iosr-JCE   National Conference On Advances In Computational Biology, Communication, And Data Analytics (ACBCDA 2017)

Abstract: In recent years the topic of data hiding has become very popular and a lot of research is being done in this field. The use of computer networks for data transmission has created the need for security. The security plays an important role in transmission of confidential data over internet. So, as a part of improving security in data transmission, we aim to hide the data inside an encrypted video. Thereby, confidentiality of the video as well as the embedded data is maintained. The embedded data can be extracted without any error, and also the cover image restoration is also free from error...........

Keywords - AES, Context Free Grammar (CFG), LSB, Reversible data hiding (RDH), RSA.

[1]. Gayatri Pisal, Aparna More, Sonali Pawar, and Ashwini Vishwakarma "Separable Reversible Data Hiding in Encrypted Video File IJRCS - International Journal of Research in Computer Science, Volume: 02 Issue: 04 2015.
[2]. Mr. Ratnakar Kumbhar, Mr. Sagar Yamgar, Ms. Rupali Ghule, Prof. Murkute P.K "Data Hiding in Encrypted H.264/AVC Video Streams By Codeword Substitution" IEEE International Journal of Computer Science and Information Technology Research ISSN 2348-120X (online) Vol. 3, Issue 2, pp: (323-331), Month: April - June 2015
[3]. Z. Ni, Y. Shi, N. Ansari, and S. Wei, "Reversible data hiding", IEEE Trans.Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354362, Mar.2006.
[4]. J. Kieffer and E-h. Yang, "Design of context-free grammars for lossless data compression,"Technical Report, Dept. of Electrical & Computer Engineering, University of Minnesota Twin Cities.
[5]. Lixiao Zheng, Duanyi Wu, "A Sentence Generation Algorithm for Testing Grammars", 2009 33rd Annual IEEE International Computer Software and Applications Conference

Abstract: Association rule and data mining techniques is most commonly used nowadays by every organizations and individual to extract the knowledge or the useful information from large amount of data. Knowledge and the information gives a gain to the organization .The main objective of the association rule hiding algorithms is to hide sensitive information so that they cannot be discovered through association rule mining algorithm, but at the same time not losing the great benefit of association rule mining and try to hide more and more rules and retrieve the original database without losing the integrity of the database when association rule mining algorithm is inversed. However the proposed system will hide the sensitive rule by using the dummy items and generate different database which is known as modified database so that no one can get the original database.
Keywords: Association rule, Data Mining, Frequent Itemset, Knowledge Discovery in Database(KDD), Sensitive Rule.

[1]. Anton Flank , Multirelational Association Rule Mining, 7th September 2004.
[2]. Suma B,Association Rule Hiding Methodologies: A Survey, International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 2 Issue 6, June– 2013.
[3]. K. Srinivasa Ra , B. Srinivasa Rao , An Insight in to Privacy Preserving Data Mining Methods , The SIJ Transactions on Computer Science Engineering & its Applications (CSEA), Vol. 1, No. 3, July-August 2013 .
[4]. N V Muthu lakshmi,Dr. K Sandhya Rani,Privacy Preserving Association rule mining for Horizontally Partitioned Distributed Database, International Journal of Computer Science and Information Technologies, Vol. 3 (1) , 2012, 3176 – 3182.
[5]. Khalid Iqbal, Sohail Asghar, Simon Fong, A PPDM Model Using Bayesian Network for Hiding Sensitive XML Association Rules, IEEE-2011..

Abstract: Steganography is an art of hiding secret information into another cover medium like image, audio, video. Cryptography is an art of converting plain data into unreadable format. Steganography can be integrated with Cryptography in order to enhance the security of data. In this paper, a new method is proposed that integrates Steganography and Cryptography for 24 bit color images. In this method, LSB based method is used to hide an image in another image. The resulting stego image is then encrypted using chaotic theory. This new integrated method ensures the enhancement in the data hiding capacity and the security of the image.

Keywords- Image, Steganography, Cryptography, Encryption, Decryption, Data hiding, Security.

