Items where Author is "Jarwar, Muhammad Aslam"

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Number of items: 14.

Article

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KHOWAJA,, Sunder Ali, DAHRI, Kamran, JARWAR, Muhammad Aslam and LEE, Ik Hyun (2023). Spike learning based privacy preservation of Internet of Medical Things in Metaverse. Journal of Biomedical and Health Informatics (JBHI).

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GUOA, Wanying, QURESHI, Nawab Muhammad Faseeh, JARWAR, Muhammad Aslam, KIM, Jaehyoun and SHIN, Dong Ryeol (2023). AI-Oriented Smart Power System Transient Stability: The Rationality, Applications, Challenges and Future Opportunities. Sustainable Energy Technologies and Assessments, 56: 102990.

PHANI PRAVEEN, S, ALI, Mohammed Hasan, JARWAR, Muhammad Aslam, PRAKASH, Chander, REDDY, Chavva Ravi Kishore, MALLIGA, L and CHANDRU VIGNESH, C (2023). 6G assisted federated learning for continuous monitoring in wireless sensor network using game theory. Wireless Networks.

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GOKULAKRISHNAN, S., JARWAR, Muhammad Aslam, ALI, Mohammed Hasan, KAMRUZZAMAN, M.M., MEENAKSHISUNDARAM, Iyapparaja, JABER, Mustafa Musa and KUMAR, R. Lakshmana (2023). Maliciously roaming person's detection around hospital surface using intelligent cloud-edge based federated learning. Journal of Combinatorial Optimization, 45 (1): 13.

VIVEKANANDA, G.N., JARWAR, Muhammad Aslam, JABER, Mustafa Musa, PRAKASH, Chander, BUDDHI, Dharam, GNANASIGAMANI, Lydia J. and SANZ-PRIETO, Ivan (2022). Effective two-tier tokenization for intelligent transportation supply chain systems using hybrid optimized query expansion. Multimedia Tools and Applications.

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KHOWAJA, Sunder Ali, KHUWAJA, Parus, DEV, Kapal and JARWAR, Muhammad Aslam (2022). PROMPT: PROcess Mining and Paravector Tensor based Physical Health Monitoring Framework. IEEE Sensors Journal, p. 1.

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KHOWAJA, SA, LEE, IH, DEV, K, JARWAR, Muhammad Aslam and QURESHI, NMF (2022). Get Your Foes Fooled: Proximal Gradient Split Learning for Defense Against Model Inversion Attacks on IoMT Data. IEEE Transactions on Network Science and Engineering.

Pre-print

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D ANI, Uchenna, M WATSON, Watson, TUPTUK, Nilufer, HAILES, Steve and JARWAR, Muhammad Aslam (2023). Socio-technical security modelling: analysis of state-of-the-art, application, and maturity in critical industrial infrastructure environments/domains. [Pre-print] (Unpublished)

Book Section

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JARWAR, Muhammad Aslam, ALI, Sajjad, INAYATULLAH, and SHAH, Sayed Chhattan (2024). Taking IoT security to the next level: Hyperledger fabric private blockchain enabled IoT middleware. In: 2023 IEEE Globecom Workshops (GC Wkshps). IEEE.

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KUMAR, Sunil, JEONG, SeungMyeong, AHN, Il-Yeop and JARWAR, Muhammad Aslam (2022). Things Data Interoperability Through Annotating oneM2M resources for NGSI-LD Entities. In: 2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics). Los Alamitos, California., IEEE Computer Society Conference Publishing Services, 119-124.

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JARWAR, Muhammad Aslam, WATSON, Jeremy, ANI, Uchenna Daniel and CHALMERS, Stuarts (2022). Industrial Internet of Things security modelling using ontological methods. In: NIFORATOS, Evangelos, KORTUEM, Gerd, MERATNIA, Nirvana, SIEGEL, Josh and MICHAHELLES, Florian, (eds.) IoT 2022: proceedings of the 12th International Conference on the Internet of Things. Association for Computing Machinery, 163-170.

Monograph

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SMART, Paul, BONIFACE, Michael, JARWAR, Muhammad Aslam and WATSON, Jeremy (2023). SOfIoTS: Ontological Framework, Demonstration Outcomes, and Recommendations for Further Work (D3/D4). -.

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SMART, Paul, BONIFACE, Michael, JARWAR, Muhammad Aslam and WATSON, Jeremy (2023). Secure ontologies for the Internet of Things: representing risk and security concepts using basic formal ontology. Project Report. Unspecified.

Conference or Workshop Item

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JARWAR, Muhammad Aslam, ADRIANE, Chapman, MARK, Elliot and FATEMEH, Raji (2021). Modelling data environments within PROV to assist anonymisation decision-making. In: 2021 UNECE/Eurostat Expert Meeting on Statistical Data Confidentiality, PoznaƄ, Poland, 01-03 Dec 2021.

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