SECURITY SERVICES
1.A Survey Of Biometrics Security System:
International Journal of Engineering Research in Computer Science and Engineering (IJERCSE) Vol 2, Issue 8, August 2015.
Biometrics refers to the automatic identification of person based on his/her physiological or behavioral characteristics. This method of identification is preferred over traditional methods involving passwords and PIN numbers for various reasons: the person to be identified is required to be physically present at the point of identification. The identification based on biometric techniques obviates the need to remember a password or carry a token. With the increased use of computers as vehicles of information technology, it is necessary to restrict access to sensitive/personal data. By replacing PINs, biometric techniques can potentially prevent unauthorized access to or fraudulent use of ATMs, cellular phones, smart cards, desktop PCs, workstations, and computer networks. PINs and passwords may be forgotten, and token based methods of identification like passports and driver's licenses may be forged, stolen, or lost. Thus biometric systems of identification are enjoying a renewed interest. Various types of biometric systems are being used for real-time identification, the most popular are based on face recognition and fingerprint matching. However, there are other biometric systems that utilize iris and retinal scan, speech, facial thermo grams, and hand geometry. A biometric system is essentially a pattern recognition system which makes a personal identification by determining the authenticity of a specific physiological or behavioral characteristics possessed by the user.
2.Face Description With Local Binary Patterns:
Application to Face Recognition:Timo Ahonen, Student Member, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 28, NO. 12, DECEMBER 2014
This paper presents efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a face descriptor.The performance of the proposed method is assessed in the face recognition problem under different challenges.The LBP operator was originally designed for texture description. The operator assigns a label to every pixel of an image by thresholding the 3x3 neighborhood of each pixel with the center pixel value and considering the result as a binary number. In this work, the LBP method presented in the previous section is used for face description. The procedure consists of using the texture descriptor to build several local descriptions of the face and combining them into a global description. Instead of striving for a holistic description, this approach was motivated by two reasons the local feature-based hybrid approaches to face recognition have been gaining interest lately , which is understandable given the limitations of the holistic representations. These local feature-based and hybrid methods seem to be more robust against variations in pose or illumination than holistic methods. Another reason for selecting the local feature-based approach is that trying to build a holistic description of a face using texture methods is not reasonable since texture descriptors tend to average over the image area. This is a desirable property for ordinary textures, because texture description should usually be invariant to translation or even rotation of the texture and especially, for small repetitive textures, the small-scale relationships determine the appearance of the texture and thus, the largescale relations do not contain useful information.
3.Continuous Authentication Using Multimodal Biometrics:
“Face recognition using eigenfaces” in IEEE-2015 Conference on Computer Vision and Pattern Recognition.
USER authentication is extremely important for computer and network system security. Currently, knowledge-based methods (e.g., passwords) and token-based methods(e.g:smart cards) are the most popular approaches. However, these methods have a number of security flaws. For example, passwords can be easily shared, stolen, and forgotten .Similarly, smart cards can be shared, stolen, duplicated, or lost. To circumvent these issues, a number of login authentication methods, including textual, graphical passwords and biometric authentication have been utilized. All of the above login methods share a common problem, namely, they authenticate a user only at the initial login session and do not reauthenticate a user until the user logs out. Anyone can access the system resources if the initial user does not properly log out or the user leaves the workstation unattended to take a short break without logging out. To resolve this problem, the system must continuously monitor and authenticate the user after the initial login session. In order to achieve this objective, need to develop robust, reliable, and user-friendly methods for continuous user authentication. It is desirable that the resulting system has good usability by authenticating a user without his active cooperation.
Continuous Authentication is essential in online examinations where the user has to be continuously verified during the entire session. It can be used in many real time applications, when accessing a secure file or during the online banking transactions where there is need of highly secure continuous verification of the user. A number of biometric characteristics exist and are used in various applications. Each biometric has its own strengths and weaknesses, and the choice depends on the application some of the commonly used hard biometrics are Face, Hand geometry, Fingerprint, Iris. Soft biometrics include Keystroke, Voice, Color of the clothing, Facial color etc. Single biometric trait (unimodal technique) is not sufficient to authenticate a user continuously because the system sometimes cannot observe the bio-metric information. To address the limitations of single biometrics, using multimodal biometrics is a good solution. It is the combination of two or more biometric traits to raise systems security and reliability. Multimodal has several advantage over unimodal. Combining the results obtained by different biometric traits by an effective fusion scheme can significantly improve the overall accuracy of the biometric system. Multimodal system increases the number of individuals that can enroll. It provides resistance against spoofing. The proposed work includes Sclera and Fingerprint as their Multimodal biometric traits for continuous authentication of the user. The blood vessel structure of the sclera is unique to each person, and it can be remotely obtained non-intrusively in the visible wavelengths.
4.Utlising Biometrics For Transparent User Authentication OnDevice:
Sevasti Karatzouni, Nathan L. Clarke and Steven M. Furnell ,Member,IEEE-2015
The increasing capabilities of mobile handsets and networks have enabled the creation of a wide range of datacentric services. The volume of information that can be stored and accessed through mobile devices have become enormous. This has raised significant concerns regarding the sensitivity of the information for both individual and more particularly organizations. A recent study by Gartner reports 80% of organizations critical information is stored on mobile devices. It can be therefore suggested that providing appropriate protection against unauthorized access to information becomes significantly important.
A significant component of the device security consists of user authentication. The current authentication facility in mobile handsets is primarily achieved by the Personal Identification Number (PIN). Unfortunately PINs, being a secret-knowledge technique, have a number of well documented drawbacks: security relies on the user and therefore bad practices from the latter significantly diminishes the security that PINs provide.
All authentication approaches, including bio-metric approaches, have focused upon establishing point-of-entry authentication of the user. Although this is imperative to establish at the beginning of a session, unfortunately no further verification of the user is undertaken until the device is switched off again. With the increasing reliance upon mobile devices, few devices are now actually even switched off, removing any protection point-of-entry solutions offer. The ability to provide non-intrusive authentication in a transparent fashion, without the explicit interaction of the user will assist in establishing the identity of the user throughout the session. Of the three authentication approaches: secret-knowledge, tokens and bio-metrics, only the latter really provides an effective mechanism to achieve this. Through the careful application of particular bio-metric techniques it could be possible to not only increase security but do so in a user convenient manner. It is important however to utilize techniques that lend themselves towards transparent application.
