SlideShare ist ein Scribd-Unternehmen logo
1 von 14
Detection and identification of
cheaters in (t, n) secret
sharing scheme
Presented by
Outline
• Problem definition
• Literature survey
• System features
• System Architecture
• Analysis Models
• UML diagrams
• System Implementation Plans
• Grantt chart, Cost implementation model
Problem definition
In a (t, n) secret sharing scheme, a secret s is divided
into n shares and shared among a set of n shareholders
by a mutually trusted dealer in such a way that any t or
more than t shares will be able to reconstruct this secret;
but fewer than t shares cannot know any information
about the secret.
Literature survey
 There are many research papers in the literatures to investigate the problem of cheater
detection and/or identification for secret sharing schemes.
 In 1979, Shamir and Blakley first developed the concept of the (t,n) threshold secret sharing scheme.
Then Naor and Shamir extended the secret sharing concept into image research, and referred it as image
secret sharing in 1994, which was based on the model of secret sharing proposed by the two above-
mentioned scholars: For image information P, we would like to generate n shadow images so that any t or
more participants can reconstruct the original secret image, but any t-1 or less participants can not get
sufficient information to reconstruct the original secret image.
 After Naor and Shamir, many secret sharing schemes have been proposed for processing 256 gray-level
image. But in these schemes, shadow images have larger image sizes compared to that of the original
secret image. The contrast ratio in the reconstructed image is quite poor
System features
 Hardware & Software Requirements
Hard disk 80 GB
RAM 1GB
Technology Java
Tools Net-beans IDE
Processor Intel Pentium IV or above
Operating System Windows XP
System features continued..
Quality Attributes
• Usability : The application seem to user friendly since the GUI is
interactive.
• Maintainability : This application is maintained for long period of time
since it will be implemented under java platform .
• Reusability : The application can be reusable by expanding it to the
new modules
• Portability: The application is purely a portable mobile application since it
can only be operated on android Operating system.
System architecture
• Thien-Lin scheme and the intractability of the
discrete logarithm:
• IT contains three phases: Initialization phase, Construction phase
and Reconstruction & Verification phase:
•
• Initialization phase: In this phase, the holder and the participants need some
intercommunication, but this can be done over a public channel. Firstly, H chooses two
prime numbers, p and q, and computes N=pq. Both p and q should satisfy the same
properties as the two primes used in RSA cryptosystem which can prevent anybody
factor N efficiently. Subsequently, H chooses an integer g∈[N1/2,N] such that g is
relatively prime to p and q. Publishes {g, N}.Each participant Mi∈M randomly chooses
an si∈[2, N] asher/his own secret shadow and computes Ri =gsi modN, finally Mi
provides Ri to H. H must ensure that Ri≠Rj for all Mi≠Mj. Once Ri=Rj, H should
demand these Mi s to choose new si s. Publishes Ri.
System architecture
Construction phase: H randomly chooses an integer s0∈[2,N] such that s0 is
relatively prime to (p−1) and (q−1). Then H computes f and makes
s0 f=1modφ(N), whereφ(N) is the Euler phi-function;
H Computes R0 =gs0 modN and Ii =Rs0 i modN, i=1, 2,…, n. Publishes {R0, f};
The new image P′ is divided into several sections according to lexicography
order. Each section contains t pixels, and each pixel of the image belongs to one
and only one section. For the section j, H constructs (t−1) th-degree polynomial
hj(x) mod 251 as follows:
hjðxÞ ¼ b0 þ b1x þ: : : þ bt_1xt_1mod251:
Here b0, b1,…, bt − 1 are the t pixels of the section;
H evaluates yi=hj(Ii), i=1, 2,…, n. Publishes (y1, y2,…,y
System architecture
 Reconstruction and verification phase : Without loss of generality, members of M′={M1,
M2,…, Mt} will cooperate to reconstruct the image P′.
1) Mi∈M′ computes her/his own sub-secret(pseudo shadow) Ii V¼ Rsi 0 modN, where si is secret
shadow of Mi;
2) Anybody can verify Ii′ provided by Mi: if I′I f=Ri mod N, then Ii′ is true; otherwise Ii′ is false
and Mi may be a cheater;
Reconstruct the image P′: with the knowledge of t pairs of (Ii′,yi) and the Lagrange
interpolating polynomial, the (t−1)th-degree polynomial hj(x) can be uniquely determined as
follows:
 In initialization phase, each participant Mi chooses her/his own secret shadow si, the holder H is absolutely
not a cheater
Use case
Activity
State transition
System Implementation Plan
SR
No
Task Name Duration
1 Project topic finalization 10 days
2 Studying Core java,J2SE 10 days
3 Implementation of Shamir’s SSS system 30 days
4 Implementation of detecting system 7 days
5 Implementation of identifying cheaters 10 days
Grant chart & cost implementation
model
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Training System
installation
Studying Core
java
Implementation
of Modules
Testing Documentation
Cost(in RS)
Time(in days)

