Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Publication
- Publication Type
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Development And Validation Of A Proof-Of-Concept Prototype For Analytics-Based Malicious Cybersecurity Insider Threat In A Real-Time Identification System, Angel L. Hueca
CCE Theses and Dissertations
Insider threat has continued to be one of the most difficult cybersecurity threat vectors detectable by contemporary technologies. Most organizations apply standard technology-based practices to detect unusual network activity. While there have been significant advances in intrusion detection systems (IDS) as well as security incident and event management solutions (SIEM), these technologies fail to take into consideration the human aspects of personality and emotion in computer use and network activity, since insider threats are human-initiated. External influencers impact how an end-user interacts with both colleagues and organizational resources. Taking into consideration external influencers, such as personality, changes in organizational polices …
Ransomware Behavioural Analysis On Windows Platforms, Nikolai Hampton, Zubair A. Baig, Sherali Zeadally
Ransomware Behavioural Analysis On Windows Platforms, Nikolai Hampton, Zubair A. Baig, Sherali Zeadally
Research outputs 2014 to 2021
Ransomware infections have grown exponentially during the recent past to cause major disruption in operations across a range of industries including the government. Through this research, we present an analysis of 14 strains of ransomware that infect Windows platforms, and we do a comparison of Windows Application Programming Interface (API) calls made through ransomware processes with baselines of normal operating system behaviour. The study identifies and reports salient features of ransomware as referred through the frequencies of API calls
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Australian Information Security Management Conference
Traditional firewalls are losing their effectiveness against new and evolving threats today. Artificial intelligence (AI) driven firewalls are gaining popularity due to their ability to defend against threats that are not fully known. However, a firewall can only protect devices in the same network it is deployed in, leaving mobile devices unprotected once they leave the network. To comprehensively protect a mobile device, capabilities of an AI-driven firewall can enhance the defensive capabilities of the device. This paper proposes porting AI technologies to mobile devices for defence against today’s ever-evolving threats. A defensive AI technique providing firewall-like capability is being …
Extraction Of Patterns In Selected Network Traffic For A Precise And Efficient Intrusion Detection Approach, Priya Naran Rabadia
Extraction Of Patterns In Selected Network Traffic For A Precise And Efficient Intrusion Detection Approach, Priya Naran Rabadia
Theses: Doctorates and Masters
This thesis investigates a precise and efficient pattern-based intrusion detection approach by extracting patterns from sequential adversarial commands. As organisations are further placing assets within the cyber domain, mitigating the potential exposure of these assets is becoming increasingly imperative. Machine learning is the application of learning algorithms to extract knowledge from data to determine patterns between data points and make predictions. Machine learning algorithms have been used to extract patterns from sequences of commands to precisely and efficiently detect adversaries using the Secure Shell (SSH) protocol. Seeing as SSH is one of the most predominant methods of accessing systems it …
A Novel Cooperative Intrusion Detection System For Mobile Ad Hoc Networks, Adam Solomon
A Novel Cooperative Intrusion Detection System For Mobile Ad Hoc Networks, Adam Solomon
CCE Theses and Dissertations
Mobile ad hoc networks (MANETs) have experienced rapid growth in their use for various military, medical, and commercial scenarios. This is due to their dynamic nature that enables the deployment of such networks, in any target environment, without the need for a pre-existing infrastructure. On the other hand, the unique characteristics of MANETs, such as the lack of central networking points, limited wireless range, and constrained resources, have made the quest for securing such networks a challenging task. A large number of studies have focused on intrusion detection systems (IDSs) as a solid line of defense against various attacks targeting …