Kakoli Banerjee

Work place: JSS Academy of Technical Education, Noida, Uttar Pradesh, India

E-mail: kakoli.banerjee@jssaten.ac.in


Research Interests: Computer Science & Information Technology


Dr. Kakoli Banerjee, Associate Professor (Computer Science and Engineering Department), JSS Academy of Technical Education, Noida. She graduated from IET, Kanpur – B.Tech (CSE), did her Post Graduation from MNNIT, Allahabad – M.Tech (CSE) and Doctorate (Ph.D) from Shobhit University, Saharanpur. She has 22 years’ of experience in academics and in industry. She have published around 45 research papers in international journals of repute indexed in SCI, Scopus, ESCI, Google Scholar, and other eminent databases. Currently, she is working for a funded projects, sanctioned by the Collaborative Research and Innovation Program (CRIP) under TEQIP- 3 by Dr. A. P. J. Abdul, Kalam Technical University Uttar Pradesh, Lucknow. She is a member of IEEE and other professional societies such as ISTE, CSI, etc. She has been a reviewer and guest editor of several reputed journals and books. She has also served in many conferences as session chair. She has two Granted Patent to my name and eight published. She has developed video content for Dr. A.P.J. Abdul Kalam Technical University, Lucknow and Swayamprabha Chanel of Government of India for subjects like Operating System and Database Management System. She has published book - "Industry 4.0: Research Trends, Challenges and Future of AI in Data Science", CRC Press, Taylor & Francis Group and "Decision Analytics for Sustainable Development in Smart Society 5.0”, Springer Nature.

Author Articles
An Enhanced Method Utilizing Hopfield Neural Model for Mobile Agent Protection

By Pradeep Kumar Niraj Singhal Ajay Kumar Kakoli Banerjee

DOI: https://doi.org/10.5815/ijwmt.2023.05.03, 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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