Abhisek Banerjee | Cybersecurity | Best Researcher Award

Mr. Abhisek Banerjee | Cybersecurity | Best Researcher Award

Mr at Indian Institute of Information Technology India

Abhisek Banerjee is a Lead Technical Architect with over 19 years of IT experience, specializing in AI, Cloud Security, Digital Transformation, and Application Integration. He is currently a PhD scholar at the Indian Institute of Information Technology, Kalyani, focusing on Gen AI-based security solutions. With deep expertise in cloud platforms (Oracle Cloud, AWS, Azure), he has led numerous enterprise-level digital transformation projects, integrating cutting-edge technologies like Langchain, Hugging Face, TensorFlow, and Keras to drive business innovation. His work emphasizes enhancing operational efficiency, securing data, and mitigating security vulnerabilities in multi-cloud environments.

Profile

Scopus

 

Education 🎓

PhD (Pursuing) – Indian Institute of Information Technology, Kalyani, India. ME (IT – Software Engineering) – Jadavpur University, 2005, 81.6%. BTech (Electronics & Telecom Engineering) – University of Kalyani, 2003, 81.4%. Higher Secondary (12th) – R.K.M.V.C.College, Rahara [WBBHSC], 1999, 85%.; Secondary (10th) – R.K.M. Boys’ Home High School, Rahara [WBBSE], 1997, 90.3%

Experience 🧑‍🏫

With over 19 years of experience, Abhisek Banerjee has handled large-scale digital transformation initiatives, focusing on multi-cloud environments (Oracle Cloud, AWS, Azure). He has led projects in application modernization, data integration, and cloud security, architecting solutions using cutting-edge technologies such as Langchain, Hugging Face, TensorFlow, and Keras. He has engineered seamless data integration frameworks, API-led connectivity, and cloud-native security solutions, ensuring compliance and data protection. Additionally, Abhisek has worked on the design of microservices, DevOps automation, and advanced machine learning models for cloud security. His contributions include deploying robust data privacy measures and threat detection frameworks across cloud platforms.

Awards and Honors 🏆

Research Excellence Award (GEU, DDN) in 2015 for outstanding research contributions. Early Career Research Award from the Science and Engineering Research Board (SERB), 2017. DST Travel Grant (2012) to attend an international conference in Pittsburgh, USA. Best Paper Presentation Award at TriboIndia-2023 Conference, NIT Srinagar. GUCOST and DTE Funding for workshops on cloud technologies and security. Membership in the International Association of Advanced Materials (IAAM) for five years.

Research Focus 🔍

Abhisek’s research focuses on cloud security vulnerabilities, with a specific interest in the detection and remediation of covert malware attacks using machine learning and deep learning techniques. His work integrates Generative AI, CNN, Vision Transformer, and GAN models to address threats like steganography-based backdoor attacks in cloud environments. By utilizing Computer Vision techniques and AI-driven models, he aims to develop intelligent security solutions that can proactively identify and neutralize security threats. Abhisek’s current projects involve training custom AI models for threat detection and deploying them within multi-cloud architectures to ensure data integrity and privacy. His research has the potential to revolutionize cybersecurity strategies in cloud and IoT ecosystems.

Conclusion

This individual demonstrates significant research excellence, particularly in Metallurgical & Materials Engineering, with notable contributions recognized by both national and international bodies. Their impressive list of awards, research experience, and funding achievements make them a strong contender for the Best Researcher Award. By expanding their research collaborations, improving visibility in high-impact journals, and engaging more publicly in research discourse, they can further enhance their profile and continue making substantial contributions to their field.

Publications 📚

  • “A Study on Multivariable Process Control Using Message Passing Across Embedded Controllers”
    • Journal: ISA Transactions
    • Volume: 46(2), Pages 247–253
    • Year: 2007
    • Authors: Das, M.; Banerjee, A.; Ghosh, R.; Chandra, A.K.; Gupta, A.
    • Citations: 6

 

  • “A Study on Hardware-in-Loop Simulation with Embedded Controllers Using TCP/IP and UDP”
    • Conference: 3rd International Conference on Computing, Communications and Control Technologies (CCCT 2005)
    • Volume: 3, Pages 103–108
    • Year: 2005
    • Authors: Banerjee, A.; Das, M.; Ghosh, R.; Balasubramanian, R.; Gupta, A.
    • Citations: 1

 

Farah Jemili | Cybersécurité

Assist Prof Dr Farah Jemili: Leading Researcher in Cybersécurité

Assist Prof Dr Farah Jemili at University of Sousse Tunisia.

🎉🏆Congratulations, Assist Prof Dr Farah Jemili, on winning the esteemed Women Researcher Award from Young scientist Awards! Your dedication, innovative research, and scholarly contributions have truly made a significant impact in your field. Your commitment to advancing knowledge and pushing the boundaries of research is commendable. Here’s to your continued success in shaping the future of academia and making invaluable contributions to your field. Well done 🌟

👨‍🏫  Farah Jemili, an Professor at the  University of Sousse, Tunisia, stands as a distinguished academic and researcher in the Computer Science. Holding a Ph.D Assistant Professor research in artificial intelligence &Big Data Analysis at MARS lab.,IsITCom, University of Sousse, Tunisia . their professional journey exemplifies dedication and expertise. 📚

Professional Profile

Academic Qualifications

Ph.D, Eng., Assistant Professor, Researcher in Artificial Intelligence & Big Data Analysis at MARS Lab , ISITCom, University of Sousse, Tunisia

💼Employment :

Assistant Professor(FSB BIZERTE) 2004 to 2010|Employment

Farah Jemili’s citation metrics and indices from Google Scholar are as follows:

📊 Citation Metrics (Google Scholar):

  • Cited by: All – 398, Since 2018 – 286
  • h-index: All – 11, Since 2018 – 9
  • i10-index : All -11 Since 2018 -9
Publications

32 Documents

📚Top Noted Publications (Journals)

A framework for an adaptive intrusion detection system using Bayesian network  Published in 2007/5/23 Cited by 115

Distributed deep learning approach for intrusion detection system in industrial control systems based on big data technique and transfer learning Published online: 25 Jul 2023.

A framework for an adaptive intrusion detection system using Bayesian network

Using MongoDB databases for training and combining intrusion detection datasets Published in 2018 Cited by 11.

A survey of attacks in mobile ad hoc networks

Anomaly-based behavioral detection in mobile Ad-Hoc networks

Real-time data fusion for intrusion detection in industrial control systems based on cloud computing and big data techniques

Distributed Architecture of an Intrusion Detection System in Industrial Control Systems Published in 2022/9/21 Cited by 8

Neuro-fuzzy and genetic-fuzzy based approaches in intrusion detection: Comparative study Published in 2017 cited by 5

OuajdiKorbaa.” Neuro-fuzzy and genetic-fuzzy based approaches in intrusion detection: Comparative study.” Software, Telecommunications and Computer Networks (SoftCOM) Published in 2017 Cited by 5