Dr. SOMNATH B THIGALE
Verified @gmail.com
Professor CSE Dept. FTC COER,Sangola
More than 16 years of experience
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Computer Networks and Communications, Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Rajesh Maharudra Patil, N. Madhukeshwara, Swagat Madhav Karve, Pranav Chippalkatti, and Somnath B. Thigale
Informa UK Limited
Shagufta Md. R. Bagwan, Sanjay Kumar, and Somnath B.Thigale
IEEE
When it comes to identifying people automatically, bio-metrics is the field of study that uses observable traits of the human body, both innate and acquired, to do so. “Bio-metrics is a rapidly developing breakthrough that is being used to increase security and verify sensitive systems. A multimodal bio-metric system combines data from several sources to solve these issues and outperform a uni-modal system in terms of recognition accuracy. Since spoofing can’t be performed on many bio-metric sources at once, multimodal systems have a lower failure to enroll rate. As a level-based method, multimodal bio-metrics combines information at several stages, including sensing, features, matches, and decisions. Because it includes more substantive information, fusion at the score level delivers superior recognition performance, and it is both possible and practicable. The purpose of this study is to evaluate the efficacy of combining fingerprint, face, and iris bio-metrics based on matching score. The fusion rule and classification are carried out using three different soft computing methodologies; the SVM classifier, the sparse SVM classifier, and the rough set fuzzy classifier”.
Shagufta Md. R. Bagwan, Gyanendra Gupta, and Somnath B.Thigale
IEEE
Compared to more traditional methods of verification, Bio-metric systems provide a greater level of safety for a wider range of uses (like pin, passwords etc.). “Bio-metric systems have broad social and practical applications. Among them include authentication for computers, attendance tracking for businesses, financial transactions, safeguarding private information, controlling access to buildings and airports, and so on. A person’s identity may be confirmed via the use of both their physical characteristics and their behavioural patterns thanks to the bio-metric system. Bio-metric systems and their effects on modern society are discussed in this article. While single-trait bio-metric user identification is widely utilised at the moment, it does not offer sufficient authentication for highly secure applications. To solve these issues, researchers have developed multi-modal bio-metric systems. User authentication in a multi-modal bio-metric system may be based on a wide variety of factors, including both physical and behavioural characteristics. Additionally, age, height, hair colour, eye colour, gender, and other “soft” bio-metric features are also employed. Even the most subtle Bio-metric methods aren’t without their flaws. Soft bio-metric iris and facial features were used to create the algorithm for the paper work multi-modal bio-metric system.: The research presented in this article enhances user authentication and security without sacrificing speed.
Somnath B. Thigale, Rahul Pandey, and Virendrakumar A. Dhotre
Springer International Publishing
Virendrakumar A. Dhtore, Avnish Raj Verma, and Somnath B. Thigale
Springer International Publishing
Somnath B. Thigale, Rahul K. Pandey, Prakash R Gadekar, Virendrakumar A. Dhotre, and Aparna A. Junnarkar
International University of Sarajevo
For IoT enabled networks, the security and privacy is one of the important research challenge due to open nature of wireless communications, especially for the networks like Vehicular Ad hoc Networks (VANETs). The characteristics like heterogeneity, constrained resources, scalability requirements, uncontrolled environment etc. makes the problems of security and privacy even more challenging. Additionally, the high degree of availability needs of IoT networks may compromise the integrity and confidentially of communication data. The security threats mainly performed during the operations of data routing, hence designing the secure routing protocol main research challenge for IoT networks. In this paper, to design the lightweight security algorithm the use of Named Data Networking (NDN) which provides the benefits applicable for IoT applications like built-in data provenance assurance, stateful forwarding etc. Therefore the novel security framework NDN based Cross-layer Attack Resistant Protocol (NCARP) proposed in this paper. In NCARP, we designed the cross-layer security technique to identify the malicious attackers in network to overcome the problems like routing overhead of cryptography and trust based techniques. The parameters from the physical layer, Median Access Control (MAC) layer, and routing/network layer used to compute and averages the trust score of each highly mobility nodes while detecting the attackers and establishing the communication links. The simulation results of NCARP is measured and compared in terms of precision, recall, throughput, packets dropped, and overhead rate with state-of-art solutions.