Digital Commons Network^™

Agriculture 4.0 And Beyond: Evaluating Cyber Threat Intelligence Sources And Techniques In Smart Farming Ecosystems, Hang T. Bui, Hamed Aboutorab, Arash Mahboubi, Yansong Gao, Nazatul H. Sultan, Aufeef Chauhan, Mohammad Z. Parvez, Michael Bewong, Rafiqul Islam, Zahid Islam, Seyit A. Camtepe, Praveen Gauravaram, Dineshkumar Singh, M. A. Babar, Shihao Yan

Research outputs 2022 to 2026

The digitisation of agriculture, integral to Agriculture 4.0, has brought significant benefits while simultaneously escalating cybersecurity risks. With the rapid adoption of smart farming technologies and infrastructure, the agricultural sector has become an attractive target for cyberattacks. This paper presents a systematic literature review that assesses the applicability of existing cyber threat intelligence (CTI) techniques within smart farming infrastructures (SFIs). We develop a comprehensive taxonomy of CTI techniques and sources, specifically tailored to the SFI context, addressing the unique cyber threat challenges in this domain. A crucial finding of our review is the identified need for a virtual Chief Information …

Examination Of Traditional Botnet Detection On Iot-Based Bots, Ashley Woodiss-Field, Michael N. Johnstone, Paul Haskell-Dowland

Research outputs 2022 to 2026

A botnet is a collection of Internet-connected computers that have been suborned and are controlled externally for malicious purposes. Concomitant with the growth of the Internet of Things (IoT), botnets have been expanding to use IoT devices as their attack vectors. IoT devices utilise specific protocols and network topologies distinct from conventional computers that may render detection techniques ineffective on compromised IoT devices. This paper describes experiments involving the acquisition of several traditional botnet detection techniques, BotMiner, BotProbe, and BotHunter, to evaluate their capabilities when applied to IoT-based botnets. Multiple simulation environments, using internally developed network traffic generation software, were …

Developing A Novel Ontology For Cybersecurity In Internet Of Medical Things-Enabled Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Syed A. A. Shah

Research outputs 2022 to 2026

IoT has seen remarkable growth, particularly in healthcare, leading to the rise of IoMT. IoMT integrates medical devices for real-time data analysis and transmission but faces challenges in data security and interoperability. This research identifies a significant gap in the existing literature regarding a comprehensive ontology for vulnerabilities in medical IoT devices. This paper proposes a fundamental domain ontology named MIoT (Medical Internet of Things) ontology, focusing on cybersecurity in IoMT (Internet of Medical Things), particularly in remote patient monitoring settings. This research will refer to similar-looking acronyms, IoMT and MIoT ontology. It is important to distinguish between the two. …

A Systematic Review Of K-12 Cybersecurity Education Around The World, Ahmed Ibrahim, Marnie Mckee, Leslie F. Sikos, Nicola F. Johnson

Research outputs 2022 to 2026

This paper presents a systematic review of K-12 cybersecurity education literature from around the world. 24 academic papers dated from 2013-2023 were eligible for inclusion in the literature established within the research protocol. An additional 19 gray literature sources comprised the total. A range of recurring common topics deemed as aspects of cybersecurity behavior or practice were identified. A variety of cybersecurity competencies and skills are needed for K-12 students to apply their knowledge. As may be expected to be the case with interdisciplinary fields, studies are inherently unclear in the use of their terminology, and this is compounded in …

Pdf Malware Detection: Toward Machine Learning Modeling With Explainability Analysis, G. M.Sakhawat Hossain, Kaushik Deb, Helge Janicke, Iqbal H. Sarker

Research outputs 2022 to 2026

The Portable Document Format (PDF) is one of the most widely used file types, thus fraudsters insert harmful code into victims' PDF documents to compromise their equipment. Conventional solutions and identification techniques are often insufficient and may only partially prevent PDF malware because of their versatile character and excessive dependence on a certain typical feature set. The primary goal of this work is to detect PDF malware efficiently in order to alleviate the current difficulties. To accomplish the goal, we first develop a comprehensive dataset of 15958 PDF samples taking into account the non-malevolent, malicious, and evasive behaviors of the …

Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman

Research outputs 2022 to 2026

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, …

Authenticated Public Key Elliptic Curve Based On Deep Convolutional Neural Network For Cybersecurity Image Encryption Application, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek M. Hassan

Research outputs 2022 to 2026

The demand for cybersecurity is growing to safeguard information flow and enhance data privacy. This essay suggests a novel authenticated public key elliptic curve based on a deep convolutional neural network (APK-EC-DCNN) for cybersecurity image encryption application. The public key elliptic curve discrete logarithmic problem (EC-DLP) is used for elliptic curve Diffie–Hellman key exchange (EC-DHKE) in order to generate a shared session key, which is used as the chaotic system’s beginning conditions and control parameters. In addition, the authenticity and confidentiality can be archived based on ECC to share the (Formula presented.) parameters between two parties by using the EC-DHKE …

Modulation Recognition Of Low-Snr Uav Radar Signals Based On Bispectral Slices And Ga-Bp Neural Network, Xuemin Liu, Yaoliang Song, Kuiyu Chen, Shihao Yan, Si Chen, Baihua Shi

Research outputs 2022 to 2026

In this paper, we address the challenge of low recognition rates in existing methods for radar signals from unmanned aerial vehicles (UAV) with low signal-to-noise ratios (SNRs). To overcome this challenge, we propose the utilization of the bispectral slice approach for accurate recognition of complex UAV radar signals. Our approach involves extracting the bispectral diagonal slice and the maximum bispectral amplitude horizontal slice from the bispectrum amplitude spectrum of the received UAV radar signal. These slices serve as the basis for subsequent identification by calculating characteristic parameters such as convexity, box dimension, and sparseness. To accomplish the recognition task, we …

On Irs-Assisted Covert Communication With A Friendly Uav, Xiaobei Xu, Linzi Hu, Sha Wei, Yuwen Qian, Shihao Yan, Feng Shu, Jun Li

Research outputs 2022 to 2026

Driven by the rapidly growing demand for information security, covert wireless communication has become an essential technology and attracted tremendous attention. However, traditional wireless covert communication is continuously exposing the inherent limitations, creating challenges around deployment in environments with a large number of obstacles, such as cities with high-rise buildings. In this paper, we propose an intelligent reflecting surface (IRS)-assisted covert communication system (CCS) for communicating with a friendly unmanned aerial vehicle (UAV) in which the UAV generates artificial noise (AN) to interfere with monitoring. Furthermore, we model the power of AN emitted by the UAV using an uncertainty model, …

A Novel Authentication Method That Combines Honeytokens And Google Authenticator, Vassilis Papaspirou, Maria Papathanasaki, Leandros Maglaras, Ioanna Kantzavelou, Christos Douligeris, Mohamed A. Ferrag, Helge Janicke

Research outputs 2022 to 2026

Despite the rapid development of technology, computer systems still rely heavily on passwords for security, which can be problematic. Although multi-factor authentication has been introduced, it is not completely effective against more advanced attacks. To address this, this study proposes a new two-factor authentication method that uses honeytokens. Honeytokens and Google Authenticator are combined to create a stronger authentication process. The proposed approach aims to provide additional layers of security and protection to computer systems, increasing their overall security beyond what is currently provided by single-password or standard two-factor authentication methods. The key difference is that the proposed system resembles …

Low-Complexity Three-Dimensional Aoa-Cross Geometric Center Localization Methods Via Multi-Uav Network, Baihua Shi, Yifan Li, Guilu Wu, Riqing Chen, Shihao Yan, Feng Shu

Research outputs 2022 to 2026

The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization of the distributed sensors. However, there are few works focusing on three-dimensional (3-D) scenarios. Furthermore, although the maximum likelihood estimator (MLE) has a relatively high performance, its computational complexity is ultra-high. Therefore, it is hard to employ it in practical applications. This paper proposed two center of inscribed sphere-based methods for 3-D AOA positioning via multiple UAVs. …

Knowledge Organization System For Partial Automation To Improve The Security Posture Of Iomt Networks, Kulsoom Saima Bughio

