What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Operating system
The scientist’s investigation covers issues in Computer security, The Internet, Cloud computing, Artificial intelligence and Computer vision.
His study in Computer security is interdisciplinary in nature, drawing from both Phishing, Spoofed URL, Denial-of-service attack and Smart city.
His Denial-of-service attack research includes elements of Network security, Application layer, Digital identity and Taxonomy.
His research in The Internet intersects with topics in Layer, Bandwidth and Security privacy, Internet privacy.
His Cloud computing study combines topics in areas such as Wireless, Wireless network, Database, Computer network and Big data.
His studies in Artificial intelligence integrate themes in fields like Machine learning and Pattern recognition.
His most cited work include:
- Secure integration of IoT and Cloud Computing (505 citations)
- Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings (243 citations)
- Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security (184 citations)
What are the main themes of his work throughout his whole career to date?
Brij B. Gupta mostly deals with Computer security, Denial-of-service attack, Cloud computing, The Internet and Artificial intelligence.
His work in the fields of Authentication overlaps with other areas such as Service provider.
His Authentication research is multidisciplinary, relying on both Overhead and Public-key cryptography.
His biological study spans a wide range of topics, including Network simulation, Computer network and Flooding.
His work deals with themes such as Distributed computing and Big data, which intersect with Cloud computing.
He works mostly in the field of Artificial intelligence, limiting it down to topics relating to Machine learning and, in certain cases, Phishing, as a part of the same area of interest.
He most often published in these fields:
- Computer security (49.11%)
- Denial-of-service attack (24.68%)
- Cloud computing (18.58%)
What were the highlights of his more recent work (between 2020-2021)?
- Artificial intelligence (21.12%)
- Computer security (49.11%)
- Denial-of-service attack (24.68%)
In recent papers he was focusing on the following fields of study:
Brij B. Gupta spends much of his time researching Artificial intelligence, Computer security, Denial-of-service attack, Machine learning and Deep learning.
His study focuses on the intersection of Artificial intelligence and fields such as Pattern recognition with connections in the field of F1 score, Centroid and Intelligent decision support system.
His work on Authentication as part of general Computer security research is often related to Defence mechanisms, thus linking different fields of science.
Brij B. Gupta combines subjects such as Probabilistic logic, Cloud computing and Reliability with his study of Denial-of-service attack.
The Cloud computing study combines topics in areas such as Variable, Computer network and The Internet.
The study incorporates disciplines such as Fake news, Internet privacy and Social network in addition to Deep learning.
Between 2020 and 2021, his most popular works were:
- Blockchain-based authentication and authorization for smart city applications (49 citations)
- Blockchain-based authentication and authorization for smart city applications (49 citations)
- IoT-Based Big Data Secure Management in the Fog Over a 6G Wireless Network (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- The Internet
His scientific interests lie mostly in Computer security, Artificial intelligence, Deep learning, Reputation and Convolutional neural network.
His Computer security research includes themes of The Internet, Denial-of-service attack and Big data.
The concepts of his Big data study are interwoven with issues in Computer network and Cloud computing.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Fake news, Internet privacy and Social network.
His research integrates issues of Image, Enhanced Data Rates for GSM Evolution, Set and Pattern recognition in his study of Deep learning.
He has included themes like Small and medium-sized enterprises, Cross-site scripting, Information privacy and Payload in his Convolutional neural network study.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
