Faculty of Computing

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Subject: search.filters.subject.Security Solution

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    ARGUS - An Adaptive Smart Home Security Solution
    (IEEE, 2022-12-09) Ratnayake, R.M. Ruwin R.; Abeysiriwardhena, G.D.N.D.K.; Perera, G.A.J.; Senarathne, A; Ponnamperuma, R.; Ganegoda, B.A.
    Smart Security Solutions are in high demand with the ever-increasing vulnerabilities within the IT domain. Adjusting to a Work-From-Home (WFH) culture has become mandatory by maintaining required core security principles. Therefore, implementing and maintaining a secure Smart Home System has become even more challenging. ARGUS provides an overall network security coverage for both incoming and outgoing traffic, a firewall and an adaptive bandwidth management system and a sophisticated CCTV surveillance capability. ARGUS is such a system that is implemented into an existing router incorporating cloud and Machine Learning (ML) technology to ensure seamless connectivity across multiple devices, including IoT devices at a low migration cost for the customer. The aggregation of the above features makes ARGUS an ideal solution for existing Smart Home System service providers and users where hardware and infrastructure is also allocated. ARGUS was tested on a small-scale smart home environment with a Raspberry Pi 4 Model B controller. Its intrusion detection system identified an intrusion with 96% accuracy while the physical surveillance system predicts the user with 81% accuracy.
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    SentinelPlus: A Cost-Effective Cyber Security Solution for Healthcare Organizations
    (IEEE, 2021-12-09) Janith, K; Iddagoda, R; Gunawardena, C; Sankalpa, K; Abeywardena, K. Y; Yapa, K
    Electronic Protected Health Information (ePHI) has proven to be quite lucrative by cybercriminals due to their long shelf life and multiple possible avenues of monetization. These highly sensitive data has become an easy target for cyber attackers due to the poor cyber resiliency strategies exercised by Healthcare Organizations. The reasoning behind the poor cyber security management in the healthcare sector sums to the collective impact of budgetary restriction, lack of cyber security competency and talent in the domain, prioritizing convenience over security, and various work culture malpractices. Further-more, a substantial number of data breaches in the healthcare sector are known to be caused by human errors, security misconfigurations, and information mismanagement. Secondly, the increasing prevalence of ransomware and botnet attacks has hampered the efficiency and availability of healthcare services. As a result, in order to provide a holistic security mechanism, this paper presents "SentinelPlus," a machine learning-based security management suite.