Research outputs 2022 to 2026

Remote patient monitoring is a healthcare delivery model that uses technology to collect and transmit patient data from a remote location to healthcare providers for analysis and treatment. Remote patient monitoring systems rely on a network infrastructure to gather and transmit data from patients to healthcare providers through a network. While these systems become more prevalent, they may also become targets for cyberattacks. This paper deals with the development of a domain ontology to facilitate partial automation to improve the security posture of IoT networks used in remote patient monitoring. For this purpose, it captures the semantics of the concepts …

A Review Of Cyber Vigilance Tasks For Network Defense, Oliver A. Guidetti, Craig Speelman, Peter Bouhlas

Research outputs 2022 to 2026

The capacity to sustain attention to virtual threat landscapes has led cyber security to emerge as a new and novel domain for vigilance research. However, unlike classic domains, such as driving and air traffic control and baggage security, very few vigilance tasks exist for the cyber security domain. Four essential challenges that must be overcome in the development of a modern, validated cyber vigilance task are extracted from this review of existent platforms that can be found in the literature. Firstly, it can be difficult for researchers to access confidential cyber security systems and personnel. Secondly, network defense is vastly …

Cyber-Aidd: A Novel Approach To Implementing Improved Cyber Security Resilience For Large Australian Healthcare Providers Using A Unified Modelling Language Ontology, Martin Dart, Mohiuddin Ahmed

Research outputs 2022 to 2026

Purpose: This paper proposes a novel cyber security risk governance framework and ontology for large Australian healthcare providers, using the structure and simplicity of the Unified Modelling Language (UML). This framework is intended to mitigate impacts from the risk areas of: (1) cyber-attacks, (2) incidents, (3) data breaches, and (4) data disclosures. Methods Using a mixed-methods approach comprised of empirical evidence discovery and phenomenological review, existing literature is sourced to confirm baseline ontological definitions. These are supplemented with Australian government reports, professional standards publications and legislation covering cyber security, data breach reporting and healthcare governance. Historical examples of healthcare cyber …

Hybrid Warfare And Disinformation: A Ukraine War Perspective, Sascha-Dominik Dov Bachmann, Dries Putter, Guy Duczynski

Research outputs 2022 to 2026

Misinformation, disinformation and mal information are part of the information disorder construct, dominating the information warfare domain. These are key enablers associated with grey zone operations, and an integral part of current adversaries' and competitors' hybrid warfare tool kit. Disinformation, in combination with influence operations, also plays an important role within the concept of hybrid warfare; both from a threat–and own resilience perspective. This article reflects on these information warfare tools and their application by Russia in the current Russo-Ukraine war, offering potentially considerable force multipliers in the information domain for the Russian aggressor. Hybrid warfare and associated threats, specifically …

Evaluating Staff Attitudes, Intentions, And Behaviors Related To Cyber Security In Large Australian Health Care Environments: Mixed Methods Study, Martin Dart, Mohiuddin Ahmed

Research outputs 2022 to 2026

Background: Previous studies have identified that the effective management of cyber security in large health care environments is likely to be significantly impacted by human and social factors, as well as by technical controls. However, there have been limited attempts to confirm this by using measured and integrated studies to identify specific user motivations and behaviors that can be managed to achieve improved outcomes.

Objective: This study aims to document and analyze survey and interview data from a diverse range of health care staff members, to determine the primary motivations and behaviors that influence their acceptance and application of cyber …

Malbot-Drl: Malware Botnet Detection Using Deep Reinforcement Learning In Iot Networks, Mohammad Al-Fawa'reh, Jumana Abu-Khalaf, Patryk Szewczyk, James J. Kang

Research outputs 2022 to 2026

In the dynamic landscape of cyber threats, multi-stage malware botnets have surfaced as significant threats of concern. These sophisticated threats can exploit Internet of Things (IoT) devices to undertake an array of cyberattacks, ranging from basic infections to complex operations such as phishing, cryptojacking, and distributed denial of service (DDoS) attacks. Existing machine learning solutions are often constrained by their limited generalizability across various datasets and their inability to adapt to the mutable patterns of malware attacks in real world environments, a challenge known as model drift. This limitation highlights the pressing need for adaptive Intrusion Detection Systems (IDS), capable …

