A New Cheating Prevention Scheme For Visual Cryptography 第十六屆全國資訊安全會議 Jun 8 2006 Du-Shiau Tsai ab,Tzung-her Chen c and Gwoboa Horng a a Department of Computer.

Slides:



Advertisements
Similar presentations
Visual Cryptography Moni Naor Adi Shamir Presented By:
Advertisements

多媒體網路安全實驗室 An efficient and security dynamic identity based authentication protocol for multi-server architecture using smart cards 作者 :JongHyup LEE 出處.
Cheating prevention in visual cryptography Author: C.M. Hu and W.G. Tzeng Source: IEEE-TIP 2007 Presenter: Yu-Chi Chen Date: /4/13 1.
1 Visual Cryptography: Secret Sharing without a Computer Ricardo Martin GWU Cryptography Group September 2005.
國立暨南國際大學 National Chi Nan University A Study of (k, n)-threshold Secret Image Sharing Schemes in Visual Cryptography without Expansion Presenter : Ying-Yu.
IEEE TRANSACTIONS ON IMAGE PROCESSING,2007 指導老師:李南逸 報告者:黃資真 Cheating Prevention in Visual Cryptography 1.
Visual Cryptography Jiangyi Hu Jiangyi Hu, Zhiqian Hu2 Visual Cryptography Example Secret sharing Visual cryptography Model Extensions.
Edith C. H. Ngai1, Jiangchuan Liu2, and Michael R. Lyu1
1 視覺密碼學 Chair Professor Chin-Chen Chang ( 張真誠 ) National Tsing Hua University ( 清華大學 ) National Chung Cheng University ( 中正大學 ) Feng Chia University (
Data classification based on tolerant rough set reporter: yanan yean.
5. Halftoning Newspaper photographs simulate a greyscale, despite the fact that they have been printed using only black ink. A newspaper picture is, in.
Efficient fault-tolerant scheme based on the RSA system Author: N.-Y. Lee and W.-L. Tsai IEE Proceedings Presented by 詹益誌 2004/03/02.
Halftoning Technique Using Genetic Algorithm Naoki Kobayashi and Hideo Saito 1994 IEEE.
1 Hidden Exponent RSA and Efficient Key Distribution author: He Ge Cryptology ePrint Archive 2005/325 PDFPDF 報告人:陳昱升.
(r, n)-Threshold Image Secret Sharing Methods with Small Shadow Images Xiaofeng Wang, Zhen Li, Xiaoni Zhang, Shangping Wang Xi'an University of Technology,
Interaction of water waves with an array of vertical cylinders using null-field integral equations Jeng-Tzong Chen 1 ( 陳正宗 ) and Ying-Te Lee 2 ( 李應德 )
Seeing-Is-Believing: Using Camera Phones for Human- Verifiable Authentication Jonathan M. McCune Adrian Perrig Michael K. Reiter Carnegie Mellon University.
Attention Deficit Hyperactivity Disorder (ADHD) Student Classification Using Genetic Algorithm and Artificial Neural Network S. Yenaeng 1, S. Saelee 2.
Security and Protection of Information, Brno Using quasigroups for secure encoding of file system Eliška Ochodková, Václav Snášel
1 Template-Based Classification Method for Chinese Character Recognition Presenter: Tienwei Tsai Department of Informaiton Management, Chihlee Institute.
Different Types of Fields to Describe the Earth. Anisotropy, heterogeneity SEM of shale (Josh et al., 2012)
Arindam K. Das CIA Lab University of Washington Seattle, WA MINIMUM POWER BROADCAST IN WIRELESS NETWORKS.
Cryptanalysis and Improvement of an Access Control in User Hierarchy Based on Elliptic Curve Cryptosystem Reporter : Tzer-Long Chen Information Sciences.
Yu-Li Lin and Chien-Lung Hsu Department of Information Management, Chang-Gung University Information Science(SCI) Reporter: Tzer-Long Chen.
D´ej`a Vu: A User Study Using Images for Authentication Rachna Dhamija,Adrian Perrig SIMS / CS, University of California Berkeley 報告人:張淯閎.
XOR-Based Meaningful Visual Secret Sharing by Generalized Random Grids Xiaotian Wu, Lu Dai, Duanhao Ou, Wei Sun 報告者: 李宏恩.
Visual Cryptography Advanced Information Security March 11, 2010 Presenter: Semin Kim.
Boolean Minimizer FC-Min: Coverage Finding Process Petr Fišer, Hana Kubátová Czech Technical University Department of Computer Science and Engineering.
Visual Cryptography Hossein Hajiabolhassan Department of Mathematical Sciences Shahid Beheshti University Tehran, Iran.
Visual Secret Sharing Schemes for Plural Secret Images Allowing the Rotation of Shares Kazuki Yoneyama Wang Lei Mitsugu Iwamoto Noboru Kunihiro Kazuo Ohta.
S ECURE A UTHENTICATION USING I MAGE P ROCESSING AND V ISUAL C RYPTOGRAPHY FOR B ANKING A PPLICATIONS Guided By Prof. Rashmi Welekar Submitted By Deepti.
DYNAMIC FACILITY LAYOUT : GENETIC ALGORITHM BASED MODEL
Jaroslaw Kutylowski 1 HEINZ NIXDORF INSTITUTE University of Paderborn Algorithms and Complexity Robust Undetectable Interference Watermarks Ryszard Grząślewicz.
A new provably secure certificateless short signature scheme Authors: K.Y. Choi, J.H. Park, D.H. Lee Source: Comput. Math. Appl. (IF:1.472) Vol. 61, 2011,
國立清華大學高速通訊與計算實驗室 NTHU High-Speed Communication & Computing Laboratory Optimal Provisioning for Elastic Service Oriented Virtual Network Request in Cloud.
Reversible Data Hiding for Point-Sampled Geometry JOURNAL OF INFORMATION SCIENCE AND ENGINEERING Vol. 23, pp , 2007 PENG-CHENG WANG AND CHUNG-MING.
Image Size Invariant Visual Cryptography for General Access Structures Subject to Display Quality Constraints 報告者 : 陳建宇.
A Fast Genetic Algorithm Based Static Heuristic For Scheduling Independent Tasks on Heterogeneous Systems Gaurav Menghani Department of Computer Engineering,
Efficient multi-secret image sharing based on Boolean operations Signal Processing Tzung-Her Chen, Chang-Sian Wu.
Authors: Tzung-Her Chen, Kai-Hsiang Tsao, and Kuo-Chen Wei Source: Proceedings of The 8th International Conference on Intelligent System Design and Applications.
A New Approach for Visual Cryptography Wen-Guey Tzeng and Chi-Ming Hu Designs, codes and cryptography, 27, ,2002 Reporter: 李惠龍.
 劉庭瑋 Electronic Medical Report Security Using Visual Secret Sharing Scheme.
人力資源報告 Image and Signal Processing 1 Steganography Using Sudoku Revisited Wien Hong, Tung-Shou Chen, Chih-Wei Shiu Department of Information Management,
A Study on Visual Secret Display Student: Ming-Chiang Chen Advisors: Dr. Shyong Jian Shyu and Dr. Kun-Mao Chao 1.
National Taiwan University Department of Computer Science and Information Engineering An Approximation Algorithm for Haplotype Inference by Maximum Parsimony.
Genetic Algorithms An Evolutionary Approach to Problem Solving.
Visual Cryptography Given By: Moni Naor Adi Shamir Presented By: Anil Vishnoi (2005H103017)
Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm Jianmin Zhang, Sikun Li, and Shengyu Shen School of Computer Science, National University.
Zurich University, 11 April  A secret sharing scheme is a method of dividing a secret S among a finite set of participants.  only certain pre-specified.
Visual Secret Sharing Chair Professor Chin-Chen Chang (張真誠)
An Information Hiding Scheme Using Sudoku
Information Steganography Using Magic Matrix
The Recent Developments in Visual Cryptography
Information Steganography Using Magic Matrix
Physics-based simulation for visual computing applications
指導教授: Chang, Chin-Chen (張真誠)
The Recent Developments in Visual Secret Sharing
A Study of Digital Image Coding and Retrieving Techniques
Embedding Secrets Using Magic Matrices
Advisor: Chin-Chen Chang1, 2 Student: Yi-Pei Hsieh2
Source:Journal of Real-Time Image Processing, vol.14, pp.41-50, 2016
The New Developments in Visual Cryptography
ARRAY DIVISION Identity matrix Islamic University of Gaza
Information Steganography Using Magic Matrix
A Secret Enriched Visual Cryptography
Hiding Multiple Watermarks in Transparencies of Visual Cryptography
Optimal XOR based (2,n)-Visual Cryptography Schemes
Information Hiding Techniques Using Magic Matrix
Steganographic Systems for Secret Messages
Cheating and Prevention in Visual Secret Sharing
Presentation transcript:

