Look At Computer Network Is Supported By Network Computer Science Essay

Published Date: 02 Nov 2017

Index Terms — Fingerprint Enrollment, Encryption, Fingerprint Enhancement, Fingerprint Verification, One Time Password Generation, Mobile Network, Password Verification.

INTRODUCTION

The website based substantiation aspect implements website based substantiation, which is also known as Website Validation Proxy. You can use the website based substantiation feature to validate end users on host systems that don’t run the IEEE 802.1X supplicant. User can be configuring the website based substantiation feature on Layer 2 and Layer 3 interfaces.

When a user initiates an HTTP session, the website based substantiation feature intercepts access HTTP packets from the host and sends web-design login page to the user. The user keys in their credentials, which the website based substantiation feature sends to the XXX server for validation. If the validation succeeds, website based substantiation sends a Login-Successful web-design page to the host and applies the right to use policies returned by the XXX server.

If the validation fails, validation based validation feature sends a Login-Fail web-design page to the user, which prompts the user to retry the login effort. If the user exceeds the highest number of failed login attempts, website based substantiation sends a Login-Expired web-design page to the host process and the user can located on a watch list for a waiting time.

Website based multi-way substantiation is commonly found in electronic computer substantiation, where basic substantiation is the method of a requesting entity presenting some indication of its identity to a second entity. Website based multi-way substantiation seeks to lessen the probability that the requestor is presenting fake substantiation of its identity. The number of factors is significant, as it implies a high probability that the owner of the identity substantiation indeed holds that identity in a different realm. In realism, there are more variables to believe when establish the relative guarantee of honesty in an identity declaration than just how many factors are used [5].

Website based multi-way substantiation is often confused with other forms of substantiation. Website based multi-way substantiation requires the utilize of two of the three substantiation factors. The factors are recognized in the principles and system for right of admission to U.S. Federal Government systems.

Website based multi-way substantiation is not a novel concept, having been used all through history. When a bank client visit a neighboring automated teller machine (ATM), a substantiation thing is use a physical ATM card the client slides into the ATM machine. The next thing is the customer enters the PIN number through the keyboard. Without the corroborate substantiation of these factors, substantiation does not succeed. This situation illustrates the fundamental concept of the majority Website based multi-way substantiation systems: the grouping of a information factor and a control factor. Website based multi-way substantiation (or multi-factor substantiation) is sometimes confused with "strong substantiation", however, "strong substantiation" and "multi-factor substantiation" are basically dissimilar processes. Soliciting a variety of answers to challenge question may be measured strong substantiation but, except the process also retrieves, it would not be considered Multi-way substantiation. The United State Federal Financial Institutions Examination Council issue supplemental regulation on this topic in August 2006, in which they clarify, "By clarity true multifactor substantiation requires the use of declaration from two or more of this three category of factor. Using many solutions from the matching category, would not comprise multifactor substantiation [6]."

Related Work

A research a password authenticated group key exchange protocol for secured communication of mobile ad-hoc networks. It is concerned with improving the security of the NEKED protocol. NEKED protocol is vulnerable not only to an attack against backward secrecy but also to an attack against password security. Same pair-wise key is used for two consecutive runs of setup and join. Same pair-wise key is used in computing two related parameters [1]. Proposed an Improved password based substantiation protocol for network security. Uses PAKE protocol which is vulnerable to server compromise attack. This is meets some draw backs threats due to the low entropy of passwords, Amplified password file is impractical [2]. Proposed an improvement GPAKE protocol. This is securely establish a session key between the client and the gateway. This still able to gain information of password by performing an undetectable on-line password guessing attack [3]. Examines passwords, security tokens and biometrics based on their characteristic for substantiation. Analysis is done based on knowledge based, object-based and id based substantiation. This is mainly meet this draw backs that are Multi-passwords are less security, Tokens are inconvenient and costly and Inconvenient the user by many false non matches [4]. Provides a solution for the online learning environment using biometric based substantiation. Using methodologies are handles five step processes to ensure the user substantiation but the user must be certified frequently for substantiation.

