Fingerprint combination for privacy protection
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we propose here a novel system for protecting finger print privacy by combining two different fingerprints into a new identity. In the enrollment, two fingerprints are captured from two different fingers Thus, a new virtual identity is created for the two different fingerprints, which can be matched using minutiae-based fingerprint matching technique.
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50409621003 fingerprint recognition system-ppt
This document describes a fingerprint recognition system that uses minutiae-based matching. It extracts minutiae features like ridge endings and bifurcations from fingerprints. These minutiae templates are stored in a database along with unique IDs. The system then performs verification by comparing a given fingerprint's minutiae to templates in the database. It also allows identification by searching the entire database for any matching templates without an ID. The proposed system aims to improve matching performance by reconstructing fingerprints' orientation fields from minutiae and incorporating this additional information into the matching process.
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minutiae extraction algorithm into hardware implementation with 14.05 % of EER, better than reference
algorithm, which is 20.39 % .The computational time is 18 seconds less than a similar method, which takes
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This document summarizes several computer vision and soft computing techniques that have been used for offline signature verification and forgery detection in previous research studies. It discusses techniques like fuzzy logic, artificial neural networks, feature extraction methods, and related systems developed by other researchers that have used approaches like neural networks trained on local and global features to classify signatures. The document also provides a brief introduction to concepts like computer vision technology, the need for automated signature verification systems, and defines terms like soft computing and discusses some common soft computing techniques.
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The document is a seminar report submitted by Nikita Sanjay Rajbhoj to Prof. Ashwini Jadhav at G.S. Moze College of Engineering. It discusses big data, including its definition, characteristics, architecture, technologies, and applications. The report includes an abstract, introduction, and sections on definition, characteristics, architecture, technologies, and applications of big data. It also includes references, acknowledgements, and certificates.
Shoulder surfing resistant graphical
TEXTUAL passwords have been the most widely used authentication method for decades. Comprised of number sand upper- and lower-case letters, textual passwords are considered strong enough to resist against brute force
attacks. However, a strong textual password is hard to memorize and recollect .Therefore, users tend to choose passwords that are either short or from the dictionary, rather than random alphanumeric strings.
Various graphical password authentication schemes
were developed to address the problems and weaknesses associated with textual passwords. Based on some studies such as those in , humans have a better ability to memorize images with long-term memory(LTM) than verbal representations. Image-based passwords were proved to be easier to recollect in several user studies As a result, users can set up a complex authentication password and are capable of recollecting it after a long time even if the memory is not activated periodically.
The human actions such as choosing bad passwords for
new accounts and inputting passwords in an insecure way for later logins are regarded as the weakest link in the authentication chain [16]. Therefore, an authentication scheme should be designed to overcome these vulnerabilities.
In this paper, we present a secure graphical authentication system named Pass Matrix that protects users from becoming victims of shoulder surfing attacks when inputting passwords in public through the usage of one-time login indicators. A login indicator is randomly generated for each pass-image and will be useless after the session terminates. The login indicator provides better security against shoulder surfing attacks, since users use a dynamic pointer to point out the position of their passwords rather than clicking on
the password object directly.
M phil-computer-science-biometric-system-projects
List of Biometric System IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Biometric System for M.Phil Computer Science students.
184
Face detection is one of the most suitable applications for image processing and biometric programs. Artificial neural networks have been used in the many field like image processing, pattern recognition, sales forecasting, customer research and data validation. Face detection and recognition have become one of the most popular biometric techniques over the past few years. There is a lack of research literature that provides an overview of studies and research-related research of Artificial neural networks face detection. Therefore, this study includes a review of facial recognition studies as well systems based on various Artificial neural networks methods and algorithms.
Enhancing a Dynamic user Authentication scheme over Brute Force and Dictionar...
