S MERCY SHALINIE
Articles written in Sadhana
Volume 45 All articles Published: 4 May 2020 Article ID 0100
P VIMALA RANI S MERCY SHALINIE
Information Centric Network (ICN) is a promising next-generation internet architecture in which the network focuses on retrieving the content by employing open in-network caching scheme to provide an efficient content distribution to users. However, such open in-network caching is vulnerable to networkanomalies. In particular, cache pollution attack disrupts the smooth working of in-network caching by flooding unpopular contents. Hence, the in-network caching malfunctions and legitimate consumer requests are dropped. To address this problem, a secure framework based on Fuzzy Restricted Boltzmann Machine has been proposed to detect the anomalies and defend against such pollution attacks in ICN. Further, a reward-based cache replacement (ReBac) algorithm that is capable of avoiding cache pollution attack has also been proposed. Theexperimental results obtained while testing the proposed framework show better detection rate compared with the state-of-art solution and the proposed framework shows better cache rate
Volume 46 All articles Published: 4 September 2021 Article ID 0181
J FELICIA LILIAN K SUNDARAKANTHAM S MERCY SHALINIE
The web contains lots of information that gets updated every second. Searching for a relevant document from the web needs an efficient scrutinization. As the user’s need varies based on location, intention and purpose the retrieval of an efficient response is a challenge. To address this challenge an informationretrieval technique has been put forth along with the advent of the machine learning and deep learning models. We have proposed a QeCSO algorithm to perform an efficient retrieval of relevant response. The AttentionbasedBi-directional LSTM (ATT-BLSTM) helps to improve the retrieval of the relevant document based on its feature that correlates the semantics between the query and the content. On further expanding the query we can observe a steep improvement in retrieving the response. To perform this, the output from ATT-BLSTM is given as an input to the meta-heuristic algorithm called cuckoo search. It helps us to retrieve the exact term to expand the query and make our search to move closer to an optimal solution. The performance of our approach iscompared to those of other models based on the evaluation metrics such as accuracy and
Volume 47 All articles Published: 18 October 2022 Article ID 0208
Blockchain-based anonymous anti-counterfeit supply chain framework
N ANITA M VIJAYALAKSHMI S MERCY SHALINIE
For the last decade, businesses and industries have been facing difficulties in tracking their products. During the supply chain process, the attackers add their counterfeit products into the market along with legitimate products. With the increase in the number of counterfeits entering the open market, it is hard todiscover the source of the counterfeit product. Most of the existing anti-counterfeit solutions are centralized. However, current solutions lack in anti-counterfeiting, decentralization, auditing, transparency, traceability, and tag cloning. To mitigate these issues, we proposed a Blockchain-based Anonymous Anti-Counterfeit (BA2C) supply chain framework that exploits Radio Frequency Identification (RFID) and blockchain technologies. The proposed model streamlined all the transactions through Ethereum, a blockchain-based platform with the support of Proof of Authority (PoA) consensus. Furthermore, the confidentiality of transactions is gained by incorporating zk-SNARKS on the Ethereum blockchain. In this work, the proposed model was tested in terms oftransaction cost, latency, and throughput. Further, it was compared with the existing system and was found to perform better transactions in the supply chain management in terms of lower cost and higher scalability. This work concluded that the proposed model was more appropriate to evaluate the critical issues of the supply chain.
Volume 48, 2023
All articles
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