[1] Shahzad Alam, S M Zakariya, M Q Rafiq, "Analysis of Modified LSB Approaches of Hiding Information in Digital Images", 2013 5th International Conference on Computational Intelligence and Communication Networks, @ 2013 IEEE.
[2] A. Joseph Raphael, Dr. V. Sundaram, "Cryptography and Steganography–A Survey", Int. J. Comp. Tech. Appl., Vol 2 (3), 626-630.
[3] Vipul Shanna, Madhusudan, "Two New Approaches for Image Steganography Using Cryptography", 2015 Third International Conference on Image Information Processing, © 2015 IEEE.
[4] Xinyi Zhou, Wei Gong, WenLong Fu, LianJing Jin, "An Improved Method for LSB Based Color Image steganography Combined with Cryptography", copyright 2016 IEEE ICIS 2016, June 26-29, 2016, Okayama, Japan.
[5] Moresh Mukhedkar, Prajkta Powar, Peter Gaikwad, "Secure non real time image encryption algorithm development using cryptography & Steganography", ©2015 IEEE..

Abstract: Analysis of emotion in text is a very young field in the area of computational linguistics. Analysis of emotions involves evaluation and classification of text into emotion classes based on certain levels as defined by emotion dimensional models which are described in the theory of psychology. Emotion analysis and classification is performed to identify the expressions of emotion in a given text. In this paper a huge dataset of social media data (tweets) is classified into five emotion categories (happy, sad, anger, fear and surprise) using machine learning techniques(Naïve Bayes and Support Vector Machine).

Keywords: classification, emotion, emotion analysis, Naïve Bayes, SVM.

[1]. Yoad Lewenberg, Yoram Bachrach, Svitlana Volkova," Using Emotions to Predict User Interest Areas in Online Social Networks", 2015 IEEE
[2]. James A. Russell, "Emotion in Human Consciousness Is Built in Core Affect", Journal of Consciousness Studies,12,No.8-10,pp 26-42, 2005. [3]. DavidWatson; Auke Tellegan, "Towards a consensual structure of Mood", Psychological Bulletin, Vol. 98, No. 2. 219-235,1985.
[4]. Hugo Lövheim, A new three-dimensional model for emotions and monoamine neurotransmitters, Medical Hypotheses 78 (2012) 341–348. Processing and its Applications.Research in Computing Science 46, 2010, pp. 131-142.
[5]. Paul Ekman, "Universals and Cultural Differences in Facial Expressions of Emotion", Nebraska Symposium on Motivation, Vol 19,1971.

Abstract: These days, wireless Monitoring for home security only using motion detection is among the cutting-edge technology in the field of IOT. To implement real-time surveillance of the home security, the intelligent remote monitoring system was developed for home security based on motion detection technique and GSM / GPRS network. In some image conversion method, the system can send images to the cell phone connected to it by using GPRS technology after confirming an intruder. The introduction of a variety of sensors and the enhancement of system's reliability guaranteed that the intelligent remote monitoring system can be responsible for home security. The hardware and software design............

Keywords:- Intrusion, Motion Detection, Surveillance, GPRS

[1]. Young-Kee Jung, Kyu-Won Lee, Dong-Min Woo, AND Yo-Sung Ho: "Automatic Video Object Tracking Using A Mosaic-Based Background", K. Aizawa, Y. Nakamura, And S. Satoh (Eds.): Pcm 2004, Lncs 3332, PP. 866–873, 2004. @Springer-Verlag Berlin Heidelberg 2004
[2]. V. D. Ambeth Kumar, M. Ramakrishanv. D. Ambeth Kumar, M. Ramakrishna: "Web Cam Motion Detection Surveillance System Using Temporal Difference AND Optical Flow Detection WITH Multi Alerts".
[3]. Jun Ke, Amit Ashok, Mark A. Neifelda: "Block-Wise Motion Detection Using Imaging System". Department OF Electrical Computer Engineering, University OF Arizona, Tucson, Az 85721-0104, Usa College OF Optical Sciences, University OF Arizona, Tucson, Az 85721-0104, Usa
[4]. Microsoft Security Research & Defense, [Online], VAILABLE: http://Blogs.Technet.Com/Srd/Archive/2008/02 /06/The-Kill 2d00 Bit-Faq 3a00 -Part-1-OF-3.ASPX
[5]. Eric Galloix, Janne Heikkila,¨ Olli Silvendepartment OF Electrical Engineering P.O. Box 4500, Fin-90014 University Of Oulu, Finland : "Motion Detection Against CHANGING ILLUMINATION: A Classifyingapproach".