This document summarizes a research paper that proposes enhancing user authentication to protect against brute force and dictionary attacks. The paper conducts a review of existing graphical password techniques and proposes a new technique that sends text messages and emails for additional authentication. Key features include challenging hackers with many CAPTCHAs while allowing legitimate users to log in with one CAPTCHA. The technique aims to trace hackers by flooding their IP addresses and locking accounts on machines with many failed login attempts.
Security using image processing
Using image stitching and image steganography security can be provided to any image which has to be
sent over the network or transferred using any electronic mode. There is a message and a secret image that
has to be sent. The secret image is divided into parts.The first phase is the Encrypting Phase, which deals
with the process of converting the actual secret message into ciphertext using the AES algorithm. In the
second phase which is the Embedding Phase, the cipher text is embedded into any part of the secret image
that is to be sent. Third phase is the Hiding Phase, where steganography is performed on the output image
of Embedding Phase and other parts of the image where the parts are camouflaged by another image using
least significant bit replacement. These individual parts are sent to the concerned receiver. At the
receivers end decryption of Hiding phase and Embedding Phase takes place respectively. The parts
obtained are stitched together using k nearest method. Using SIFT features the quality of the image is
improved.
Graphical Password Authentication using image Segmentation for Web Based Appl...
One of the most important topics in information security today is user authentication. User authentication is a fundamental component in most computer security contexts. It provides the basis for access control and user accountability. While there are various types of user authentication systems, alphanumeric passwords are the most common type of user authentication. They are versatile and easy to implement and use. However, it can either be long and secure or short and hard to remember. A graphical based password is one promising alternatives of textual passwords. According to human psychology, humans are able to remember pictures easily. In this paper, graphical passwords have been designed to try to make password more memorable and easier for people to use, and it is less vulnerable to brute force attacks than a text based password. The aim of the system is to implement a strong security. The proposed system segments the image like a grid, which has a maximum four fragments. Then, each segment of the image is dragged in a particular sequence onto an empty grid of size 6x6 and placed on a particular segment of the empty grid, to form the user' password. When the user logs into the system, the user needs to drag each segment of the image onto the same empty grid of size 6x6 in the correct sequence and position of the segments that user had specified during registration. Maw Maw Naing | Ohnmar Win ""Graphical Password Authentication using image Segmentation for Web Based Applications"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25184.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25184/graphical-password-authentication-using-image-segmentation-for-web-based-applications/maw-maw-naing
Fingerprint based transaction system
This document outlines the software requirements specification for a fingerprint-based transaction system. It includes sections on introduction, overall description of the system, system features, and software interface requirements. The system will use fingerprint authentication to allow users to conduct transactions without cash or ATM cards. It aims to provide a secure and convenient transaction method. The document defines requirements for the fingerprint database, transaction processing, performance, and interfacing with bank computer systems.
IJSRED-V2I2P33
This document presents a statistical-ANN hybrid technique for offline signature recognition. It extracts features from signatures using statistical approaches like invariant moment methods, and then classifies signatures using an artificial neural network (ANN). The system takes in signature images, preprocesses them, extracts features, and trains an ANN classifier. It can recognize and verify signatures on a test database with reasonable accuracy. The hybrid statistical-ANN approach aims to minimize intra-personal variations between genuine signatures while maximizing inter-personal variations to distinguish forgeries.
Final ppt
This document discusses Shweta Somani's enrollment number and a face recognition project. The project focuses on developing a fast, simple and accurate computational face recognition model that works in different environments. Two algorithms were applied: Eigenfaces and Local Binary Patterns. Eigenfaces does not handle external variations well and requires more training images, while Local Binary Patterns handles external variations and requires fewer training images.