A New Cheating Prevention Scheme For Visual Cryptography 第十六屆全國資訊安全會議 Jun Du-Shiau Tsai ab,Tzung-her Chen c and Gwoboa Horng a a Department of Computer Science, National Chung Hsing University b Department of Information Management, Hsiuping institue of Technology c Department of Computer Science and Information Engineering, National Chiayi University 報告人:張淯閎

2 Conspectus  Abstract  Visual Cryptography  Cheating in Visual Cryptography  VC Cheating Protection Scheme  Simulated Results  Conclusion

3 Abstract  Naor and Shamir proposed the (k,n) Visual Cryptography(VC for short) scheme in 1995, and has been used in numerous applications.  In 2006, Horng et al. proposed that cheating is possible in VC.  In this study, a new scheme used Generic Algorithms(GA for short) is proposed to solve the cheating problem.

4 Visual Cryptography  The nm subpixels is described as an n×m boolean matrix S=[S ij ] such that S ij = 1 if and only if the j th subpixel of the i th share is black. A solution to the (k,n) VC scheme consists of two collections of n×m boolean matrices C 0 (For white) and C 1 (For black).  The solution is considered valid if the following three conditions are met : 1.H(V) ≦ d-α*m in C 0 2.H(V) ≧ d in C 1 3.For any subset {i 1,i 2, …,i q } of {1,2, …,n} with q < k, the two collections of q×m matrices D t for t ε {0,1} obtained by restricting each n×m matrix in C t (where t=0,1) to rows i 1,i 2, …,i q are indistinguishable in the sense that they contain the same matrices with the same frequencies.

5 Cheating in Visual Cryptography  Horng et al. proposed that cheating is possible in (k,n) VC when k is smaller than n.  The key point of cheating is how to predict and rearrange the positions of black and white subpixels in the victim ’ s and cheater ’ s share.  Figure 1. shows the whole cheating process and Table 1. shows the cheaters create to change the decoded image.

Figure 1.: the cheating process

Pixel in Secret Image Share pixel in Share S A Share pixel in Share S B Share pixel in Share S C Pixel in Cheating Image Share pixel in Share S A ’ Share pixel in Share S B ’ Case1white[1 0 0] white[1 0 0] Case2white[1 0 0] black[0 1 0][0 0 1] Case3black[1 0 0][0 1 0][0 0 1]white[0 0 1] Case4black[1 0 0][0 1 0][0 0 1]black[1 0 0][0 1 0] Table 1.: The concept of cheating in VC

8 VC Cheating Protection Scheme(1)  Figure 2. shows the process to proposed scheme. ● First, The rotation process turns SI with different degrees of angle to generate SI. ● Second, used GA to proposed scheme. Figure 2. The sketch of proposed scheme

9 VC Cheating Protection Scheme(2) Individual 1 Individual 2 Individual 3... Fitness Function Transmutation stop yes or no? ReproductionCrossoverMutation Population Simulation environment MatingPool New generation Figure 3.GA Process

10 VC Cheating Protection Scheme(3) Figure 4. The chromosomes

11 VC Cheating Protection Scheme(4) IF H(V j ) = E V THEN ρ j = 1 ELSEρ j = 0, where j = 1,2, …,n IF H(g (i1,i2 ) ) satisfy S V (i1,i2 ) THEN ψ (i1,i2 ) = 1 else ψ (i1,i2 ) = 0, where i 1 < i 2 < n fitness value = Fitness function algorithm

12 Simulated Results(1) Figure 5. Decoded images in the (2, 4) cheating prevention scheme

13 Simulated Results(2) Figure 7: Results of simulated cheating attack.

14 Conclusion  The proposed scheme does against the cheating attack in VC.  The GA based share construction method provides another direction for creating shares.