Abstract: This paper investigates the development of digital image analysis approach for estimation of physical properties of soil in lieu of conventional laboratory approach. The traditional laboratory approach attracts some drawbacks such as lot of manual involvement, time consuming, chances of creeping of human errors, uncertain prediction and always invasive in nature . The signal processing methods involve enhancing original image using filters and calculating the features of the transformed images. In this paper Low mask, Gabor Filter and color quantization are applied to the original images to extract the texture features of soil images for retrieval. Results on a database of 100 soil images..........

Keywords: Soil Texture, Types of soil, Soil texture, Law mask features, Color Quantization

[1]. Evaluation of Texture Methods for Image Analysis by Mona Sharma, Sameer Singh.
[2]. Wavelet Based Features for Texture Classification by P.S.Hiremath, Dept. of P.G.Studies and Research in Computer Science, Gulbarga University,
[3]. Texture segmentation: Co-occurrence matrix and Laws' texture masks methods by Guillaume Lemaitre - Miroslav
[4]. Role of Soil in Groundwater Protection by Carl F. Engle, Craig G. Cogger, and Robert G. Stevens
[5]. Determining Composition of Grain Mixtures by Texture Classification Based on Feature Distributions by.Timo Ojala, Matti Pietikäinen

Abstract: The classification of point source objects into stars and galaxies largely depends on spectrographic surveys, which are expensive and time-consuming. This paper attempts to estimate, with a considerable accuracy, the possibility to classify these objects using only photometric data. Various machine learning algorithms are used to determine correlation, if any, between the properties of an object and photometric parameters. The focus is on the pre-processing of data to generate the most accurate predicting feature. In-depth............

Keywords— Machine Learning, Star-Galaxy Classification, Process Model

[1]. Alam, Shadab and Albareti, Franco D and Prieto, Carlos Allende and Anders, Friedrich and Anderson, Scott F and Anderton, Timothy and Andrews, Brett H and Armengaud, Eric and Aubourg, Eric and Bailey, Stephen and others. The eleventh and twelfth data releases of the Sloan Digital Sky Survey: Final data from SDSS-III. The Astrophysical Journal Supplement Series219(1), May 22, 2015,1--12.
[2]. W. Romanishin An Introduction to Astronomical Photometry Using CCDs. University of Oklahoma (31), October 22, 2002.
[3]. Waisberg, I. R. Astronomical point source classification through machine learning. Stanford project year 2013., December 13, 2013.
[4]. Yanxia Zhang, Yongheng Zhao, Automated Clustering Algorithms for Classification of Astronomical Objects, Astronomyand Astrophysics, 422(3) · March 2004, 1113--1121.
[5]. K Dhanasekaran and B Surendiran, Nature-inspired classification for mining social space information: National security intelligence and big data perspective, Green Engineering and Technologies (IC-GET), 2016 Online International Conference, pp. 1-6, 2016

Abstract: Internet of Things (IoT) in industries has created a new revolution in industries. IoT in industry has given rise to the term "INDUSTRY 4.0" where systems are connected to each other over the internet and can communicate with each other to take necessary decisions (also called as M2M communication) through artificial intelligence. In this paper, we shall design a system which will automatically control and monitor the industrial applications and also allow the user to control the application from anywhere in the world. Having control over the applications over the internet is one of the best ways to deal with the industrial applications

Keywords - Artificial intelligence, Industry 4.0, M2M communication

[1]. Mark D. Sen Gupta, CSIA Executive Conference San Diego, April 2014
[2]. M. Kim and K. Kim, AUTOMATED RFID-BASED IDENTIFICATION SYSTEM FOR STEEL COILS, Progress In Electromagnetics Research, Vol. 131, 1–17, 2012
[3]. S.d.t. Kelly, n.k. Suryadevara and S.C. Mukhopadhyay Towards the Implementation of IoT for Environmental Condition Monitoring in Homes,IEEE Paper 2013
[4]. Jinsung Byun, Insung Hong, Byoungjoo Lee, and Sehyun Park, Member Intelligent Household LED Lighting System Considering Energy Efficiency and User Satisfaction,IEEE paper February 2013
[5]. Gopinath Shanmuga Sundaram, Bhanuprasad Patibandala, Harish Santhanam Bluetooth Communication using a Touchscreen Interface with the Raspberry Pi 978-1- 4799-0053-4/13/31.00 2013 IEEE

Abstract: Currently wireless technology, fitness trackers and body sensor devices are creating great impact on the quality of living and healthcare system. The main aim of fitness bands is to keep you motivated during your regular workouts by providing necessary information regarding your fitness level over the entire day. This information can be obtained by using a fitness band or a smartphone app. The main objective of this study is to provide the necessary information regarding the electronic sensors used in these bands and also their working to determine step count, heart rate, quality of sleep, calories burnt etc.