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Design of digital signature verification algorithm using relative slope method
Design of digital signature verification algorithm using relative slope method
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FINGERPRINT BASED ATM SYSTEM
Biometric system is a pattern identification system that recognizes an individual by determining the originality of the physical features and behavioral characteristic of that person. Of all the recently used biometric techniques, fingerprint identification systems have gained the most popularity because of the prolonged existence of fingerprints and its extensive use. Fingerprint is dependable biometric trait as it is an idiosyncratic and dedicated. It is a technology that is increasingly used in various fields like forensics and security purpose. The vital objective of our system is to make ATM transaction more secure and user friendly. This system replaces traditional ATM cards with fingerprint. Therefore, there is no need to carry ATM cards to perform transactions. The money transaction can be made more secure without worrying about the card to be lost. In our system we are using embedded system with biometrics i.e r305 sensor and UART microcontroller. The Fingerprint and the user_id of all users are stored in the database. Fingerprints are used to identify whether the Person is genuine. A Fingerprint scanner is used to acquire the fingerprint of the individual, after which the system requests for the PIN (Personal Identification Number). The user gets three chances to get him authenticated. If the fingerprints do not match further authentication will be needed. After the verification with the data stored in the system database, the user is allowed to make transactions.
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This document reviews a technique for combining two fingerprints from different fingers to generate a new combined fingerprint identity for privacy protection. In the enrollment phase, minutiae positions from one fingerprint and orientation from another fingerprint are extracted and combined with reference points from both fingerprints to generate a combined minutiae template. In authentication, the same two fingerprints are matched against the stored template using a two-stage matching process. The combined template cannot be traced back to the original fingerprints, improving anonymity. The combined template can also be reconstructed into a combined fingerprint image to form a new virtual identity matched using standard fingerprint algorithms. The technique aims to protect privacy by preventing full minutiae disclosure of any single fingerprint if the database is stolen.
Effectiveness of various user authentication techniques
This document discusses and compares various user authentication techniques. It analyzes one-time password authentication using smart phones (oPass), 3D password authentication using a virtual environment, and smart card-based authentication. oPass requires the user to remember only a long-term password for their phone, while the website generates one-time passwords via SMS. 3D passwords combine multiple authentication methods by having users navigate and interact with virtual objects. Smart card authentication does not store passwords in verification tables and allows password changes for mutual authentication. The document examines the advantages and disadvantages of these approaches.
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Bio atm with-microsoft_finger_print_sdk
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nullcon 2011 - Penetration Testing a Biometric System
The document provides guidance on penetration testing biometric fingerprint authentication systems. It outlines various potential attack vectors, including local attacks on the fingerprint sensor and USB data manager, as well as remote attacks on the remote IP management, backend database, and fingerprint manager admin interface. The document then details methods for conducting local attacks, such as using a fingerprint logger to steal a print and reproducing fake fingerprints to trick the sensor. It also discusses vulnerabilities in biometric device network protocols and remote administration capabilities. The goal is to evaluate security and identify ways to bypass authentication or steal sensitive user data from biometric systems.
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For security and surveillance automated personal identification is major issue. We can see a lot varieties of biometric systems like face detection, fingerprint recognition, iris recognition, voice recognition, palm recognition etc. In our project we will only go for fingerprint recognition. Never two peoples have exactly same fingerprints even twins, they are totally unique. The sensors capture the finger prints of humans and convert them into images and a minutiae extraction algorithm extracts the location of minutiae points called termination and bifurcation. A database system stores these patterns and minutiae points of fingerprint. A large storage space required to store bifurcation and termination points for the fingerprint database. LZW compression algorithm has been used to reduce the size of data. With LZW applied on these extracted minutiae points, these minutiae points get encoded which add more security feature.
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7. 9589 1-pb
This document describes a new password authentication method that combines textual passwords with a modified cued click points technique for increased security. The method uses a special key display interface that breaks the user's password into a combination of four passwords plus three additional strings. These seven strings are then encrypted using a novel one-way encryption algorithm called One-time Data Division (ODD). This produces a 256-character encrypted password that is stored in the database for authentication. The encryption is complex and lossy, making the original password irrecoverable even by an administrator. The method aims to provide strong security while maintaining usability.
