A Novel Approach of Card Payment to Avoid Shoulder Surfing Attacks

Authors: Akanksha Gat, Neha Bhosale, Harshada Deshmukh, Snehal Gore, Shwetambari Chiwhane

Abstract— As per the recent Reserve Bank of India Mandate, the customers who have used their credit card at an international Point of Sale (POS) terminal will have to be re-carded with a Chip+PIN credit card. A chip is a small microchip embedded in customer’s credit card. Chip is encrypted so transactions are more secure on the card. The Chip+PIN card is a most superior level of security on customer’s card, in line with best global practice of security of transactions. When customer uses a Chip+PIN credit card at a Point of Sale terminal, the Point of Sale (POS) machine will prompt customer for his/her PIN to be entered, you are required to enter the Credit Card or ATM PIN in the terminal and complete the transaction. To complete the transaction we need to provide 4 digit PIN number into that device. We suspect a security thread in this process. While providing PIN in front of friends, relative or unknown person, it is affected by “Shoulder attacks”.

Keywords— Cloud Security, Shoulder Attack, Card Payment Security

References-

[1] Veerraju Gampala, Srilakshmi Inuganti, Satish Muppidi,”Data Security in Cloud Computing with Elliptic Curve Cryptography”, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume 2, Issue 3, July 2012.

[2] Gayatri Kulkarni , Pranjali Gujar, Madhuri Joshi, Shilpa Jadhav,”Message Security Using Armstrong Numbers and Authentication Using Colors”, International Journal of Advanced Research in Advance Computer Science and Software Engineering ISSN:2277 128X, Volume 4, Issue 1, January 2014

[3] J.Rajalakshmi and V.Valarmathi Assistant Professor, “Preventing Human Shoulder Surfing and to Provide Resistence Against Pin Entry” International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) ISSN: 0976-1353 Volume 13 Issue 1, March 2015.

[4] Mun-kyu,”Security Notions and Advanced method for Human Shoulder- Surfing Resistant PIN entry”,IEEE Transactions on Information Forensics and Security, Volume 4,No 4,April 2014

Secure Transmission of Hard Copy to Soft Copy Using OCR and Data Hiding Technology

Authors: Riya. P. Ahuja, Mohini. R. Pasalkar, Ameya. J. Jadhav, Swati Shirke

Abstract— Most of the times you have to face this situation that you need the matter which you have in hard copy into a soft copy, like any official paper, notes etc. That you have in hard copy but you want them into a soft copy. So that you can use them through system or you can use them as your security purpose. What will you do to face this kind of a problem? Will you type all those papers or matter to get them into soft copy? In this article we will see how to convert your hard copy into a soft copy by using OCR and also for secure transmission by using data hiding techniques because Information hiding has importance in information security. With the help of a scanner or MFD you get software which is called OCR. Which converts your hard copy into soft copy, but when this copy is to be secure that is information is to be hidden. The soft copy which you get is encrypted into an image a Steganography is used for information hiding. Where Edge adaptive image steganography based on LSB is a popular type of steganographic algorithms used for hiding image in secured manner.

Keywords—Opticalcharacterrecognition, Multi-function device, encrypt, Steganography, EDGE, List-significant bit.

References-

[1] K. Naveen BrahmaTeja1, Dr. G. L. Madhumati 2, K. Rama Koteswara Rao. International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 11, November 2012).Data Hiding Using EDGE Based Steganography.