A Review Of Multi-Factor Authentication In The Internet Of Healthcare Things, Tance Suleski, Mohiuddin Ahmed, Wencheng Yang, Eugene Wang

Research outputs 2022 to 2026

Objective: This review paper aims to evaluate existing solutions in healthcare authentication and provides an insight into the technologies incorporated in Internet of Healthcare Things (IoHT) and multi-factor authentication (MFA) applications for next-generation authentication practices. Our review has two objectives: (a) Review MFA based on the challenges, impact and solutions discussed in the literature; and (b) define the security requirements of the IoHT as an approach to adapting MFA solutions in a healthcare context. Methods: To review the existing literature, we indexed articles from the IEEE Xplore, ACM Digital Library, ScienceDirect, and SpringerLink databases. The search was refined to combinations …

Identity-Based Edge Computing Anonymous Authentication Protocol, Naixin Kang, Zhenhu Ning, Shiqiang Zhang, Sadaqat Ur Rehman, Muhammad Waqas

Research outputs 2022 to 2026

With the development of sensor technology and wireless communication technology, edge computing has a wider range of applications. The privacy protection of edge computing is of great significance. In the edge computing system, in order to ensure the credibility of the source of terminal data, mobile edge computing (MEC) needs to verify the signature of the terminal node on the data. During the signature process, the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance. Therefore, it is very necessary to improve efficiency through computational offloading. Therefore, this paper proposes an identity-based …

Camdec: Advancing Axis P1435-Le Video Camera Security Using Honeypot-Based Deception, Leslie F. Sikos, Craig Valli, Alexander E. Grojek, David J. Holmes, Samuel G. Wakeling, Warren Z. Cabral, Nickson M. Karie

Research outputs 2022 to 2026

The explosion of online video streaming in recent years resulted in advanced services both in terms of efficiency and convenience. However, Internet-connected video cameras are prone to exploitation, leading to information security issues and data privacy concerns. The proliferation of video-capable Internet of Things devices and cloud-managed surveillance systems further extend these security issues and concerns. In this paper, a novel approach is proposed for video camera deception via honeypots, offering increased security measures compared to what is available on conventional Internet-enabled video cameras.

Going Beyond: Cyber Security Curriculum In Western Australian Primary And Secondary Schools. Final Report, Nicola F. Johnson, Ahmed Ibrahim, Leslie Sikos, Marnie Mckee

Research outputs 2022 to 2026

There is no doubt cyber security is of national interest given the rife nature of cyber crime and the alarming increase of victims who have endured identify theft, fraud and scams. Curriculum within K-12 schools tends to be fixed and any modifications are subject to extensive consultation within a prolonged review cycle. Therefore, this report has gone beyond curriculum to explore the potential of national awareness campaigns and dynamic digital cyber security licences as alternative possibilities for instigation. The role of leaders in various school sectors and systems is critical for a successful roll out. This final report culminates from …

Physical Layer Authenticated Image Encryption For Iot Network Based On Biometric Chaotic Signature For Mpfrft Ofdm System, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek Hassan

Research outputs 2022 to 2026

In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the multi-parameter fractional Fourier transform–Orthogonal frequency division multiplexing (MP-FrFT-OFDM) is suggested for secure image transmission over the IoT network. In addition, a new robust multi-cascaded chaotic modular fractional sine map (MCC-MF sine map) is designed and analyzed. Also, a new dynamic chaotic biometric signature (DCBS) generator based on combining the biometric signature and the proposed MCC-MF sine map random chaotic sequence output is also designed. The final output of the proposed DCBS generator is used as a dynamic secret key for the MPFrFT OFDM system in which …

A Cross-Domain Trust Model Of Smart City Iot Based On Self-Certification, Yao Wang, Yubo Wang, Zhenhu Ning, Sadaqat Ur Rehman, Muhammad Waqas

Research outputs 2022 to 2026

Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced …

Intrusion Detection Based On Bidirectional Long Short-Term Memory With Attention Mechanism, Yongjie Yang, Shanshan Tu, Raja Hashim Ali, Hisham Alasmary, Muhammad Waqas, Muhammad Nouman Amjad

Research outputs 2022 to 2026

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. …

The Wacdt, A Modern Vigilance Task For Network Defense, Oliver A. Guidetti, Craig Speelman, Peter Bouhlas

