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Articles 1 - 4 of 4
Full-Text Articles in Cybersecurity
Ecu-Malnett V2, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone
Ecu-Malnett V2, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone
Research Datasets
ECU-MALNETT (ECU MALware NETwork Traffic) is a real world, reproducible dataset of labeled benign and malicious network flows built from the Peekaboo execution corpus. Peekaboo runs evasive malware with dynamic binary instrumentation and records raw host-level PCAPs while granting full Internet access, yielding noisy, real-world captures with background OS activity and concurrent processes. To derive trustworthy labels from these traces, we apply Construct, a baseline aware, zero-trust labeling framework. Construct first ingests a baseline capture to establish reference sets (DNS qnames, HTTP hosts, TLS SNIs, and socket endpoints) and grows a conservative benign IP pool only via whitelisted DNS resolutions. …
A Knowledge-Driven, Ai-Assisted Cyber Defence Framework For Iomt Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Abdul M. Unar
A Knowledge-Driven, Ai-Assisted Cyber Defence Framework For Iomt Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Abdul M. Unar
Research outputs 2022 to 2026
The rapid adoption of Internet Medical Things (IoMT) technologies in remote patient monitoring has reshaped healthcare delivery by enabling continuous, real-time clinical observation outside traditional care settings. However, this shift has also expanded the cyber-attack surface across heterogeneous, resource-constrained medical devices, wireless networks, cloud services, and third-party platforms. In cyber warfare, healthcare has become an incorporated target of geopolitics, with hospitals, remote monitoring systems, and emergency health systems being used to broaden the attack surface for adversaries to exploit. Existing security approaches for IoMT environments remain largely manual, fragmented, and reactive, limiting their effectiveness in dynamically assessing vulnerabilities and supporting …
Ecu-Malnett, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone
Ecu-Malnett, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone
Research Datasets
ECU-MALNETT (ECU MALware NETwork Traffic) is a real world, reproducible dataset of labeled benign and malicious network flows built from the Peekaboo execution corpus. Peekaboo runs evasive malware with dynamic binary instrumentation and records raw host-level PCAPs while granting full Internet access, yielding noisy, real-world captures with background OS activity and concurrent processes. To derive trustworthy labels from these traces, we apply Construct, a baseline aware, zero-trust labeling framework. Construct first ingests a baseline capture to establish reference sets (DNS qnames, HTTP hosts, TLS SNIs, and socket endpoints) and grows a conservative benign IP pool only via whitelisted DNS resolutions. …
Contexts For Children’S Digital Citizenship In India, Korea And Australia: A Literature Review, Kylie Stevenson, Emma Jayakumar, Viet Tho Le, Yeonghwi Ryu, Harrison See
Contexts For Children’S Digital Citizenship In India, Korea And Australia: A Literature Review, Kylie Stevenson, Emma Jayakumar, Viet Tho Le, Yeonghwi Ryu, Harrison See
Research outputs 2022 to 2026
Children’s digital citizenship today: In an increasingly digitised and technically mediated world, an individual’s digital citizenship, or “ability to use digital technology and media in safe, responsible and ethical ways” (DQ Institute, 2019) has never been more relevant, particularly when it concerns our youngest digital citizens. Navigating online spaces safely and confidently are skills fundamental to a modern individual’s social and emotional development, education, work and play. A digital citizen’s abilities, however, are greatly impacted by notions of access; not just physical access, but also access mediated culturally and socio-economically. Less is known about very young children’s experiences of digital …