Keywords: Fitness band, Healthcare system, Internet of things (IoT), Sensors.

[1]. Tyler Hayes, What's inside fitness tracker, anyway? — November 29, 2014 1:00 PM
[2]. Fatemma El-Amraww, Are currently available wearable devices for activity tracking and heart rate monitoring accurate, precise, medically Benefitial?
[3]. Inna vishi, Mover of mirrors ,How do optical heart rate sensor work?, written Jun 20,2015
[4]. Michael sawh , Sensors explored: galvanic skin response sensor, Wednesday August 24,2016 (https:\\www.wearable.com/author/m.sawh)
[5]. A.Yufera,GHueras, A Olm, A microscopic technique based on bioimpedence sensor.

Abstract: The word "vote" means to choose from a list, to elect or to determine. The main goal of voting is to come up with leaders of the people's choice. In order to provide preventive measure, the proposed project will be implemented with two security measures namely face recognition and "UNIQUE ID" Verification. Face recognition is used to verify voters, to eliminate fake votes and to eliminate repeated voting. "UNIQUE ID No." is used to fetch all the details of voter's from the database. Based on the region, voters will get list of candidates from which voter's will select one candidate. Data regarding votes and voters will be stored in main database using encryption technique. Data will be stored at only one place, so winning party information can be announced within short time period. In this paper, we present an efficient online voting system..

Keywords – Face Recognition, E-voting, One Time Password

[1]. D. Ashok Kumar, T. Ummal Sariba Begum, A Novel design of Electronic Voting System Using Fingerprint, International Journal of Innovative Technology & Creative Engineering (Issn: 2045-8711)
[2]. KashifHussainMemon, Dileep Kumar and Syed Muhammad Usman, Next Generation A Secure E-Voting System Based On Biometric Fingerprint Method, 2011 International Conference On Information And Intelligent Computing IPCSIT Vol.18
[3]. A.S. Belenky and R.C. Larson, "To Queue or not to Queue?," OR/MS 27, October 2013, pp. 30-34.
[4]. R. Krimmer (ed.), Online Voting, Proceedings of the 2nd International Workshop, Gesellschaft für Informatik, Bonn, Köllen Druck Verlag
[5]. GmbH, Bonn, October 2013.

Abstract: Nature is of course a great and immense source of inspiration for solving hard and complex problems in computer science since it exhibits extremely diverse, dynamic, robust, complex and fascinating phenomenon. It always finds the optimal solution to solve its problem maintaining perfect balance among its components. Nature inspired algorithms are Meta heuristics that mimics the nature for solving optimization problems opening a new era in computation. This paper presents a broad overview of biologically inspired optimization algorithms, such as Ant Colony Optimization (ACO), Genetic Algorithm (GA), Evolutionary Algorithm (EA) and Particle Swarm Optimization(PSO). By analyzing and investigating die rent approaches, this paper gives an overview about the researches on bio-inspired algorithm, its computations and human interaction.

Keywords:- Ant colony Optimization, Evolutionary algorithm, Genetic algorithm, Particle Swarm intelligence, Stochastic Diffusion, Artificial ant colony.

[1]. Michael Meisel a, Vasileios Pappas b, Lixia Zhang a University of California, Los Angeles, Department of Computer Science, Los Angeles, CA 90095, USAb IBM T.J. Watson Research Center, P.O. Box 704, Yorktown Heights, NY 10598, USA
[2]. Christian Blum 1 ALBCOM, LSI, UniversitatPolitècnica de Catalunya, JordiGirona 1-3, Campus Nord, 08034 Barcelona, Spain Accepted 11 October 2005
[3]. Swarm Intelligence –Introduction EVALife Group, Dept. of Computer Science, University of Aarhus ThiemoKrink
[4]. B. Atakan, O. B. Akan, An Information Theoretical Approach for Molecular Communication, in: 2nd IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2007), Budapest, Hungary, 2007.
[5]. Falko Dressler a, Ozgur B. Akan ba Computer Networks and Communication Systems, Dept. of Computer Science, University of Erlangen, Erlangen 91058, Germanyb Dept. of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey

Abstract: E-wallet Authenticated Electronic Toll Plaza is a technology enabling the electronic collection of toll payments using the RFID (Radio Frequency Identification) technology. This system is capable of determining if the car is registered or not, and then informing the authorities of toll payment violations, debits, and participating accounts. The most obvious advantage of this technology is the opportunity to eliminate congestion at tollbooths, especially during festive seasons when traffic tends to be heavier than normal. It is also a method by which to curb complaints from motorists regarding the inconveniences involved in manually making payments at the tollbooths. The E-Wallet Authenticated Electronic toll plaza is an effective and a digitalized way run the toll system on the highways..............

