Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Swamy, S.C.

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    A Security Approach to Build a Trustworthy Ubiquitous Learning System
    (Institute of Electrical and Electronics Engineers Inc., 2020) Samyama Gunjal, S.G.; Swamy, S.C.
    Modern learning systems, say a tutoring platform, has many characteristics like digital data presentation with interactivity, mobility, which provides information about the study-content as per the learners understanding levels, intelligent learners behavior, etc. A sophisticated ubiquitous learner system maintains security and monitors the mischievous behavior of the learner, and authenticates and authorizes every learner, which is quintessential. Some of the existing security schemes aim only at single entry-point authentication, which may not suit to ubiquitous tutor platform. We propose a secured authentication scheme which is based on the information utility of the learner. Whenever a learner moves into a tutor platform, which has ubiquitous learner system technology, the system at first-begins with learners' identity authentication, and then it initiates trust evaluation after the successful authentication of the learner. Periodic credential verification of the learner will be carried out, which intensifies the authentication scheme of the system proposed. BAN logic has been used to prove the authentication in this system. The proposed authentication scheme has been simulated and analyzed for the indoor tutor platform environment. © 2020 IEEE.
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    Household Vehicle Ownership Prediction Using Machine Learning Approach
    (Institute of Electrical and Electronics Engineers Inc., 2022) Manjushree, N.S.; Samyama Gunjal, G.H.; Swamy, S.C.; Giridharan, A.
    Predictions of vehicle ownership and their influencing factors play an important role in transportation policy making. In the era of urbanization and globalization, vehicle ownership patterns have become a more relevant issue in developing countries attempting to achieve sustainable transportation development goals. Machine learning techniques facilitate tremendously in predicting the vehicle ownership patterns, required to achieve the above said goal. In the proposed work, the machine learning models such as decision tree, random forest and multinomial logistic regression models are applied over household datasets, to predict the household factors influencing vehicle ownership. According to the ML model, influencing factors on Household Vehicle Ownership (HVO) prediction are number of persons having DL in a household, number of persons drive in a household, number of persons using ride source service or public transport in a household. Analysis of datasets showed that, total income of a household, number of persons in household and distance travelled each day are positively associated with vehicle ownership of the household. The predictions of this study would be useful mainly for local governments, transportation agencies, planners and policy-makers. © 2022 IEEE.
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    Designing Secure Clusters using Blockchain for IoT
    (Institute of Electrical and Electronics Engineers Inc., 2022) Karthik, B.; Samyama Gunjal, G.H.; Manjushree, N.S.; Swamy, S.C.
    Internet of Things(IoT) has become a major component of our lives, where numerous independent devices connect, communicate and interact with one another. It is an evolving technology where devices are intelligent, independent and exchange information with one another without the need for human intervention. Hence these devices must identify, authenticate each other and ensure data integrity and security to avoid being targeted by various malicious attacks. To overcome these limits, a secure decentralized system has been proposed in this work. Here devices can create secure clusters along with security features provided by blockchains, where devices can identify, authenticate and trust each other for data integrity and availability. The implementation of proposed work is done using java and python language and also using ethereum blockchain. Initially, there was only one mode of communication where devices belonging to the same cluster could communicate with each other which are termed as Intra cluster communication. In the proposed system, major focus is on the Inter cluster communication where devices belonging to different clusters can communicate with each other. By using inter cluster communication, the performance and availability of data for the application are enhanced. The results obtained in the proposed work will satisfy the security, efficiency, and low cost needs of the Internet of Things. © 2022 IEEE.