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All Outputs (6)

TrustMod: a trust management module for NS-3 simulator. (2021)
Conference Proceeding
HAJAR, M.S., KALUTARAGE, H. and AL-KADRI, M.O. 2021. TrustMod: a trust management module for NS-3 simulator. In Zhao, L., Kumar, N., Hsu, R.C. and Zou, D. (eds.) Proceedings of 20th IEEE (Institute of Electrical and Electronics Engineers) International conference on Trust, security and privacy in computing and communications 2021 (IEEE TrustCom 2021), 20-21 October 2021, Shenyang, China: [virtual event]. Piscataway: IEEE [online], pages 51-60. Available from: https://doi.org/10.1109/TrustCom53373.2021.00025

Trust management offers a further level of defense against internal attacks in ad hoc networks. Deploying an effective trust management scheme can reinforce the overall network security. Regardless of limitations, however, security researchers often... Read More about TrustMod: a trust management module for NS-3 simulator..

LTMS: a lightweight trust management system for wireless medical sensor networks. (2021)
Conference Proceeding
HAJAR, M.S., AL-KADRI, M.O. and KALUTARAGE, H. 2020. LTMS: a lightweight trust management system for wireless medical sensor networks. In Wang, G., Ko, R., Bhuiyan, M.Z.A. and Pan, Y. (eds.). Proceedings of 19th Institute of Electrical and Electronics Engineers (IEEE) Trust, security and privacy in computing and communication international conference 2020 (TrustCom 2020), 29 Dec 2020 - 1 Jan 2021, Guangzhou, China. Piscataway: IEEE [online], pages 1783-1790. Available from: https://doi.org/10.1109/TrustCom50675.2020.00245

Wireless Medical Sensor Networks (WMSNs) offer ubiquitous health applications that enhance patients' quality of life and support national health systems. Detecting internal attacks on WMSNs is still challenging since cryptographic measures can not pr... Read More about LTMS: a lightweight trust management system for wireless medical sensor networks..

Resource efficient boosting method for IoT security monitoring. (2021)
Conference Proceeding
ZAKARIYYA, I., AL-KADRI, M.O. and KALUTARAGE, H. 2021. Resource efficient boosting method for IoT security monitoring. In Proceedings of 18th Institute of Electrical and Electronics Engineers (IEEE) Consumer communications and networking conference 2021 (CCNC 2021), 9-12 January 2021, [virtual conference]. Piscataway: IEEE [online], article 9369620. Available from: https://doi.org/10.1109/ccnc49032.2021.9369620

Machine learning (ML) methods are widely proposed for security monitoring of Internet of Things (IoT). However, these methods can be computationally expensive for resource constraint IoT devices. This paper proposes an optimized resource efficient ML... Read More about Resource efficient boosting method for IoT security monitoring..

ETAREE: an effective trend-aware reputation evaluation engine for wireless medical sensor networks. (2020)
Conference Proceeding
HAJAR, M.S., AL-KADRI, M.O. and KALUTARAGE, H. 2020. ETAREE: an effective trend-aware reputation evaluation engine for wireless medical sensor networks. In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) Communications and network security conference (CNS 2020), 29 June - 1 July 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9162325. Available from: https://doi.org/10.1109/CNS48642.2020.9162325

Wireless Medical Sensor Networks (WMSN) will play a significant role in the advancements of modern healthcare applications. Security concerns are still the main obstacle to the widespread adoption of this technology. Conventional security approaches,... Read More about ETAREE: an effective trend-aware reputation evaluation engine for wireless medical sensor networks..

Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm. (2019)
Conference Proceeding
ZAKARIYYA, I., AL-KADRI, M.O., KALUTARGE, H. and PETROVSKI, A. 2019. Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm. In Obaidat, M. and Samarati, P. (eds.) Proceedings of the 16th International security and cryptography conference (SECRYPT 2019), co-located with the 16th International joint conference on e-business and telecommunications (ICETE 2019), 26-28 July 2019, Prague, Czech Republic. Setúbal, Portugal: SciTePress [online], 2, pages 523-528. Available from: https://doi.org/10.5220/0008119205230528.

Using Machine Learning (ML) for Internet of Things (IoT) security monitoring is a challenge. This is due to their resource constraint nature that limits the deployment of resource-hungry monitoring algorithms. Therefore, the aim of this paper is to i... Read More about Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm..

Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus. (2019)
Conference Proceeding
KALUTARAGE, H.K., AL-KADRI, M.O., CHEAH, M. and MADZUDZO, G. 2019. Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus. In Hof, H.-J., Fritz, M., Kraub, C. and Wasenmüller, O. (eds.). Proceedings of 2019 Computer science in cars symposium (CSCS 2019), 8 October 2019, Kaiserslautern, Germany. New York: ACM [online], article number 7. Available from: https://doi.org/10.1145/3359999.3360496

Automotive electronics is rapidly expanding. An average vehicle contains million lines of software codes, running on 100 of electronic control units (ECUs), in supporting number of safety, driver assistance and infotainment functions. These ECUs are... Read More about Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus..