Volume-07 , Special Issue-14 , May - 2019 Go Back

the traditional way of authenticating a user via Username and password is very much popular in digital world, where as for more security OTP is used, One Time Password is the technique which is two way authentications. This OTP technique can be used as service is cloud to users as One Time Password as service, in OTP as a cloud service some of the cloud service providers will provide this OTP for different cloud users for their online application login and website authentication. Cloud users can register their different web applications in the different cloud service. This will enable for this users access for accounts using OTP verification without maintaining many other passwords and several OTP accounts. In this paper author has given architecture for secure, privacy-friendly and trusted OTP provider and authentication phases are given. The purpose of doing survey of One Time Password as Service is to understand the need on one time password as service for authentication its fundamentals along with drawbacks of different authentication

One Time Password (OTP), Authentication, Cloud, Two-factor Authentication, Multi-factor Authentication, cloud based OTP, cloud-based authentication service

[1] Ieee transactions on information forensics and security, vol. 14, no. 3, march 2019 otpaas one time password as a service emir erdem and mehmet tahir sandkkaya ,member, ieee
[2] L. Lamport, password authentication with insecure communication, common. Acm, vol. 24, no. 11, pp. 770772, nov. 1981.
[3] N. Haller, the s/key one-time password system, document 1760,internet engineering task force, fremont, ca, usa, 1995. [online].available: https://www.ietf.org/rfc/rfc1760.txt
[4] D. Mraihi, m. Bellare, f. Hoornaert, d. Naccache, and o. Ranen,hotp: an hmac-based one-time password algorithm, document4226, internet engineering task force, fremont, ca, usa,2005. [online]. Available: https://www.ietf.org/rfc/rfc4226.txt
[5] D. Mraihi, s. Machani, m. Pei, and j. Rydell, totp: time- basedone-time password algorithm, document 6238, internet engineering task force, fremont, ca, usa, 2011. [online]. Available: https://www.ietf.org/rfc/rfc6238.txt
[6] B. Groza and d. Petrica, one time passwords for uncertain numberof authentications, in proc. 15th int. Conf. Control syst. Computer sci. (cscs), 2005, pp. 669674.
[7] M. H. Eldefrawy, m. K. Khan, k. Alghathbar, t.-h. Kim, and h.elkamchouchi, mobile one-time passwords: two-factor authentication using mobile phones, secure commun. Netw., vol. 5, no. 5, pp.508516, 2012.
[8] L. Gong, j. Pan, b. Liu, and s. Zhao, a novel one-time password mutual authentication scheme on sharing renewed finite random sub passwords, j. Comput. Syst. Sci., vol. 79, no. 1, pp. 122130, 2013.
[9] A. A. Yassin, h. Jin, a. Ibrahim, w. Qiang, and d. Zou, cloud authentication based on anonymous one-time password, in ubiquitous information technologies and applications (lecture notesin electrical engineering), y.-h. Han, d.-s. Park, w. Jia, and s.-s,yeo, eds. Ordrecht, the netherlands: springer, 2013, pp. 423431.
[10] F. Cheng, security attack safe mobile and cloud-based onetimepassword tokens using rubbing encryption algorithm, mobilenetw. Appl., vol. 16, no. 3, pp. 304336, 2011.
[11] B. Vaidya, j. H. Park, s.-s. Yeo, and j. J. Rodrigues, robust one time password authentication scheme using smart card for home network environment, comput. Commun., vol. 34, no. 3, pp. 326336,2011.
[12] K.-c. Liao, w.-h. Lee, m.-h. Sung, and t.-c. Lin, a one-time password scheme with qr-code based on mobile phone, in proc.5th int. Joint conf. Inc. (ims idc), 2009, pp. 20692071.
[13] Yubikey. Accessed: mar. 20, 2017. [online]. Available: https://www.yubico.com
[14] Google authenticator. Accessed: mar. 20, 2017. [online]. Available: https://github.com/google/google-authenticator/wiki

Siddharth S. Gosavi, Gopal k Shyam, "Survey on Enhancement of One Time Password as a Service (OTPaaS)", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.193-198, 2019.

The coin based mobile battery proposed in this paper provides services to rural where grid power is unavailable for large duration to charge their phones. Installation of battery charger is quick and easy. Urban population uses advanced technological mobile that have batteries with higher storage, while people in rural cannot afford such expense. Sources are direct power grid and solar energy respectively in rural areas.

Microcontroller, UART Serial Channel, LCD, In-System Programmable

[1] Fukumi.M, Mitsukura.Y, Norio Akamatsu, (2000), Design and Evaluation of neural Networks for Coin Recognition by using GA and SA‟, IEEE, pp 178-183.
[2] Thumwarin. P, S.Malila, P.Janthawang, W.Pibulwej, T.Matsura, (2006), A Robust Coin Recognition method with rotation Invariance‟, IEEE, pp. 520-523.
[3] Velu, C. M. and Vivekanandan, P. “Indian Coin Recognition System of Image Segmentation by Heuristic Approach and Hough Transform (HT)”, International Journal of Open Problems in Computational Mathematics, Vol. 2, No 2, pp. 254-271,2009.
[4] Bremananth.R, B.Balaji, M.Sankari, A.Chitra, (2005), A New approach to Coin recognition using Neural Pattern Analysis‟, IEEE Indicon Conference, pp. 366-370

Mylara Reddy, Sai Charan, Akshay R, Badrinath N, Rakshith S N, "Mobile Charging On Coin Insertion", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.199-201, 2019.

Photograph sharing is a tempting feature which popularizes online social networks. It might liberate user’s secrecy if users are agreed to post, tag, comment, mention a photo publicly. In this paper we address this problem and learn the case when a user posts a photo having individuals excluding her/him. To stop the security dropout of a photo we plot a system that permit everyone in a photograph be alert about the photo uploading action and join in the judgment of photo uploading activity. To achieve this motive FR system needed which identifies individuals in the photograph. However requesting extra security can restrain the quantity of photos freely accessible to prepare the Face recognition technique. To control such problem proposed system endeavors to utilize user’s personal photos for outline a individualized Face recognition system specifically made for distinct probable photo co-possessor with covering their secrecy. We evolve a distributed consensus system to minimize the computational miscellaneous and defend the personal instructing data.

online Social networks, photo secrecy, FR system, support vector machine, collaborative learning

[1] A. Besmer and H. Richter Lipford. Moving beyond untagging: photo privacy in a tagged world. In proceedings of the SIGCHI conference on Human Factors in Computing Systems, CHI ’10, PAGES 1563-1572, New York, NY, USA, 2010. ACM.
[2] J. Y. Choi, W. De Neve, K. Plataniotis, and Y.-M. Ro. Collaborative face recognition for improved face annotation in personal photo collections shared on online social networks. Multimedia, IEEE Transaction on, 13(1):14-28, 2011.
[3] N. Mavridis, W. Kazmi, and P. Toulis. Friends with faces: How social networks can enhance face recognition and vice versa. In Computational Social Networks Analysis, Computer Communications and Networks, pages 453-482. Springer London, 2010.
[4] I. Altman. Privacy regulation: Culturally universal or culturally specific? Journal of social issues, 33(3):66-84.
[5] A. C. Squiccarini, M. Shehab, and F. Paci. Collective privacy management in social networks. In Proceeding of the 18th International Conference on World Wide Web, WWW ’09, pages 521-530, New York, NY, USA, 2009. ACM.
[6] Z. Stone, T. Zickler, and T. Derrell. Toward large-scale face recognition using social network context. Proceeding of the IEEE, 98(8):1408-1415.
[7] Z. Stone, T. Zickler, and T. Derrell. Autotagging facebook: social network context improves photo annotation. In Computer Vision and Pattern Recognition Workshop, 2008. CVPRW’08. IEEE Computer Society Conference on, pages 1-8. IEEE, 2008.
[8] Kaihe Xu, Yuanxiong Guo, Linke Guo, Yuguang Fang, Xiaolin Li. My Privacy My Decision: Control of Photo Sharing on Online Social Networks, IEEE Transaction on Dependable and Secure Computing, April 2017.

Rekha, Venkatesh Prasad, "Preventing Privacy Leakage of Photo Sharing on Online Social Networks", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.202-205, 2019.

In the recent years, many companies and organizations are using traditional biometric attendance system for taking attendance of it’s workers or employees. This will keep track of employee’s attendance i.e he has logged into the office or not but it will not keep track of whether the employee is present at the workplace or not. In this modern era, it is seen that after giving attendance many employees fly away from their workplace to escape from doing work. This paper focuses on Android Attendance system where an Android device will be used instead of Biometric Attendance System. Here, the entire workplace will be a wife zone. An android application will be developed in java and android and installed into employee mobile phone which connects to wifi whenever the employee enters the wifi zone. So connection or disconnection of mobile phone to the wifi will determine whether the employee is present in the workplace or not.

Server, wifi, android attendances, admin, mobile phone

[1] Dhiman Kumar Sarker, Nafize Ishtiaque Hossain, and Insan Arafat Jamil, “Design and implementation of smart attendance management system using multiple step authentication” in Computational Intelligence (IWCI), International Workshop on. IEEE, 2016, pp. 91–95.
[2] M.K.Yeop,M.Z.A.AbdulAziz,M.S.R.MohdShah,M.F.AbdKadir”Smart Attendance System by using RFID”Asia-Pacific Conference on Applied Electromagnetics 2007l, Biometric Sensors Types and Its Working, 2014.
[3] Siti Aisah Mohd Noor,Norliza Zaini,Mohd Fuad Abdul Latip Nabilah Hamzah”Andriod –based attendance management system”2015 IEEE Conference on Systems,Process and Control(ICSPC).
[4] Shota Noguchi,Michitoshi Niibori,Erjing Zhou,Masaru Kamada”Student Attendance Management System with Bluetooth Low Energy Beacon and Andriod Devices”2015 18th International Conference on Network-Based Information Systems
[5] T. Agarwal, Biometric Sensors Types and Its Working, 2014[Online]. Available: https://www.elprocus.com/differenttypes-biometric-sensors.

Matle Venkata Anusha, Nagaveni M, Giraddi. R Satyaraddi, Anilkumar Ambore, "Android Attendances System Using Wifi", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.206-209, 2019.

Humans communicate with one another not solely through their vocal talents however additionally through the gestures that they create. A gesture will go an excellent approach in golf shot through our purpose and creating the opposite person perceive U.S. and computers are not any totally different during this and may be controlled and created to retort handy and head gestures employing a gesture recognition system. during this project a gesture recognition models is meant that acknowledge hand or head gestures that`s down ,up, left, right and cross, supported the signal from three-axis measuring device. Mouse management supported Gesture entomb action takes advantage of continuity and dynamics of the user’s movement of the hand to regulate the mouse movement. Once there`s any movement of the body there`s generation of signal however common supply is face or hand. This project presents the maneuver of mouse pointer and performs numerous operations like left click, right click, double click and gap and shutting a folder by blinking your eyes. Recognizing gestures may be advanced task that involves several aspects like motion modelling, motion analysis and pattern recognition. Therefore for recognizing the gestures numerous mouse events are performed.

Gesture Recognition System (GRS), Three-axis accelerometer, Head Gesture

[1] Granit Luzhnica, Elizabeth Lex, Viktoria Pammer. A Sliding Window Approach to The Natural Hand Gesture Recognition using a Custom DataGlove. In: 3D User Interfaces (3DUI); 2016 IEEE Symposium on ; 2016 Mar 19 ; New York : IEEE; 2016 ; p.81-90.
[2] Ji-Hwan Kim,Nguyen Duc Thang,Tae-Seong Kim. 3-D hand Motion Tracking and Gesture Recognition Using the Data Glove. In; Industrial Electronics; 2009 IEEE International Symposium on; 2009 July 5; New York: IEEE; 2009 ; p.1013-1018.
[3] Hung CH, Bai YW, Wu HY. Home outlet and the LED array lamp controlled by a smartphone with a hand gesture recognition. In: Consumer Electronics (ICCE); 2016 IEEE International Conference on ; 2016 Jan 7; New York : IEEE;2016 ; p.5-6.
[4] Hung CH, Bai YW, Wu HY. Home appliance control by a hand gesture recognition belt in LED array lamp case. In: Consumer Electronics (GCCE); 2015 IEEE 4th Global Conference on ; 2015 Oct 27; New York : IEEE;2015; p. 599-600
[5] She Y, Wang Q, Jia Y, Gu T, He Q, Yang B. A real-time hand gesture recognition approach based on motion features of the feature points. In Computational Science and Engineering (CSE); 2014 IEEE 17th International Conference on; 2014 Dec 19; New York: IEEE;2014;p.1096-1102.
[6] Lee DH, Hong KS. A Hand gesture recognition system based on the difference image entropy. In: Advanced Information Management and Service (IMS), 2010 6th International Conference on; 2010 Nov 30; Seoul; New York: IEEE; 2010 ; p. 410-413.
[7] Dulayatrakul J, Prasertsakul P, Kondo T, Nilkhamhang I. Robust implementation of hand gesture recognition for the remote human-machine interaction. In Information Technology and Electrical Engineering (ICITEE); 2015 7th International Conference on ;2015 Oct 29; p. 247-252.
[8] Tsai TH, Huang CC, Zhang KL. Embedded virtual mouse system by using the hand gesture recognition. In: Consumer Electronics-Taiwan (ICCE-TW); 2015 IEEE International Conference on; 2015 Jun 6; Taiwan, Taipei; New York: IEEE; 2015; p. 352-353.
[9] Adnan Ibraheem and Rafiqu Izaman Khan, “Survey on Various Gesture Recognition Technologies and Techniques”, International Journal of Computer Applications p.0975 –8887 Volume 50 – No.7, July 2012.

Aruna Kumara B, T.Hashmitha, Swathi S.G, Swathi G, Vineeth P, "Recognizing Mouse events through Head/Hand movement", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.210-213, 2019.

Cloud cache is a use of mists that release associations from developing administrative information stockpiling frameworks. Be that as it may, distributed storage offers ascend to security concerns. If there should arise an occurrence of gathering shared information, the information faces particular cloud and ordinary insider dangers. Protect information distribution in a gathering conflict inside dangers vindictive clients is an essential analysis problem. We propose this system,which gives: 1) info hiding and trustworthiness; 2) get to control; 3) info distribution without utilizing register serious reencryption; 4) internal danger security; and 5) forward and in reverse access control. The Secure information partaking in cloud approach encodes a folder with a key with solitary encryption. Two diverse key offers for every client are created, with client just having one offer. The ownership of a solitary offer of a key enables this strategy to counter the insider dangers. The alternative key offer is put away by a confided in outsider, which is known as the cryptographic server. This philosophy is relevant to customary and portable distributed estimating situations.

Access control, distributed computing, abnormal state Petri nets, displaying, Satisfiability Modulo Theory, Scythe.

[1] K. Alhamazani et al., “An overview of the commercial cloud monitoring tools: Research dimensions, design issues, state-of-the-art,” Computing, DOI: 10.1007/s00607-014-0398-5, 2014, to be published.
[2] A. N. Khan, M. L. M. Kiah, S. U. Khan, and S. A. Madani, “Towards secure mobile cloud computing: A survey,” Future Gen. Comput. Syst.,
[3] A. Abbas and S. U. Khan, “A review on the State-of-the-art privacy preserving approach esine-health clouds,IEEEJ. Biomed. HealthInformat., vol. 18, no. 1, pp. 1431–1441, Jul. 2014.

Sowmya Sundari L K, Pallavi K R, P. Bhavya Shree, P. Lakshmi Viharika, R. Hari Chandana, "Secured Data Sharing in Clouds", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.214-217, 2019.

Private web Hosting for Confidential information is a web application is mainly designed and developed to focus on cost management of various distributed cloud computing administrations and models that are utilized by business stages like DevOps/IT Organizations for using the web service like storage. In a distributed computing approach cost depends on measure of information stockpiling and hour of upkeep so cloud service provider will fix the expense for User information. In our application the cost of information will vary from text, picture ,video. Assume the user will upload image to the cloud, the service cost of image is higher when compared to text .The application also focuses on the key aspect of the application that is pay per use of the service the payments are done only for the resources that are utilized at specific duration by the user where overcoming the major drawback in the models that where designed earlier where the users had to take either the yearly plan or the monthly plan but now we have an advancement ie pay per use which is a major change that has been implemented in this application. The user can store possess information in distributed storage zone. They can see distributed storage information whenever from any place subsequently making it best and convenient application. The User should pay for the storage cost just which is having incorporated capacity and propelled security turns out to be progressively solid. This administration has just been fused of utilizing such administrations in numerous IT, business divisions for expansive capacity of business confidential information and completely annulling the future crisis with incredible administration and security

centralized storage, confidential, Cloud Computing, Web Host, Storage

[1] Mayuri R. Gawande, International Journal of Computer Science and Mobile Computing, Vol.3, issue.3, March-2014, pg. 169-175, 2014.
[2] http://www.wallstreetandtech.com/technology-risk-management/the-holy-grail-of-cloud-computing-maint/240006774.
[3] NIST Special Publication 500–291 version 2, NIST Cloud Computing Standards Roadmap, July 2013, Available at http://www.nist.gov/itl/cloud/publications.cfm.
[4] Chunye Gong, Jie Liu, Qiang Zhang, Haitao Chen and Henghu Gong, The Characteristics of Cloud Computing, IEEE International Conference on Parallel Processing Workshops, 2010, pp. 275-279.
[5] Ryan K L Ko etal..‘Trustcloud: a framework for accountability and trust in cloud computing.’IEEE World Congress on Services, pp584-588, 2011

N.S.Nikhil, Nonika Sharma, N. Prashanth, M. Harini, Chaithra M H, "Private Web hosting for Confidential Data using Cloud", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.218-223, 2019.

Machine Learning has several applications in Healthcare Domain. It provides more efficient, faster, smarter ways to detect and cure various diseases. Machine learning approaches are widely used for cancer diagnosis. In our approach we classify cancerous and noncancerous Oral Cancer images. We focused on image pre-processing, segmentation using image segmentation app in Matlab to improve the image quality and thereby improving the accuracy of classification and cancer detection. This approach using Support Vector Machines (SVM) obtained an accuracy of 89.2%. This method can be easily adopted for early cancer detection.