Weitere ähnliche Inhalte

Was ist angesagt?

Basics of Image Processing using MATLAB
Basics of Image Processing using MATLABBasics of Image Processing using MATLAB
Basics of Image Processing using MATLABvkn13
 
Introductory Digital Image Processing using Matlab, IIT Roorkee
Introductory Digital Image Processing using Matlab, IIT RoorkeeIntroductory Digital Image Processing using Matlab, IIT Roorkee
Introductory Digital Image Processing using Matlab, IIT RoorkeeVinayak Sahai
 
Designing a Proof GUI for Non-Experts
Designing a Proof GUI for Non-ExpertsDesigning a Proof GUI for Non-Experts
Designing a Proof GUI for Non-ExpertsMartin Homik
 
Image Matting Using Linear Optimization
Image Matting Using Linear OptimizationImage Matting Using Linear Optimization
Image Matting Using Linear OptimizationConrad Triquell
 
Point cloud library
Point cloud libraryPoint cloud library
Point cloud libraryBindu Karki
 
Forelasning4
Forelasning4Forelasning4
Forelasning4Memo Love
 
A NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGES
A NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGESA NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGES
A NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGESIJTET Journal
 
유한요소법(FEM)을 이용한 구조해석
유한요소법(FEM)을 이용한 구조해석유한요소법(FEM)을 이용한 구조해석
유한요소법(FEM)을 이용한 구조해석chimco.net
 
Images in matlab
Images in matlabImages in matlab
Images in matlabAli Alvi
 
Image Storage, Indexing and Recognition
Image Storage, Indexing and RecognitionImage Storage, Indexing and Recognition
Image Storage, Indexing and RecognitionAdeel Riaz
 
GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...
GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...
GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...Fabio Petroni, PhD
 
Summer training matlab
Summer training matlab Summer training matlab
Summer training matlab Arshit Rai
 
LCBM: Statistics-Based Parallel Collaborative Filtering
LCBM: Statistics-Based Parallel Collaborative FilteringLCBM: Statistics-Based Parallel Collaborative Filtering
LCBM: Statistics-Based Parallel Collaborative FilteringFabio Petroni, PhD
 
Matlab for Electrical Engineers
Matlab for Electrical EngineersMatlab for Electrical Engineers
Matlab for Electrical EngineersManish Joshi
 

Was ist angesagt? (20)

Basics of Image Processing using MATLAB
Basics of Image Processing using MATLABBasics of Image Processing using MATLAB
Basics of Image Processing using MATLAB
 
Introductory Digital Image Processing using Matlab, IIT Roorkee
Introductory Digital Image Processing using Matlab, IIT RoorkeeIntroductory Digital Image Processing using Matlab, IIT Roorkee
Introductory Digital Image Processing using Matlab, IIT Roorkee
 