Keywords: Android Application, Cloud Computing, RFID Tag, RFID Reader, SMS.

[1]. Tejonidhi Aphale1, Rahul Chaudhari2, Jinit Bansod3 1,2,3Department of Electronics and Telecommunication Engineering,PVG‟s College of Engineering and Technology, Pune
[2]. AungMyint Win1, Chaw MyatNwe2, KyawZinLatt3 1 2 3Department of Electronic Engineering, Mandalay Technological University (MTU), Myanmar
[3]. Yamini S. Kale, Pooja D. Gangurde, Shruti S. Buchade, Madhuri A. Ahirrao Pune Vidyarthi Griha's College of Engineering, Dindori road,Mhasrul, Nashik. 422004

[4]. Toll Collection System by using RFID & Cloud Computing Yamini S. Kale, Pooja D. Gangurde, Shruti S. Buchade, Madhuri A. Ahirrao Pune Vidyarthi Griha's College of Engineering, Dindori road,Mhasrul, Nashik. 422004
[5]. Electronic Toll Collection System Using Passive RFID Technology. Khadijah Kamarulazizi, Dr.Widad Ismail.

Abstract: This paper focuses on the different image enhancement techniques. Image enhancement has found to be one of the most important vision applications because it has ability to enhance the visibility of images. It enhances the perceivability of poor pictures. Distinctive procedures have been proposed so far for improving the quality of the digital images. To enhance picture quality image enhancement can specifically improve and limit some data presented in the input picture. Image processing typically relies on accurate, simple...............

Keywords: Wiener filter, spatial domain, Wavelet transform, Gabor filter, ANN..

[1]. Image Enhancement Algorithm in Embedded Network Video Monitoring System 2012 978-1-4673-0915-8/12/$31.00 ©2012 IEEE
[2]. Image enhancement algorithm research based on the archives monitoring under low illumination 978-1-4799-7071-1/15/$31.00 ©2015 IEEE
[3]. Sun, Chi-Chia. Shanq-Jang Ruan. Mon-ChauShie, and Tun-Wen Pai. "Dnamic contrast enhancement based on histogram specification." Consumer Electronics, IEEE Transactions on 51, no.4(2005): 1300-1305
[4]. Mallat, S.G.: "Multifrequency channel decompositions of image and wavelet models‟, IEEE Trans. Acoust. Speech Signal Process., 1989,37, (12), pp. 2091–2110
[5]. Lu, J., Healy, D.M., and Weaver, J.B.: "Contrast enhancement of medical images using multi-scale edge repressentation‟, Opt. Eng., 1994, 33, (7),pp. 2151–2161

Abstract: Nowadays most of the citizens of India have their identity and personal documents starting from date of birth certificate, educational certificate, Voter ID, Ration Card, Driving License, vehicles registration number, PAN Card, Passport, Electricity bills, bank account numbers, insurance etc. While searching for jobs, it's mandatory to carry important documents, but this involves risk. There are chances that these documents may be lost, stolen or even sometimes people may forget to carry necessary documents. This software system transforms the paper document/identities to.............

Keywords: Digitization, Encryption, cloud storage, Rijndael encryption

[1]. N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, "Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data," IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 1, pp. 222–233, Jan. 2014.
[2]. P. Mell and T. Grance, "The NIST Definition of Cloud Computing," 2011.
[3]. Amazon, "Amazon AWS." [Online]. Available: http://aws.amazon.com/. [Accessed: 01-Jan-2015]
[4]. A Digital Envelope Scheme for Document Sharing in a Private Cloud Storage, Jedidiah Yanez-Sierra, Arturo Diaz-Perez, Victor Sosa-Sosa, J. L. Gonzalez CINVESTAV Tamaulipas – Mexico. {jyanez,adiaz,vjsosa,jgonzalez}@tamps.cinvestav.mx
[5]. DigiLocker. (2016). Digilocker.gov.in. Retrieved 4 April 2016, from https://digilocker.gov.in/www.mygov.co.in