Machine Learning,Oral Cancer, Image Segmentation, Support Vector Machines

[1] Van Dyck, &, W Stremersch S, “Marketing of the LifeSciences: A New Framework and Research Agenda for a Nascent Field”. Journal of Marketing, 73(4), 430, 2009
[2] Rowlands, S., Coverdale, S., & Callen, J, “Documentation of clinical care in hospital patients’ medical records: A qualitative study of medical students’ perspectives on clinical documentation education”. Health Information Management Journal, 45(3), 99–106, 2016
[3] Lenzer, Jeanne, “Claim that smallpox vaccine protects against HIV is premature, say critics.” BMJ (Clinical research ed.) vol. 327,7417: 699. doi:10.1136 /bmj.327.7417.699, 2003
[4] F., Abdolali, R. A., Zoroofi, Y., Otake, &Y., Sato, “Automated classification of maxillofacial cysts in cone beam CT images using contour less transformation and Spherical Harmonics,” Computer Methods and Programs in Biomedicine, 139, 197-207, 2017.
[5] Early stage oral cavity cancer detection: Anisotropic pre-processing and fuzzy C-means segmentation 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018, Volumes 2018-January, 2018
.[6] T, Karthikeyan, “Unified RF-SVM model based digital radiography classification for Inferior Alveolar Nerve Injury (IANA) identification,” Biomedical Research, 27(4), 2016.
[7] Amin, Javeria, et al. "A distinctive approach in brain tumor detection and classification using MRI." Pattern Recognition Letters ,2017.
[8] S.-W.,Chang, S., Abdul-Kareem, A.F.,Merican, & R. B. , Zain, “ Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods,” BMC Bioinformatics, 14(1), 2013.
[9] S., Galib, F., Islam, M., Abir& H.-K. , Lee, “Computer aided detection of oral lesions on CT images,” Journal of Instrumentation, 10(12), 2015.
[10] M. M. R., Krishnan, P., Shah, C. Chakraborty, & A. K., Ray, “Statistical analysis of textual features for improved classification of oral histopathological images,” Journal of medical systems, 36(2) , 2012.
[11] I., Nurtanio, E. R., Astuti, I. K. E., Purnama, M., Hariadi, & M. H. , Purnomo, “ Classifying cyst and tumor lesion using support vector machine based on dental panoramic images texture features,” IAENG International Journal of Computer Science, 40(1), 29-37, 2013.
[12] K., Nguyen, A. K., Jain, & R. L., Allen,” Automated Gland Segmentation and Classification for Gleason Grading of Prostate Tissue Images,” 20th International Conference on Pattern Recognition, 23-26, 2010.
[13] N. P., Malek, S., Schmidt, P., Huber, M. P., Manns,T.F.Greten, “The diagnosis and treatment of hepatocellular carcinoma,” Alcohol, 20, 2014.

Anooja Ali, Pooja G, Prajeela MP, Riddhi Rakesh, Tabassum Taj, "Machine Learning Approach for Cancer Detection", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.224-228, 2019.

Hand gesture is one of the most primitive ways of communication and is an area of dynamic examination for computer based vision and AI. This is a zone with numerous potential applications, giving clients a simpler and extra normal approach to speak with robots/system interfaces, without the need of any additional gadgets. In this way, the main objective of hand gesture recognition connected to Human-Computer Interaction (HCI) is to shape frameworks, which may decide explicit human motions and use them to pass on data and control gadgets. For that, vision-based hand gesture interfaces need fast signal acknowledgments continuously. This paper proposes the utilization of hand gestures and the utilization of three dimensional (3D) pivot of hand motions as the reason for clients to communicate with a computer. This paper presents strategies for Game Play utilizing both Image Processing strategy and Arduino combined with a sensor.

Gesture recognition, Image processing, Feature extraction, Human Computer Interaction, MATLAB, Controller, ADXL335 Accelerometer