Designing a Proof GUI for Non-Experts
Designing a Proof GUI for Non-ExpertsDesigning a Proof GUI for Non-Experts
Designing a Proof GUI for Non-Experts
 
Matlab project
Matlab projectMatlab project
Matlab project
 
Image Matting Using Linear Optimization
Image Matting Using Linear OptimizationImage Matting Using Linear Optimization
Image Matting Using Linear Optimization
 
Point cloud library
Point cloud libraryPoint cloud library
Point cloud library
 
Forelasning4
Forelasning4Forelasning4
Forelasning4
 
C basics
C basicsC basics
C basics
 
A NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGES
A NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGESA NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGES
A NEW VISUAL CRYPTOGRAPHY TECHNIQUE FOR COLOR IMAGES
 
MATLAB
MATLABMATLAB
MATLAB
 
유한요소법(FEM)을 이용한 구조해석
유한요소법(FEM)을 이용한 구조해석유한요소법(FEM)을 이용한 구조해석
유한요소법(FEM)을 이용한 구조해석
 
Matlab Working With Images
Matlab Working With ImagesMatlab Working With Images
Matlab Working With Images
 
Images in matlab
Images in matlabImages in matlab
Images in matlab
 
Log polar coordinates
Log polar coordinatesLog polar coordinates
Log polar coordinates
 
Image Storage, Indexing and Recognition
Image Storage, Indexing and RecognitionImage Storage, Indexing and Recognition
Image Storage, Indexing and Recognition
 
Autoencoder
AutoencoderAutoencoder
Autoencoder
 
GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...
GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...
GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Comple...
 
Summer training matlab
Summer training matlab Summer training matlab
Summer training matlab
 
LCBM: Statistics-Based Parallel Collaborative Filtering
LCBM: Statistics-Based Parallel Collaborative FilteringLCBM: Statistics-Based Parallel Collaborative Filtering
LCBM: Statistics-Based Parallel Collaborative Filtering
 
Matlab for Electrical Engineers
Matlab for Electrical EngineersMatlab for Electrical Engineers
Matlab for Electrical Engineers
 

Ähnlich wie Detection and identification of cheaters in (t, n) secret

Copyright protection scheme based on visual Cryptography: A Review
Copyright protection scheme based on visual Cryptography: A ReviewCopyright protection scheme based on visual Cryptography: A Review
Copyright protection scheme based on visual Cryptography: A Reviewiosrjce
 
Image Classification using Deep Learning
Image Classification using Deep LearningImage Classification using Deep Learning
Image Classification using Deep LearningIRJET Journal
 
Human Head Counting and Detection using Convnets
Human Head Counting and Detection using ConvnetsHuman Head Counting and Detection using Convnets
Human Head Counting and Detection using Convnetsrahulmonikasharma
 
Performance Anaysis for Imaging System
Performance Anaysis for Imaging SystemPerformance Anaysis for Imaging System
Performance Anaysis for Imaging SystemVrushali Lanjewar
 
IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...
IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...
IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...IRJET Journal
 
00463517b1e90c1e63000000
00463517b1e90c1e6300000000463517b1e90c1e63000000
00463517b1e90c1e63000000Ivonne Liu
 
IMAGE SEGMENTATION AND ITS TECHNIQUES
IMAGE SEGMENTATION AND ITS TECHNIQUESIMAGE SEGMENTATION AND ITS TECHNIQUES
IMAGE SEGMENTATION AND ITS TECHNIQUESIRJET Journal
 
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...IRJET Journal
 
Comparison of Various RCNN techniques for Classification of Object from Image
Comparison of Various RCNN techniques for Classification of Object from ImageComparison of Various RCNN techniques for Classification of Object from Image
Comparison of Various RCNN techniques for Classification of Object from ImageIRJET Journal
 
IRJET - Single Image Super Resolution using Machine Learning
IRJET - Single Image Super Resolution using Machine LearningIRJET - Single Image Super Resolution using Machine Learning
IRJET - Single Image Super Resolution using Machine LearningIRJET Journal
 
A Beginner's Guide to Monocular Depth Estimation
A Beginner's Guide to Monocular Depth EstimationA Beginner's Guide to Monocular Depth Estimation
A Beginner's Guide to Monocular Depth EstimationRyo Takahashi
 
1 of 6 LAB 5 IMAGE FILTERING ECE180 Introduction to.docx
1 of 6  LAB 5 IMAGE FILTERING ECE180 Introduction to.docx1 of 6  LAB 5 IMAGE FILTERING ECE180 Introduction to.docx
1 of 6 LAB 5 IMAGE FILTERING ECE180 Introduction to.docxmercysuttle
 
Image processing using matlab
Image processing using matlabImage processing using matlab
Image processing using matlabdedik dafiyanto
 
Ax31139148
Ax31139148Ax31139148
Ax31139148IJMER
 

Ähnlich wie Detection and identification of cheaters in (t, n) secret (20)

mini prjt
mini prjtmini prjt
mini prjt
 
Copyright protection scheme based on visual Cryptography: A Review
Copyright protection scheme based on visual Cryptography: A ReviewCopyright protection scheme based on visual Cryptography: A Review
Copyright protection scheme based on visual Cryptography: A Review
 
N017327985
N017327985N017327985
N017327985
 
Image Classification using Deep Learning
Image Classification using Deep LearningImage Classification using Deep Learning
Image Classification using Deep Learning
 
Deep learning (2)
Deep learning (2)Deep learning (2)
Deep learning (2)
 
Human Head Counting and Detection using Convnets
Human Head Counting and Detection using ConvnetsHuman Head Counting and Detection using Convnets
Human Head Counting and Detection using Convnets
 
Performance Anaysis for Imaging System
Performance Anaysis for Imaging SystemPerformance Anaysis for Imaging System
Performance Anaysis for Imaging System
 
Visual CryptoGraphy
Visual CryptoGraphyVisual CryptoGraphy
Visual CryptoGraphy
 
IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...
IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...
IRJET- An Acute Method of Encryption & Decryption by using Histograms and Che...
 
00463517b1e90c1e63000000
00463517b1e90c1e6300000000463517b1e90c1e63000000
00463517b1e90c1e63000000
 
IMAGE SEGMENTATION AND ITS TECHNIQUES
IMAGE SEGMENTATION AND ITS TECHNIQUESIMAGE SEGMENTATION AND ITS TECHNIQUES
IMAGE SEGMENTATION AND ITS TECHNIQUES
 
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...
 
Comparison of Various RCNN techniques for Classification of Object from Image
Comparison of Various RCNN techniques for Classification of Object from ImageComparison of Various RCNN techniques for Classification of Object from Image
Comparison of Various RCNN techniques for Classification of Object from Image
 
IRJET - Single Image Super Resolution using Machine Learning
IRJET - Single Image Super Resolution using Machine LearningIRJET - Single Image Super Resolution using Machine Learning
IRJET - Single Image Super Resolution using Machine Learning
 
Image Encryption in java ppt.
Image Encryption in java ppt.Image Encryption in java ppt.
Image Encryption in java ppt.
 
A Beginner's Guide to Monocular Depth Estimation
A Beginner's Guide to Monocular Depth EstimationA Beginner's Guide to Monocular Depth Estimation
A Beginner's Guide to Monocular Depth Estimation
 
1 of 6 LAB 5 IMAGE FILTERING ECE180 Introduction to.docx
1 of 6  LAB 5 IMAGE FILTERING ECE180 Introduction to.docx1 of 6  LAB 5 IMAGE FILTERING ECE180 Introduction to.docx
1 of 6 LAB 5 IMAGE FILTERING ECE180 Introduction to.docx
 
Image processing using matlab
Image processing using matlabImage processing using matlab
Image processing using matlab
 