Research outputs 2022 to 2026

Vigilance decrement refers to a psychophysiological decline in the capacity to sustain attention to monotonous tasks after prolonged periods. A plethora of experimental tasks exist for researchers to study vigilance decrement in classic domains such as driving and air traffic control and baggage security; however, the only cyber vigilance tasks reported in the research literature exist in the possession of the United States Air Force (USAF). Moreover, existent cyber vigilance tasks have not kept up with advances in real-world cyber security and consequently no longer accurately reflect the cognitive load associated with modern network defense. The Western Australian Cyber Defense …

Determinants Of Intention To Use E-Wallet: Personal Innovativeness And Propensity To Trust As Moderators, Madugoda Gunaratnege Senali, Mohammad Iranmanesh, Fatin Nadzirah Ismail, Noor Fareen Abdul Rahim, Mana Khoshkam, Maryam Mirzaei

Research outputs 2022 to 2026

This study aims to investigate the determinants of intention to use e-wallets. Drawing on the technology acceptance model (TAM), the conceptual framework was developed. The study extends the TAM in the context of e-wallets, by testing the influences of product-related factors namely perceived compatibility, perceived risk, and perceived emotions and investigating the moderating impacts of personal innovativeness and propensity to trust. To conduct an empirical study, the data were collected from Malaysian individuals with no experience with e-wallets using an online survey. Data from 374 participants were obtained and analyzed using the partial least squares technique. The results showed that …

Combining Security And Reliability Of Critical Infrastructures: The Concept Of Securability, Leandros Maglaras, Helge Janicke, Mohamed Amine Ferrag

Research outputs 2022 to 2026

The digital revolution has made people more dependent on ICT technology to perform everyday tasks, whether at home or at work. The systems that support critical aspects of this smart way of living are characterized as critical, and the security level of such systems is higher as compared to others. The definition of the criticality of a system is a rather difficult exercise, and for that reason, we have seen novel cybersecurity regulations to introduce the idea of digital managed services, which include security monitoring, managed network services, or the outsourcing of business processes that are are critical to the …

Anomaly Detection In Cybersecurity Datasets Via Cooperative Co-Evolution-Based Feature Selection, Bazlur A. N. M. Rashid, Mohiuddin Ahmed, Leslie F. Sikos, Paul Haskell-Dowland

Research outputs 2022 to 2026

Anomaly detection from Big Cybersecurity Datasets is very important; however, this is a very challenging and computationally expensive task. Feature selection (FS) is an approach to remove irrelevant and redundant features and select a subset of features, which can improve the machine learning algorithms’ performance. In fact, FS is an effective preprocessing step of anomaly detection techniques. This article’s main objective is to improve and quantify the accuracy and scalability of both supervised and unsupervised anomaly detection techniques. In this effort, a novel anomaly detection approach using FS, called Anomaly Detection Using Feature Selection (ADUFS), has been introduced. Experimental analysis …

Ransomware 2.0: An Emerging Threat To National Security, Mohiuddin Ahmed, Sascha Dominik Dov Bachmann, Abu Barkat Ullah, Shaun Barnett

Research outputs 2022 to 2026

The global Covid-19 pandemic has seen the rapid evolution of our traditional working environment; more people are working from home and the number of online meetings has increased. This trend has also affected the security sector. Consequently, the evolution of ransomware to what is now being described as ‘Ransomware 2.0’ has governments, businesses and individuals alike rushing to secure their data.

Cybersecurity Of Critical Infrastructures: Challenges And Solutions, Leandros Maglaras, Helge Janicke, Mohamed Amine Ferrag

Research outputs 2022 to 2026

People’s lives are becoming more and more dependent on information and computer technology. This is accomplished by the enormous benefits that the ICT offers for everyday life. Digital technology creates an avenue for communication and networking, which is characterized by the exchange of data, some of which are considered sensitive or private. There have been many reports recently of data being hijacked or leaked, often for malicious purposes. Maintaining security and privacy of information and systems has become a herculean task. It is therefore imperative to understand how an individual’s or organization’s personal data can be protected. Moreover, critical infrastructures …