Technology, Volume.5, Issue. 1, Nashik, India, Jan-2018.

Nowadays free Wi-Fi hotspot is available everywhere, and it gives access to user after authentication by the One time password (OTP) send on the user Mobile number. But OTP method of authentication is not so secure as many attacks can be performed to identify user OTP. For this we propose a new method of authentication using Authcoin that use blockchain to store the data which provide more security to the user credentials.

[1]. Sanda, Tomoyuki, and H. Inaba. "Proposal of new authentication method in Wi-Fi access using Bitcoin 2.0." Consumer Electronics, 2016 IEEE, Global Conference on IEEE, 2016:1-5.
[2]. S. Nakamoto. Bitcoin: A peer-to-peer electronic cash system.
[3]. Available: https://bitcoin.org/bitcoin.pdf
[4]. K. Miura and H.Inaba, "Privacy preserving digital contents circulationsystem using bitcoin 2.0," IEICE Tech. Report, vol. 2016- EIP-72, no. 5, pp. 1-4, may 2016 (in Japanese).
[5]. Coloredcoins. [Online]. Available: http://coloredcoins.orgK. Elissa, "Title of paper if known," unpublished

In today's modern world, everything is digitized where different means of interacting with digital devices are gaining popularity and importance. This Application can perform various tasks such as capture an image, snapshot, media controls using hand gestures. It is an interface that augments the real world around us with digital information. It takes input through webcam and processes the frames of images through image processing tools and perform actions which are pre-defined or can be user-defined. Our approach consists of three different steps that are hand localization, hand gesture tracking and spotting. Ittracks the candidate hand regions on the basisof skin color and motion. The algorithm find the centroids of the moving hand regions and detect a unique gesture interface to perform certain actions

Keywords: Image processing, user-defined gestures, feature recognition, feature extraction, Gesture classification.

[1]. "Hand gesture recognition system" Praveen D. Hasalkar, Rohit S. Chougule, Vrushabh B. Madake, Vishal S. Magdum, International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 4, April 2015.
[2]. "Static Hand Gesture Recognition for Human Computer Interaction" Hamid A. Jalab ;
[3]. "Hand Gesture Recognition System Using Image Processing" Sagar P. More and Abdul Sattar, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) – 2016.
[4]. "Hand Gesture Recognition using Shape and Texture evidences in Complex Background" Dinesh Kumar Vishwakarma,International Conference on Inventive Computing and Informatics (ICICI 2017)
[5]. "Gesture Controlled Touch Less Response using Image Processing"Subiya Yaseen, Shireen Fathima, Surendra K.V, Jebran P and Saba SanoberInternational Conference on Energy, Communication, Data Analytics and SoftComputing (ICECDS-2017)

The data is expanding rapidly. Different types of industries, organizations, and business store their data on an electronic medium. A big amount of data flows over the internet. Traditional data mining tools are not capable to handle textual data as it requires time and effort to extract information.[1]. In this proposed system we will transliterate audio call recordings in order to detect emotions of the speakers. Our system originally involves calls from call centres but can have exposure in other areas too. The proposed system deals with speech-to-text conversion, text classification and text clustering.

Keywords- Sentimental analysis, Text mining, Natural language processing

[1]. (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7 No. 11, 2016 Text Mining: Techniques, Applications and Issues Ramzan Talib∗, Muhammad Kashif Hanif†, Shaeela Ayesha‡, and Fakeeha Fatima§
[2]. A blog on brand24.com about sentimental analysis
[3]. Sentiment Analysis: An Overview Comprehensive Exam Paper Yelena Mejova Computer Science Department, University of Iowa
[4]. www.researchgate.net/publication/310500453_Call_center_performance_evaluation_using_big_data_analytics
[5]. 2014 IEEE 2014 International Conference on Computer, Communication, and Control Technology (I4CT 2014), September 2 - 4,2014 - Langkawi, Kedah, Malaysia Sentiment Analysis Using Support Vector Machine

Recommender system is defined as system which recommend the most suitable schemes, product or service to particular farmer based on related information about the farmer and data collected from sensors. e.g .Kisan seva , Krishi mantra, etc. The recommender system will provide the agricultural information about fertilizers, soil, climate, crop rotation, various government schemes and helping hand for business and solve the problems such as lack of information, advancement in technology. The farmer can able to grow the number of crops in their field by using this information. The system will suggest helpful information to farmer............

Keywords- Arduino, Government schemes, IoT, Recommender system, Smart Agriculture

[1]. (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7 No. 11, 2016 Text Mining: Techniques, Applications and Issues Ramzan Talib∗, Muhammad Kashif Hanif†, Shaeela Ayesha‡, and Fakeeha Fatima§
[2]. A blog on brand24.com about sentimental analysis
[3]. Sentiment Analysis: An Overview Comprehensive Exam Paper Yelena Mejova Computer Science Department, University of Iowa
[4]. www.researchgate.net/publication/310500453_Call_center_performance_evaluation_using_big_data_analytics
[5]. 2014 IEEE 2014 International Conference on Computer, Communication, and Control Technology (I4CT 2014), September 2 - 4,2014 - Langkawi, Kedah, Malaysia Sentiment Analysis Using Support Vector Machine