What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Computer network
Gautam Srivastava mainly focuses on Artificial intelligence, Computer security, Blockchain, The Internet and Computational intelligence.
His work in Artificial intelligence addresses issues such as Machine learning, which are connected to fields such as Heart disease, Fuzzy logic and Linear discriminant analysis.
His study looks at the intersection of Computer security and topics like Protocol with Payment, Exploit and Service.
His Blockchain study frequently links to other fields, such as Authentication.
Gautam Srivastava has included themes like Cryptography, Digital signature, Mutual authentication, Message queue and Overhead in his The Internet study.
His research integrates issues of Key management, Health professionals, Cryptographic primitive, Wearable technology and Big data in his study of Smart contract.
His most cited work include:
- A Decentralized Privacy-Preserving Healthcare Blockchain for IoT (192 citations)
- A Decentralized Privacy-Preserving Healthcare Blockchain for IoT (192 citations)
- Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques (112 citations)
What are the main themes of his work throughout his whole career to date?
Gautam Srivastava mostly deals with Artificial intelligence, Computer security, The Internet, Machine learning and Computer network.
His Pattern recognition research extends to Artificial intelligence, which is thematically connected.
His Computer security research is multidisciplinary, incorporating perspectives in Cloud computing and Protocol.
Machine learning is frequently linked to Malware in his study.
His study in Network packet and Encryption are all subfields of Computer network.
Many of his studies involve connections with topics such as Scalability and Blockchain.
He most often published in these fields:
- Artificial intelligence (35.93%)
- Computer security (23.95%)
- The Internet (18.26%)
What were the highlights of his more recent work (between 2020-2021)?
- Artificial intelligence (35.93%)
- The Internet (18.26%)
- Data mining (13.17%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, The Internet, Data mining, Computer security and Machine learning.
His Artificial intelligence research includes elements of Natural language processing and Pattern recognition.
His work carried out in the field of The Internet brings together such families of science as Computer network, Cloud computing and Blockchain.
His study looks at the relationship between Blockchain and topics such as Authentication, which overlap with Botnet.
His study in the field of Smart contract, Backdoor and Encryption is also linked to topics like Bridge.
As part of one scientific family, Gautam Srivastava deals mainly with the area of Smart contract, narrowing it down to issues related to the Cheque, and often Big data.
Between 2020 and 2021, his most popular works were:
- A survey on security and privacy of federated learning (26 citations)
- A survey on security and privacy of federated learning (26 citations)
- Efficient and Privacy-Preserving Medical Research Support Platform Against COVID-19: A Blockchain-Based Approach (24 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Computer network
His primary scientific interests are in Artificial intelligence, The Internet, Deep learning, Computer security and Machine learning.
His work in the fields of Artificial intelligence, such as Feature extraction, intersects with other areas such as Resource management.
His The Internet study incorporates themes from Distributed computing, Proof-of-stake, Blockchain and Data mining.
His work on Authentication, Information privacy and Backdoor as part of general Computer security research is frequently linked to Bridge, thereby connecting diverse disciplines of science.
His Authentication research focuses on Botnet and how it relates to Scalability.
His studies in Machine learning integrate themes in fields like Convolution, Human behavior and Knowledge extraction.
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