[2] Weiqi Luo, Member, IEEE, Fangjun Huang, Member, IEEE, and Jiwu Huang, Senior Member, IEEE. Edge Adaptive Image Steganography Based on LSB.Matching Revisited. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 5, NO. 2, JUNE 2010

[3] Nadeem Akhtar, Shahbaaz Khan, Pragati Johri. An Improved Inverted LSB Image Steganography. 978-1-4799-2900- 9/14/$31.00 ©2014 IEEE

[4] Mehdi Hussain, M. Hussain. Information Hiding Using Edge Boundaries of Objects. International Journal of Security and Its Applications Vol. 5 No. 3, July, 2011

[5] Susan Wiedenbeck, Jean-Camille Birget, Alex Brodskiy. Optical Character Recognition. IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 46, NO. 1, MARCH 2014

Vision Based Hand Gesture Recognition For Real Time Home Automation Application

Authors: Sagar Shimpi, Dashrath Mundkar, Rishikesh Shinde, Prajakta Nivangune, Priyanka Lanjewar, A. R. Sonawane

Abstract— We are proposing a fast algorithm for automatically identifying a limited set of gestures from hand images for home automation purpose. Gesture recognition is a challenging problem in its normal form. We are going to consider a stable set of manual commands and a reasonably organized environment, and develop a basic, so far effective, method for hand gesture recognition. Our methodology contains steps for segmenting the hand region, locating the fingers, and finally classifying the gesture. The algorithm is constant to rotation, translation and scale of the hand gesture. Now We describe the efficiency of the technique on real imagery.

Keywords— detection, hand gesture, home automation, recognition, robot control.

References-

[1] J. Davis and M. Shah "Visual Gesture Recognition", IEE Proc.-Vis. Image Signal Process., Vol. 141, No.2, April 1994.

[2] C.-C. Chang, I.-Y Chen, and Y.-S. Huang, "Hand Pose Recognition Using Curvature Scale Space", IEEE International Conference on Pattern Recognition, 2002.

[3] A. Utsumi, T. Miyasato and F. Kishino, "Multi-Camera Hand Pose Recognition System Using Skeleton Image", IEEE International Workshop on Robot and Human Communication, pp. 219-224, 1995.

[4] R. Rosales, V. Athitsos, L. Sigal, and S. Sclaroff, "3D Hand Pose Reconstruction Using Specialized Mappings", IEEE International Con. on Computer Vision, pp. 378- 385, 2001.

[5] C. Tomasi, S. Petrov, and A. Sastry, "3D = Classification + Interpolation", IEEE International Conf. on Computer Vision, 2003.

[6] W. T. Freeman and M. Roth, "Orientation Histograms for Hand Gesture Recognition", IEEE International Conf. on Automatic Face and Gesture Recognition, 1995.

[7] L. Bretzner, I. Laptev, and T. Lindberg, "Hand Gesture Recognition using Multi-Scale Color Features, Hierarchical Models and Particle Filtering", IEEE International Conf. on Automatic Face and Gesture Recognition, 2002.

[8] J. Brand and J. Mason, "A Comparative Assessment of Three Approaches to Pixel-level Human Skin Detection", IEEE International Conference on Pattern Recognition, 2000.

Palm Vein Pattern Authentication Technology

Authors: Pruthvi S. Ghael, Shubham S. Zunzunwala, Surbhi S. Thole, Tripti R. Kak, Pallavi T. Suradkar

Abstract- A contactless palm vein pattern authentication technology that uses vein patterns for biometric identification. This recognition technology is secure because the pattern that lies inside the body and as a result it is very difficult to copy. It is very much accurate — in a test using 140,000 palm patterns of 70,000 people, it had a false rejection rate of about 0.01%* and false acceptance rate which is not more than 0.00008%.

Keywords- Contactless palm vein authentication, NearInfrared, PalmSecure, Reflection photography, Vascular pattern authentication.

References-

[1] Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on (Volume:1 )

[2] Computer Sciences and Applications (CSA), 2013 International Conference

[3] Information Science and Applications (ICISA), 2013 International Conference

[4] R. Brunelli, D. Falavigna, "Person identification using multiple cues," IEEE Transactions on Pattern Analysis and Machine Intelligence 1995

[5] L. Wang, G. Leedham and Siu-Yeung Cho, Minutiae Feature Analysis for Infrared Hand Vein Pattern Biometrics,” Pattern Recognition, 41(3),2008