Preet Inder Singh

Work place: Department of CSE/IT, Lovely Professional University (Punjab), Phagwara

E-mail: preetindermail@gmail.com

Website:

Research Interests: Data Structures and Algorithms, Network Security, Artificial Intelligence, Computer systems and computational processes

Biography

Preet Inder Singh: M.Sc computer Science from D.A.V College, Amritsar in 2010. Currently pursuing M.Tech (CSE/IT) from Lovely Professional University, Phagwara, interested in Network Security, Multi-media and Artificial Intelligent Systems.

Author Articles
Digital Image Enhancement with Fuzzy Interface System

By Amanpreet Singh Preet Inder Singh Prabhpreet Kaur

DOI: https://doi.org/10.5815/ijitcs.2012.10.06, Pub. Date: 8 Sep. 2012

Present day application requires various version kinds of images and pictures as sources of information for interpretation and analysis. Whenever an image is converted from one form to another, such as, digitizing, scanning, transmitting, storing, etc. Some form of degradation occurs at the output. Hence, the output image has to undergo a process called image enhancement which consist of a collection of techniques that seeks to improve the visual appearances of an image. Image enhancement technique is basically improving the perception of information in images for human viewers and providing 'better' input for other automated image processing techniques. This thesis presents a new approach for image enhancement with fuzzy interface system. Fuzzy techniques can manage the vagueness and ambiguity efficiently (an image can be represented as fuzzy set). Fuzzy logic is a powerful tool to represent and process human knowledge in form of fuzzy if-then rules. Compared to other filtering techniques, fuzzy filter gives the better performance and is able to represent knowledge in a comprehensible way.

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Robust Security System for Critical Computers

By Preet Inder Singh

DOI: https://doi.org/10.5815/ijitcs.2012.06.04, Pub. Date: 8 Jun. 2012

Among the various means of available resource protection including biometrics, password based system is most simple, user friendly, cost effective and commonly used, but this system having high sensitivity with attacks. Most of the advanced methods for authentication based on password encrypt the contents of password before storing or transmitting in physical domain. But all conventional cryptographic based encryption methods are having its own limitations, generally either in terms of complexity, efficiency or in terms of security. In this paper a simple method is developed that provide more secure and efficient means of authentication, at the same time simple in design for critical systems. Apart from protection, a step toward perfect security has taken by adding the feature of intruder detection along with the protection system. This is possible by merging various security systems with each other i.e password based security with keystroke dynamic, thumb impression with retina scan associated with the users. This new method is centrally based on user behavior and users related security system, which provides the robust security to the critical systems with intruder detection facilities.

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Enhanced Password Based Security System Based on User Behavior using Neural Networks

By Preet Inder Singh Gour Sundar Mitra Thakur

DOI: https://doi.org/10.5815/ijieeb.2012.02.05, Pub. Date: 8 Apr. 2012

There are multiple numbers of security systems are available to protect your computer/resources. Among them, password based systems are the most commonly used system due to its simplicity, applicability and cost effectiveness But these types of systems have higher sensitivity to cyber-attack. Most of the advanced methods for authentication based on password security encrypt the contents of password before storing or transmitting in the physical domain. But all conventional encryption methods are having its own limitations, generally either in terms of complexity or in terms of efficiency.
In this paper an enhanced password based security system has been proposed based on user typing behavior, which will attempt to identify authenticity of any user failing to login in first few attempts by analyzing the basic user behaviors/activities and finally training them through neural network and classifying them as genuine or intruder.

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