Work place: Department of Computer Engineering, Pillai College of Engineering, Navi Mumbai, Mumbai University
E-mail: vsat2k@mes.ac.in
Website:
Research Interests: Data Mining, Machine Learning
Biography
Satishkumar L. Varma has completed his Ph.D. in Computer Science and Engineering under the guidance of Dr. S N Talbar from SGGS I E & T, SRTMU, Nanded, India in March 2013. He received B. Tech and M. Tech degrees in Computer Engineering from DBAT University at Lonere, Maharashtra, India in June 2000 and January 2004 respectively. He has over 19 years of the academic experience at Mumbai University, India. He is a reviewer in various Conferences and Journals including IEEE Transaction on Image Processing, Springer Signal, Image and Video Processing, Wiley ETRI Journal, etc. With 1 copyright, he has published 7 Book Chapters, 31 Journal papers, and more than 36 papers in referred National as well as International Conferences including IEEE, Springer, and IET with a second-best paper award at National level paper presentation competition in Threshold–2000. His research activities involve Digital Image and Video Processing, Medical Imaging, AI and Machine Learning, Soft Computing, Data Mining, and Information Retrieval.
By Mimi M Cherian Satishkumar L. Varma
DOI: https://doi.org/10.5815/ijcnis.2022.01.05, Pub. Date: 8 Feb. 2022
In recent years the domain of Internet of Things (IoT) has acquired great interest from the ICT community. Environmental observation and collecting information is one of the key reasons that IoT infrastructure facilitates the creation of many varieties of the latest business methods and applications. There are however still issues about security measures to be resolved to ensure adequate operation of devices. Distributed Denial of Service (DDoS) attacks are currently the most severe virtual threats that are causing serious damage to many IoT devices. With this in mind, numerous research projects were carried out to discover new methods and develop Novel techniques and solutions for DDOS attacks prevention. The use of new technology, such as software-defined networking (SDN) along with IoT devices has proven to be an innovative solution to mitigate DDoS attacks. In this article, we are using a novel data sharing system in IoT units that link IoT units with the SDN controller and encrypt information from IoT unit. We use conventional Redstone cryptographic algorithms to encrypt information from IoT devices in this framework. The Proposed Belief Based Secure Correlation methodology supports the prevention of DDOS attacks and other forms of data attacks. The system proposes new routes for transmission through the controller and communicates with approved switches for the safe transmission of data. To simulate our entire scenario, we proposed the algorithm Belief Based Secure Correlation (BBSC) implemented in SDN–IoT Testbed and verified IoT data is secure during transmission in the network.
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