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Your search keyword '"Pamula, Rajendra"' showing total 111 results
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111 results on '"Pamula, Rajendra"'

2. Genetic Algorithm Based Anomaly Detection for Intrusion Detection

Author

Mayanglambam, Sushilata D., Hulke, Nainesh, Pamula, Rajendra, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Das, Prodipto, editor, Begum, Shahin Ara, editor, and Buyya, Rajkumar, editor

Published
2024
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3. Turbulent Particle Swarm Optimization and Genetic Algorithm for Function Maximization

Author

Mayanglambam, Sushilata D., Kumar, V. D. Ambeth, Pamula, Rajendra, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Namasudra, Suyel, editor, Trivedi, Munesh Chandra, editor, Crespo, Ruben Gonzalez, editor, and Lorenz, Pascal, editor

Published
2024
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34. Blockchain-enabled secure and efficient data sharing scheme for trust management in healthcare smartphone network

Author

Rati Bhan Rati Bhan, Rajendra Pamula Rajendra Pamula, Parvez Faruki Parvez Faruki, and Jyoti Gajrani Jyoti Gajrani

Subjects
Hardware and Architecture, Software, Information Systems, Theoretical Computer Science
Abstract

Internet of Medical Things (IoMT) is an extended genre of Internet of Things (IoT) where the Things collaborate to provide remote patient health monitoring, also known as the Internet of Health (IoH). Smartphones and IoMTs' are expected to maintain a secure and trusted confidential patient-records exchange while managing the patient remotely. Healthcare organizations deploy Healthcare Smartphone Networks (HSN) for confidential patient data collection and sharing among smartphone users and IoMT nodes. However, the attackers gain access to confidential patient data via compromised/malicious IoMT nodes from the HSN. Additionally, attackers can compromise the entire network via the compromised nodes. This article proposes a Hyperledger blockchain-based technique to identify the compromised IoMT nodes and safeguard sensitive patient records. Furthermore, the paper proposes a Clustered Hierarchical Trust Management System (CHTMS) to block malicious nodes. In addition, the proposal employs Elliptic Curve Cryptography (ECC) to protect sensitive health records. Similarly, the proposed approach is resilient against denial of service, eclipse attacks, and terminal device failure. Finally, the evaluation results show that integrating blockchains into the HSN system improved the detection performance compared to the existing state-of-the-art. Therefore, the simulation results indicate better security and reliability when compared to conventional databases.

Published
2023

37. A Survey and Evaluation of Android-Based Malware Evasion Techniques and Detection Frameworks.

Author

Faruki, Parvez, Bhan, Rati, Jain, Vinesh, Bhatia, Sajal, El Madhoun, Nour, and Pamula, Rajendra

Subjects
MALWARE, OPEN-ended questions
Abstract

Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing innovative techniques to avoid or prolong malware detection effectively. Past studies have shown that malware detection systems are susceptible to evasion attacks where adversaries can successfully bypass the existing security defenses and deliver the malware to the target system without being detected. The evolution of escape-resistant systems is an open research problem. This paper presents a detailed taxonomy and evaluation of Android-based malware evasion techniques deployed to circumvent malware detection. The study characterizes such evasion techniques into two broad categories, polymorphism and metamorphism, and analyses techniques used for stealth malware detection based on the malware's unique characteristics. Furthermore, the article also presents a qualitative and systematic comparison of evasion detection frameworks and their detection methodologies for Android-based malware. Finally, the survey discusses open-ended questions and potential future directions for continued research in mobile malware detection. [ABSTRACT FROM AUTHOR]

Published
2023
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