Proposed System

In this paper mainly expose with web-based multi level substantiation. In this paper complain with biometric fingerprint, web browser and mobile device. Most bio metric substantiations are Falls Acceptance Ratio (FAR) is very high and True Acceptance Ratio (TAR) is very low. And the same time the hackers using fingerprint masking techniques, this type of techniques can generate unauthorized accessing problem. The Proposed System avoiding this type of problem and create effective substantiation and same time secured substantiation. This research mainly has two phases. Those are Enrollment and Substantiation.

Enrollment

This enrollment process is mainly included for image accusation, fingerprint features extraction and user mobile number are stored in encrypted form to the particular database. This section is used to do the registration process.

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Image Accusation: Read the fingerprint image from biometric scanner of the user side. This device is used for convert the scanned image into digital form.

Fingerprint Enhancement: Various types of biometric scanner are used for image accusation. Some devices are generating more noise in the fingerprint image. These types of fingerprint images are generating FAR are very high. So we are using noise reduction and enhancement techniques. Gabor based ridge enhancement method is supporting for enhance the finger print ridges. So this type of fingerprint enhancement techniques is improving the TAR level.

Feature Extractor: Fingerprint features are used to fingerprint matching process. Feature extractor is include for various process.,

Binarization: Using threshold, the system convert the enhanced fingerprint image to

binarization image.

Thinning: Morphological operation is supported to convert binary image into thinning image.

Core point Detection: Apply ridge orientation based core point detection algorithm, to finding the core point in the fingerprint image.

Minutia Extraction: Three types of minutiae are available in the fingerprint image; they are Bifurcation, Ridge End and Dots. Template Based minutia extraction method is used to extract the bifurcation minutia. Also the same method is used to extract the ridge-end minutia.

Cryptosystem: AES algorithm is used for, extracted fingerprint features and mobile numbers. These are converted to encryption format to store the particular database.

Authentication

This is mainly includes two types of authentication, one is fingerprint matching and another one is mobile pin number matching. Pin number matching process is supported with mobile network. Authentication process also includes, fingerprint accusation, enhancement and features extraction.

Database: Database has the fingerprint features and user mobile numbers, in encrypted format. At the time of Fingerprint matching, encrypted features are converted to decrypted format.

Fingerprint Matcher: Base Line Matching algorithm is used to match the query fingerprint features and decrypted database fingerprint features. If the matched result is given more than or equal 90% (FPF >= 90), at that time the authenticator allow the user to next stage. If the Matched result is given below 90% and above 80% or equal (FPF > 90 & FPF <=80 %) , at that time the process will be go to the random number generator. This process is second level security. If the matched result is given below 80% (FPF > 80) at that time failure message will be displayed such as "fingerprint is not matched to the database", so the user is not an authenticated person.

Random Num Generator: Random Num Generator generating a random number and send the numbers to two areas. One is pin number matcher and another one is send to mobile network. Mobile network receives the pin number. The mobile network sends the pin number through SMS. The corresponding mobile number is taken form database. A user receives the pin number and enters in the appropriate area.

Pin Num Matcher: The pin number matcher receives the original pin number from random generator and check the pin number from user. If the pin numbers are same at that time the user is declared as authenticated otherwise the user is unauthenticated.

Mobile Num Registration

Biometric Sensor

Enhancement

Module

Feature

Extractor

Encryption

Public Cloud Database

User

Private Cloud Database

Enrollment

Not Matching

Go to

Next Stage

Not Matching

Biometric Sensor

Enhancement

Module

Feature

Extractor

Matcher

Decryption

If FPF >= 90 %

else if

FPF >= 80% & FPF < 90%

Random Num

Generator

Send SMS to User Mobile

User

Mobile

Network

else

Yes

FPF > 80

Enter

Pin Num

Pin Num Matcher

NO

Yes

Private Cloud Database

Public Cloud Database

Authentication