Niraj Singhal

Work place: Shobhit Institute of Engineering & Technology (Deemed to-be-University), Meerut,250110, India



Research Interests: Web Technologies, Information Retrieval, Software Engineering, Software


Dr. Niraj Singhal is Ph.D. (Computer Engineering and Information Technology). He is Fellow and member of several International/National bodies and, reviewer and member of the advisory board for several International/National journals. He has many research publications to his credit in National/ International journals/conferences of repute. He has several years of rich experience of administration, coordinating and teaching at various levels. Presently he is working as Professor in the department of Computer Science and Engineering at Shobhit Institute of Engineering & Technology (Deemed-to-be University), Meerut. His area of interest includes system software, web information retrieval and software agents.

Author Articles
An Optimized Authentication Mechanism for Mobile Agents by Using Machine Learning

By Pradeep Kumar Niraj Singhal Mohammad Asim Avimanyou Vatsa

DOI:, Pub. Date: 8 Dec. 2023

A mobile agent is a small piece of software which works on direction of its source platform on a regular basis. Because mobile agents roam around wide area networks autonomously, the protection of the agents and platforms is a serious worry. The number of mobile agents-based software applications has increased dramatically over the past year. It has also enhanced the security risks associated with such applications. Most of the security mechanisms in the mobile agent architecture focus solely on platform security, leaving mobile agent safety to be a significant challenge. An efficient authentication scheme is proposed in this article to address the situation of protection and authentication of mobile agent at the hour of migration of across multiple platforms in malicious environment. An authentication mechanism for the mobile agent based on the Hopfield neural network proposed. The mobile agent’s identity and password are authenticate using the specified mechanism at the moment of execution of assigned operation. An evaluative assessment has been offered, along with their complex character, in comparison to numerous agent authentication approaches. The proposed method has been put into practice, and its different aspects have been put to the test. In contrasted to typical client-server and code-on-demand approaches, the analysis shows that computation here is often more safe and simpler.

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An Enhanced Method Utilizing Hopfield Neural Model for Mobile Agent Protection

By Pradeep Kumar Niraj Singhal Ajay Kumar Kakoli Banerjee

DOI:, Pub. Date: 8 Oct. 2023

Mobile agent is a piece of computer code that organically goes from one host to the another in a consistent or inconsistent environment to distribute data among users. An autonomous mobile agent is an operational programme that may migrate from one computer to machine in different networks under its own direction. Numerous health care procedures use the mobile agent concept. An agent can choose to either follow a predetermined course on the network or determine its own path using information gathered from the network. Security concerns are the main issue with mobile agents. Agent servers that provide the agents with a setting for prosecution are vulnerable to attack by cunning agents. In the same way agent could be carrying sensitive information like credit card details, national level security message, passwords and attackers can access these files by acting as a middle man. In this paper, optimized approach is provided to encrypt the data carried by mobile agent with Advanced Encryption Standard (AES) algorithm and secure key to be utilized by the AES Encryption algorithm is generated with the help of Hopfield Neural Network (HNN). To validate our approach, the comparison is done and found that the time taken to generate the key using HNN is 1101ms for 1000 iterations which is lesser than the existing models that are Recurrent Neural Networks and Multilayer Perceptron Network models. To add an additional level of security, data is encoded using hash maps which make the data not easily readable even after decrypting the information. In this way it is ensured that, when the confidential data is transmitted between the sender and the receiver, no one can regenerate the message as there is no exchange of key involved in the process.

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Secure Mobile Agent Migration Using Lagrange Interpolation and Fast Fourier Transformation

By Pradeep Kumar Niraj Singhal Dhiraj Pandey Avimanyou Vatsa

DOI:, Pub. Date: 8 Aug. 2023

Mobile agent is a processing unit works on the behalf of host computer. Mobile agent with intelligence provides a new computing prototype that is totally different from conventional prototype. Mobile agents are automatically itinerating from one host Computer to another host computer and execute assigned task on the behalf of user in heterogeneous environment under own control. Because mobile agents roam around distributed networks automatically, the security of the agents and platforms is a major concern. The number of mobile agents-based software applications has increased dramatically over the past year. It has also enhanced the security risks associated with such applications. Most protection systems in the mobile agent paradigm focus on platform security and provide few guidelines for mobile agent security, which is still a challenging topic. There is a risk to information carries by mobile agents from the malicious mobile agents who can modify and steal the confidential information. In this paper proposed multilevel authentication framework of mobile agents and platform based on Lagrange interpolation and fast Fourier transformation (LIFFT). In this frame work ‘n’ number of mobile agent have two level of security first level key used authentication and second level of key used for execution of mobile agents.

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