Reactive defense mechanisms, such as intrusion detection systems, have made significant efforts to secure a system or network for the last several decades. However, nature of reactive security mechanisms has limitations because potential attackers cannot be prevented in advance. We are facing reality with proliferation persistent, advanced, intelligent attacks while defenders often way behind taking appropriate actions thwart attackers. The concept moving target (MTD) emerged proactive...

The rise of the new generation cyber threats demands more sophisticated and intelligent defense solutions equipped with autonomous agents capable learning to make decisions without knowledge human experts. Several reinforcement methods (e.g., Markov) for automated network intrusion tasks have been proposed in recent years. In this paper, we introduce a detection method, which combines Q-learning based deep feed forward neural method detection. Our Deep Q-Learning (DQL) model provides an...

This study investigated the potential of Generative Pre-trained Transformers (GPTs), a state-of-the-art large language model, in generating cybersecurity policies to deter and mitigate ransomware attacks that perform data exfiltration. We compared effectiveness, efficiency, completeness, ethical compliance GPT-generated Governance, Risk Compliance (GRC) policies, with those from established security vendors government agencies, using game theory, cost-benefit analysis, coverage ratio,...

Moving Target Defence (MTD) has been recently proposed and is an emerging proactive approach which provides asynchronous defensive strategies. Unlike traditional security solutions that focused on removing vulnerabilities, MTD makes a system dynamic unpredictable by continuously changing attack surface to confuse attackers. can be utilized in cloud computing address the cloud's security-related problems. There are many literature proposing methods various contexts, but it still lacks...

Moving Target Defense (MTD) is a proactive security solution, which can be utilized by cloud computing in order to thwart cyber attacks. Many MTD techniques have been proposed, but there still lack of systematic evaluation methods for assessing the effectiveness proposed techniques, especially when multiple are used combinations. In this paper, we aim address aforementioned issue proposing an approach modeling and analysis techniques. We consider four metrics: system risk, attack cost,...

Data anonymization strategies such as subtree generalization have been hailed techniques that provide a more efficient strategy compared to full-tree counterparts. Many subtree-based generalizations (e.g., top-down, bottom-up, and hybrid) implemented on the MapReduce platform take advantage of scalability parallelism. However, inherent lack support for iteration intensive algorithm implementation generalization. This paper proposes Distributed Dataset (RDD)-based data technique Apache Spark...

Moving Target Defense (MTD) is a proactive security mechanism that changes the attack surface with aim of confusing attackers. Cloud computing leverages MTD techniques to enhance cloud posture against cyber threats. While many have been applied computing, there has so far no joint evaluation effectiveness respect and economic metrics. In this paper, we first introduce mathematical definitions for combination three techniques: Shuffle, Diversity, Redundancy. Then, utilize four metrics –...

Evaluating the air quality of classrooms is important as children spend a large amount time at school. Massey University (NZ) led development low-cost and affordable Indoor Air Quality (IAQ) platform called SKOMOBO that was deployed on scale across primary schools in New Zealand. When data from SKOMBO units were collected, it to detect any unexpected high pollution events. To address this concern, we propose study outlier detection for PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML"...

Multi-dimensional data anonymization approaches (e.g., Mondrian) ensure more fine-grained privacy by providing a different strategy applied for each attribute. Many variations of multi-dimensional have been implemented on distributed processing platforms MapReduce, Spark) to take advantage their scalability and parallelism supports. According our critical analysis overheads, either existing iteration-based or recursion-based do not provide effective mechanisms creating the optimal number...

The cloud model allows many enterprises able to outsource computing resources at an affordable price without having commit the expense upfront. Although providers are responsible for security of cloud, there still concerns due inherently complex operate on (e.g.,multi-tenancy). In addition, whose services have migrated into a preference their own cybersecurity situation awareness capability top mechanisms provided by providers. this way, can monitor performance offerings and choice decide...

Wireless networks need more security in comparison to the other due their intrinsic vulnerabilities possible attacks. It is expected that by using a distributed method for true random number generators (TRNG) wireless sensor (WSN) and LAN (WLAN) randomness quality of generated numbers can be enhanced. We analyze protocol TRNG named ScatterLight (L. R. Giuseppe, M. Fabrizio O. Marco, 2011) WSN. After making some changes on structure physical data sources, Enhanced introduced; it provides...

Cyberspace is full of uncertainty in terms advanced and sophisticated cyber threats which are equipped with novel approaches to learn the system propagate themselves, such as AI-powered threats. To debilitate these types threats, a modern intelligent Cyber Situation Awareness (SA) need be developed has ability monitoring capturing various analyzing devising plan avoid further attacks. This paper provides comprehensive study on current state-of-the-art SA discuss following aspects SA: key...

With the Internet of Things (IoT) generating vast amounts data, privacy breaches have become increasingly prevalent, exposing individuals to serious risks such as identity theft and life-threatening situations. This research addresses challenge identifying cybersecurity threats vulnerabilities leading breaches, evidenced by recent cyber-attacks on Australian Medibank, Optus, hospital networks. We propose a machine learning (ML)-based approach distinguish between legitimate rogue policies,...