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In today’s computerized world, cyber crime has increased. The web network of www also increases day by day. So the protection of software and data in our computers has become very important. For this purpose we are developing the “Server Security System” with the help of some technologies such as GPRS, TCP-IP, SMTP, and MIME. In our project we are developing a system such that we get the image of an unauthorized person or user. To do this we are using a webcam. We send a mail to the authorized person's GPRS phone. For this purpose we use a mobile it can be any mobile. In parallel we are changing the password by generating a random string & then Shutting-Down the computer remotely. By using java programming we can create such applications which will help us to stop the cyber crime. It is not visible to new user so that he is unaware from this software so this will definitely helpful to make them fool.
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9
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Fingerprint combination for privacy protection
- 1. D-Secure Privacy Protection based on Fingerprint
- 2. Abstract: Fingerprint recognition is an active research area nowadays. In many areas we are using fingerprint recognition for to improve the security and privacy. In finger print recognitions system the recognition can be done by fingerprint matching techniques. Fingerprint matching techniques are classified in two categories: Fingerprint verification and Fingerprint identification. In this project we are using the fingerprint verification. For this we propose here a novel system for protecting finger print privacy by combining two different fingerprints into a new identity. In the enrollment, two fingerprints are captured from two different fingers. We extract the minutiae positions from one fingerprint, the orientation from the other fingerprint, and the reference points from both fingerprints. Based on this extracted information and our proposed coding strategies, a combined minutiae template is generated and stored in a database. In the authentication, the system requires two query fingerprints from the same two fingers which are used in the enrollment. A two-stage fingerprint matching process is proposed for matching the two query fingerprints against a combined minutiae template. With the help of an existing fingerprint reconstruction approach, we are able to convert the combined minutiae template into a real-look alike combined fingerprint. Thus, a new virtual identity is created for the two different fingerprints, which can be matched using minutiae-based fingerprint matching technique. We are going to develop this project in Dot Net Technology.
- 3. Existing System: In the Existing system finger prints are scanned single finger. And it is stored in database, and while the authentication process stored finger print is matched with the enrollment finger print. This type of system didn’t provide full security and privacy to the users. Advantage: Most convenient because of Single finger print The prices of the finger print readers are pocket friendly No need to remember Password. Disadvantages: Less Security ( rejects certain percentage of the people) Limited Privacy Protection o Store the registered and the objective images in the system, which may cause the risk of exposure and leakage of the private fingerprint image. Require extra time to identify user High attacks from hackers. Proposed System: In proposed system model contain biometric authentication. During Authentication, system will verify the details in the database and identify whether the user authorized person or not. If the user is unauthorized mean, the server gives the error message to that user. If the user authorized mean, the server give the acknowledgment to user for further actions. Matching process is proposed for matching the two query fingerprints against a combined minutiae template. With the help of an existing fingerprint reconstruction approach, we are able to convert the combined minutiae template into a real-look alike combined fingerprint. Thus, a
- 4. new virtual identity is created for the two different fingerprints, which can be matched using minutiae-based fingerprint matching algorithms. Advantage: Double level Security No Limited Privacy Protection System Can Achieve A Very Low Error Rate High Performance System Specification Software Requirements: MS Windows XP/2000 MS Visual Studio.Net 2005 MS SQL Server 2000 Hardware Requirements: Hard Disk: 20GB and Above RAM: 1GB and Above Processor: Pentium III and Above
- 5. Architecture Diagram: Enrolment (Two fingerprint input) Combined Minutiae Template Generation Authorization Database Authentication (Two fingerprint input) Yes/No Two-Stage Fingerprint Matching Existing System Architecture Enrolment (Single fingerprint input) Authorization Database Authentication (Single fingerprint input) Minutiae Fingerprint Matching s Yes/No
- 6. Fingerprint Verification Algorithm Proposed Method: Minutiae Method Fingerprint verification Algorithm: Minutia method uses feature information of the terminal points and separate points of ridges of the fingerprint and their relative positions. Existing Method: Pattern Matching Method Fingerprint Verification Algorithm: Pattern-matching method verifies the identity of the patterns by directly comparing the objective fingerprint images with the registered image.