[1] Archana S. Ghotkar, Gajanan K. Kharate,”Hand Segmentation Techniques to Hand Gesture Recognition for Natural Human Computer Interaction”. International Journal of Human Computer Interaction (IJHCI), Volume (3): Issue (1): 2012
[2] [2] Harshith.C, Karthik.R.Shastry, Manoj Ravindran, M.V.V.N.S Srikanth,”Survey on various Gesture Recognition Techniques for Interfacing Machine Based on Ambient Intelligence”. (IJCSES) Vol.1 No.2, November 2010
[3] SunitaPatidar, Dr. C.S.Satsangi,”Hand Segmentation And Tracking Technique Using Color Models”. International Journal of Software & Hardware Research in Engineering volume (1) Issue (2), October 2013
[4] P. C. Badhe and V. Kulkarni, "Indian sign language translator using gesture recognition algorithm," 2015 IEEE International Conference on Computer Graphics, Vision and Information Security (CGVIS), Bhubaneswar, 2015, pp. 195-200
[5] Madhuri Sharma, Ranjna Pal and Ashok Kumar Sahoo “,Indian Sign Language Recognition Using Neural Networks and KNN Classifiers”, ARPN Journalof Engineering and Applied Sciences, Vol. 9
[6] K. Dixit and A. S. Jalal, "Automatic Indian Sign Language recognition system," Advance Computing Conference (IACC),2013 IEEE 3rd International, Ghaziabad, 2013, pp. 883-887
[7] J.R.Parker, “Algorithms for Image Processing and Computer Vision”, Edition 2, 2011, Print.
[8] Rafael C. Gonzalez and Richard E.Woods. “Digital Image Processing – Image Segmentation”, India, Published by Dorling Kindersley (India) Pvt. Ltd, 2011, Print.
[9] Thomas B. Moeslund and Erik Granum, (2001). “A Survey of Computer Vision-Based Human Motion Capture,” Elsevier, Computer Vision and Image Understanding, Vol. 81, pp. 231–268.
[10] N. Ibraheem, M. Hasan, R. Khan, P. Mishra, (2012). “Comparative study of skin color based segmentation techniques”, Aligarh Muslim University, A.M.U., Aligarh, India.
[11] Mahmoud E., Ayoub A., J¨org A., and Bernd M., (2008). “Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition”, World Academy of Science, Engineering and Technology 41.
[12] E. Stergiopoulou, N. Papamarkos. (2009). “Hand gesture recognition using a neural network shape fitting technique,” Elsevier Engineering Applications of Artificial Intelligence, vol. 22(8), pp. 1141– 1158, doi: 10.1016/j.engappai.2009.03.008
[13] M. M. Hasan, P. K. Mishra, (2011). “HSV Brightness Factor Matching for Gesture Recognition System”, International Journal of Image Processing (IJIP), Vol. 4(5).
[14] Malima, A., Özgür, E., Çetin, M. (2006). “A Fast Algorithm for Vision-Based Hand Gesture Recognition for Robot Control”, IEEE 14th conference on Signal Processing and Communications Applications, pp. 1-4. doi: 10.1109/SIU.2006.1659822
[15] Mokhar M. Hasan, Pramod K. Mishra, (2012) “Features Fitting using Multivariate Gaussian Distribution for Hand Gesture Recognition”, International Journal of Computer Science & Emerging Technologies IJCSET, Vol. 3(2).
[16] Mokhar M. Hasan, Pramod K. Mishra, (2012). “Robust Gesture Recognition Using Gaussian Distribution for Features Fitting”, International Journal of Machine Learning and Computing, Vol.2 (3).
[17] Sagar P.More, Prof. Abdul Sattar, “Hand gesture recognition system for dumb people”.
[18] Chandandeep Kaur, Nivit Gill, “An Automated System for Indian Sign Language Recognition”, International Journal of Advanced Research in Computer Science and Software Engineering.
[19] Neelam K. Gilorkar, Manisha M. Ingle, “Real Time Detection And Recognition Of Indian And American Sign Language Using Sift”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 5, Issue 5, pp. 11-18 , May 2014
[20] “HAND GESTURE RECOGNITION: A Literature Review”, Rafiqul Zaman, Khanand Noor, Adnan Ibraheem, 2012, Department of Computer Science, A.M.U. Aligarh, India.
[21] "Hand-gesture recognition using computer-vision techniques", 2013, David J. Rios-Soria, Satu E. Schaeffer, Sara E. Garza-Villarreal, Universidad Autónoma de Nuevo León (UANL) San Nicolás de los Garza, NL, Mexico.
[22] “Hand Gesture Recognition System to Control Slide Show Navigation”, 2014, Dnyanada Jadhav, Prof. L.M.R.J. Lobo, Walchand Institute of Technology, Solapur.
[23] “Hand gesture recognition system”, 2015, Prof. Praveen D. Hasalkar1, Rohit S. Chougule, Vrushabh B. Madake, Vishal S. Magdum, Department of Computer Science and Engineering, Walchand Institute of Technology, W.I.T, Solapur, Maharashtra, India.
[24] “Interaction with Virtual Game through Hand Gesture Recognition”, 2011, Siddharth S. Rautaray and Anupam Agrawal, Indian Institute of Information Technology, Allahabad.