Ax31139148
Ax31139148Ax31139148
Ax31139148
 
Matlab dip
Matlab dipMatlab dip
Matlab dip
 

Mehr von Parag Tamhane

A two stage feature selection method for text categorization
A two stage feature selection method for text categorizationA two stage feature selection method for text categorization
A two stage feature selection method for text categorizationParag Tamhane
 
Outlier detection for high dimensional data
Outlier detection for high dimensional dataOutlier detection for high dimensional data
Outlier detection for high dimensional dataParag Tamhane
 
2 d barcode based mobile payment system
2 d barcode based mobile payment system2 d barcode based mobile payment system
2 d barcode based mobile payment systemParag Tamhane
 
3 d antiphishing based cryptography
3 d antiphishing based cryptography3 d antiphishing based cryptography
3 d antiphishing based cryptographyParag Tamhane
 
Mpeg 7 video signature tools for content recognition
Mpeg 7 video signature tools for content recognitionMpeg 7 video signature tools for content recognition
Mpeg 7 video signature tools for content recognitionParag Tamhane
 
Integration of sound signature in graphical password
Integration of sound signature in graphical passwordIntegration of sound signature in graphical password
Integration of sound signature in graphical passwordParag Tamhane
 
Multi biometric cryptosystems based on feature-level fusion
Multi biometric cryptosystems based on feature-level fusionMulti biometric cryptosystems based on feature-level fusion
Multi biometric cryptosystems based on feature-level fusionParag Tamhane
 

Mehr von Parag Tamhane (7)

A two stage feature selection method for text categorization
A two stage feature selection method for text categorizationA two stage feature selection method for text categorization
A two stage feature selection method for text categorization
 
Outlier detection for high dimensional data
Outlier detection for high dimensional dataOutlier detection for high dimensional data
Outlier detection for high dimensional data
 
2 d barcode based mobile payment system
2 d barcode based mobile payment system2 d barcode based mobile payment system
2 d barcode based mobile payment system
 
3 d antiphishing based cryptography
3 d antiphishing based cryptography3 d antiphishing based cryptography
3 d antiphishing based cryptography
 
Mpeg 7 video signature tools for content recognition
Mpeg 7 video signature tools for content recognitionMpeg 7 video signature tools for content recognition
Mpeg 7 video signature tools for content recognition
 
Integration of sound signature in graphical password
Integration of sound signature in graphical passwordIntegration of sound signature in graphical password
Integration of sound signature in graphical password
 
Multi biometric cryptosystems based on feature-level fusion
Multi biometric cryptosystems based on feature-level fusionMulti biometric cryptosystems based on feature-level fusion
Multi biometric cryptosystems based on feature-level fusion
 

Kürzlich hochgeladen

Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontologyjohnbeverley2021
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Victor Rentea
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsNanddeep Nachan
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Jeffrey Haguewood
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxRustici Software
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobeapidays
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...apidays
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfOrbitshub
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...apidays
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoffsammart93
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxRemote DBA Services
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Orbitshub
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamUiPathCommunity
 

Kürzlich hochgeladen (20)

Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 

Detection and identification of cheaters in (t, n) secret

  • 1. Detection and identification of cheaters in (t, n) secret sharing scheme Presented by
  • 2. Outline • Problem definition • Literature survey • System features • System Architecture • Analysis Models • UML diagrams • System Implementation Plans • Grantt chart, Cost implementation model
  • 3. Problem definition In a (t, n) secret sharing scheme, a secret s is divided into n shares and shared among a set of n shareholders by a mutually trusted dealer in such a way that any t or more than t shares will be able to reconstruct this secret; but fewer than t shares cannot know any information about the secret.
  • 4. Literature survey  There are many research papers in the literatures to investigate the problem of cheater detection and/or identification for secret sharing schemes.  In 1979, Shamir and Blakley first developed the concept of the (t,n) threshold secret sharing scheme. Then Naor and Shamir extended the secret sharing concept into image research, and referred it as image secret sharing in 1994, which was based on the model of secret sharing proposed by the two above- mentioned scholars: For image information P, we would like to generate n shadow images so that any t or more participants can reconstruct the original secret image, but any t-1 or less participants can not get sufficient information to reconstruct the original secret image.  After Naor and Shamir, many secret sharing schemes have been proposed for processing 256 gray-level image. But in these schemes, shadow images have larger image sizes compared to that of the original secret image. The contrast ratio in the reconstructed image is quite poor
  • 5. System features  Hardware & Software Requirements Hard disk 80 GB RAM 1GB Technology Java Tools Net-beans IDE Processor Intel Pentium IV or above Operating System Windows XP
  • 6. System features continued.. Quality Attributes • Usability : The application seem to user friendly since the GUI is interactive. • Maintainability : This application is maintained for long period of time since it will be implemented under java platform . • Reusability : The application can be reusable by expanding it to the new modules • Portability: The application is purely a portable mobile application since it can only be operated on android Operating system.
  • 7. System architecture • Thien-Lin scheme and the intractability of the discrete logarithm: • IT contains three phases: Initialization phase, Construction phase and Reconstruction & Verification phase: • • Initialization phase: In this phase, the holder and the participants need some intercommunication, but this can be done over a public channel. Firstly, H chooses two prime numbers, p and q, and computes N=pq. Both p and q should satisfy the same properties as the two primes used in RSA cryptosystem which can prevent anybody factor N efficiently. Subsequently, H chooses an integer g∈[N1/2,N] such that g is relatively prime to p and q. Publishes {g, N}.Each participant Mi∈M randomly chooses an si∈[2, N] asher/his own secret shadow and computes Ri =gsi modN, finally Mi provides Ri to H. H must ensure that Ri≠Rj for all Mi≠Mj. Once Ri=Rj, H should demand these Mi s to choose new si s. Publishes Ri.
  • 8. System architecture Construction phase: H randomly chooses an integer s0∈[2,N] such that s0 is relatively prime to (p−1) and (q−1). Then H computes f and makes s0 f=1modφ(N), whereφ(N) is the Euler phi-function; H Computes R0 =gs0 modN and Ii =Rs0 i modN, i=1, 2,…, n. Publishes {R0, f}; The new image P′ is divided into several sections according to lexicography order. Each section contains t pixels, and each pixel of the image belongs to one and only one section. For the section j, H constructs (t−1) th-degree polynomial hj(x) mod 251 as follows: hjðxÞ ¼ b0 þ b1x þ: : : þ bt_1xt_1mod251: Here b0, b1,…, bt − 1 are the t pixels of the section; H evaluates yi=hj(Ii), i=1, 2,…, n. Publishes (y1, y2,…,y
  • 9. System architecture  Reconstruction and verification phase : Without loss of generality, members of M′={M1, M2,…, Mt} will cooperate to reconstruct the image P′. 1) Mi∈M′ computes her/his own sub-secret(pseudo shadow) Ii V¼ Rsi 0 modN, where si is secret shadow of Mi; 2) Anybody can verify Ii′ provided by Mi: if I′I f=Ri mod N, then Ii′ is true; otherwise Ii′ is false and Mi may be a cheater; Reconstruct the image P′: with the knowledge of t pairs of (Ii′,yi) and the Lagrange interpolating polynomial, the (t−1)th-degree polynomial hj(x) can be uniquely determined as follows:  In initialization phase, each participant Mi chooses her/his own secret shadow si, the holder H is absolutely not a cheater
  • 13. System Implementation Plan SR No Task Name Duration 1 Project topic finalization 10 days 2 Studying Core java,J2SE 10 days 3 Implementation of Shamir’s SSS system 30 days 4 Implementation of detecting system 7 days 5 Implementation of identifying cheaters 10 days
  • 14. Grant chart & cost implementation model 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Training System installation Studying Core java Implementation of Modules Testing Documentation Cost(in RS) Time(in days)