Shruthi G, Praharsh R, R Durga Sai Eswar, Ramya V, "Image processing and Controller Based Game Play Using Hand Gestures", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.229-233, 2019.

In a square chain IoT condition, when information or gadget confirmation data is put on a square chain, individual data might be spilled through the verification of-work procedure or address look. In this paper, we apply ZeroKnowledge confirmation to a savvy meter framework to demonstrate that a prover without uncovering data, for example, open key, and we have contemplated how to upgrade secrecy of square chain for security insurance. In this paper, we present a simple to-utilize NFC-based arrangement approach for IoT gadgets that is verified by fitting safety efforts in programming and equipment. Since modern utilization of such a setup approach involves unexpected necessities in comparison to home use, we present and analyze three unique design forms. The relevance of our methodology is exhibited by two prototypical executions, just as an itemized security investigation. We additionally demonstrate that the forced overhead because of the actualized safety efforts is immaterial for most setup refreshes.

Component Near Field Communication,Zero Knowledge Technology,Service Provider

[1] E. Bertino and N. Islam, “Botnets and Internet of Things security,” Computer, vol. 50, no. 2, pp. 76–79, Feb. 2017.
[2] D. Perakovic, M. Periša, and I. Cviti ´ c, “Analysis of the IoT impact on ´ volume of DDoS attacks,” in Proc. 33rd Symp. New Technol. Postal Telecommun. Traffic (PosTel), 2015, pp. 295–304.
[3] Y. M. P. Pa et al., “IoTPOT: Analysing the rise of IoT compromises,” in Proc. 9th USENIX Conf. Offensive Technol., Washington, DC, USA, 2015, p. 9.
[4] A.-R. Sadeghi, C. Wachsmann, and M. Waidner, “Security and privacy challenges in industrial Internet of Things,” in Proc. 52nd ACM/EDAC/IEEE Design Autom. Conf. (DAC), San Francisco, CA, USA, 2015, pp. 1–6.
[5] T. Ulz et al., “SECURECONFIG: NFC and QR-code based hybrid approach for smart sensor configuration,” in Proc. IEEE Int. Conf. RFID (RFID), Phoenix, AZ, USA, 2017, pp. 1–6.
[6] J. Haase, D. Meyer, M. Eckert, and B. Klauer, “Wireless sensor/actuator device configuration by NFC,” in Proc. IEEE Int. Conf. Ind. Technol. (ICIT), 2016, pp. 1336–1340.
[7] Andreas M, Masteing Bitcoin: Unlocking Digital Cryptocurrencies, pp.49-68, O’REILLY, 2015.
[8] Sung-Hoon Lee, Device authentication in Smart Grid System using Blockchai, KAIST, 2016.
[9] Buterin’s Idea to Release, 2015.
[10] Surae Noether, Review of Ctyptonote White Paper, 2016
[11] Evan Duffield,Daniel Diaz ,Dash: A Privacy-Centric Crypto-Currency, 2015.

TM.Yasmeen, Zaiba Sultana F, Zuha Fathima S.K, Basavaraj S.H, "Implementation of IoT Framework Utilizing Blockchain with Validation and Information Assurance with NFC Innovation", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.234-238, 2019.