Cybersecurity Strategy Research Articles

Complexity of Contemporary Indicators of Compromise

The cybersecurity landscape has undergone substantial transformation, especially in the sphere of Advanced Persistent Threats (APT). These evolving threats, marked by increased sophistication, scale, and impact, require the critical revaluation of traditional security models and the development of more advanced defensive strategies. This study offers a comprehensive analysis of the progress in APT attack methodologies over the past 30 years, focused on the evolving nature of compromise (IoCs) and their role in shaping future predictive and defensive mechanisms. Using a rigorous methodological approach, this survey systematically reviewed 21 significant APT incidents that span three decades. This includes integrating data from various sources such as academic journals, specialised cybersecurity blogs, and media reports. Using comparative and analytical methods, this study dissects each incident to provide an intricate understanding of the APT landscape and the evolution of IoCs. Our findings indicate a notable change in thinking from isolated hacker activities to organised state-sponsored APT operations driven by complex motives such as political espionage, economic disruption, and national security interests. Advancements in APTs are characterised by sophisticated persistence mechanisms, innovative attack vectors, advanced lateral movement within networks, and more covert data exfiltration and evasion methods.This study emphasises the difficulties in detecting advanced persistent threat (APT) activities due to their sophisticated and secretive nature. This stresses the importance of thoroughly investigating the evidence of such activities and highlights the need for a dynamic and initiative-cybersecurity approach. This study also highlights the crucial role of integrating IoC understanding into AI-driven predictive models and frameworks to predict potential APT. This integration is essential for the development of pre-emptive defence strategies. This study provides valuable information on the evolving dynamics of cyber threats and emphasises the urgent need for forward-thinking adaptive cybersecurity strategies. It offers a framework for understanding the complexities of modern APTs and guides the development of more effective AI-enhanced defence mechanisms against emerging cyber threats.

The U.S. National Cybersecurity Strategy: A Vehicle with an International Journey

The U.S. National Cybersecurity Strategy is focused on the five pillars of defending critical infrastructure: detect, disrupt, and dismantle threat actors; improve market resilience and security; invest in future resilience; and create international partnerships with shared goals. The National Cybersecurity Strategy Implementation Plan is focused on critical infrastructure supporting energy, financial, healthcare, information technology, and manufacturing sectors. In the U.S. alone, the SolarWinds supply chain attack affected nine federal agencies and about 100 companies. Ransomware attacks such as the Colonial Pipelines, the largest U.S. oil pipeline, disrupted supplies of gasoline and fuel to the U.S. East Coast and the JBS USA as the largest meat processor ransomware attack affecting one-fifth of the nation’s meat supply. The U.S. National Cybersecurity Strategy as a response to the U.S.’s critical infrastructure concerns led to the creation of two core cybersecurity documents which were crafted jointly with several other allies. Cybersecurity and Infrastructure Security Agency (CISA) crafted the Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software with joint agreement with National Security Agency (NSA), the Federal Bureau of Investigation (FBI), and 15 international government agencies to give international vendors a roadmap of the expected cybersecurity hygiene required from their products. (CISA, 2023a; Car & De Luca, 2022) Building on the Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software, CISA, FBI and NSA met with cybersecurity organizations from Australia, Canada, New Zealand, and United Kingdom and jointly created The Case for Memory Safe Roadmaps: Why Both C-Suite Executives and Technical Experts Need to Take Memory Safe Coding Seriously as a core issue identified in the earlier guidance. (CISA, 2023c). These led by the U.S. helped initiate an international cybersecurity norm insisting international software manufacturers demonstrate product security and transparency. They showed how a global community can rally to solve cybersecurity challenges that have existed for decades. This led to twenty of the largest international software vendors creating the Minimum Viable Secure Product (MSVP) Working Group to address the requirements levied by these documents; CISA has joined this working group to help shape procurement, contractual controls, self-assessment, and system development lifecycle (SDLC) with these vendors. (CISA, 2024d; MSVP, n.d.) This research argues that the U.S. National Security Council (NSC) should leverage the talent pool of CISA, National Institute of Standards and Technology (NIST), Department of Defense (DoD), FBI, and NSA to improve detection, information sharing, security standards, and implementation for not only the U.S.’s government and commercial sectors, but also helps our allies and partners. The DoD and Office of the Director of National Intelligence (ODNI) have made great strides in improving security by integrating improvements with Zero Trust Architecture (ZTA), Supply Chain Risk Management (SCRM), Software Supply Chain Security, Cybersecurity Safety Review Board (CSRB), Cybersecurity Incident & Vulnerability Response Playbooks, and DoD National Security Systems (NSS) standards. The NSC should coordinate through CISA to develop a collaborative effort to not only benefit the U.S. critical infrastructure but also help our allies and partners.

Design and Development Considerations of a Cyber Physical Testbed for Operational Technology Research and Education.

Cyber-physical systems (CPS) are vital in automating complex tasks across various sectors, yet they face significant vulnerabilities due to the rising threats of cybersecurity attacks. The recent surge in cyber-attacks on critical infrastructure (CI) and industrial control systems (ICSs), with a 150% increase in 2022 affecting over 150 industrial operations, underscores the urgent need for advanced cybersecurity strategies and education. To meet this requirement, we develop a specialised cyber-physical testbed (CPT) tailored for transportation CI, featuring a simplified yet effective automated level-crossing system. This hybrid CPT serves as a cost-effective, high-fidelity, and safe platform to facilitate cybersecurity education and research. High-fidelity networking and low-cost development are achieved by emulating the essential ICS components using single-board computers (SBC) and open-source solutions. The physical implementation of an automated level-crossing visualised the tangible consequences on real-world systems while emphasising their potential impact. The meticulous selection of sensors enhances the CPT, allowing for the demonstration of analogue transduction attacks on this physical implementation. Incorporating wireless access points into the CPT facilitates multi-user engagement and an infrared remote control streamlines the reinitialization effort and time after an attack. The SBCs overwhelm as traffic surges to 12 Mbps, demonstrating the consequences of denial-of-service attacks. Overall, the design offers a cost-effective, open-source, and modular solution that is simple to maintain, provides ample challenges for users, and supports future expansion.

Mapping the Digital Frontier: Bibliometric and Machine Learning Insights Into Public Administration Transformation

Digital transformation significantly influences public administration by integrating advanced technologies such as artificial intelligence, blockchain, and big data analytics across various governmental functions. In this study, the use of LDA alongside advanced bibliometric techniques such as citation analysis and co-citation networks to explore the evolution and current status of digital transformation in public administration provides a structured examination of large data sets obtained from the Web of Science, providing a thematic and intellectual insight into the field. Analyzing 628 articles, our research highlights how traditionally engineering-associated technologies are increasingly applied within the social sciences, transforming public management processes and policies. Our findings reveal that digital transformation in public administration is predominantly driven by external pressures rather than internal organizational initiatives. The importance of this study lies in its ability to map and visualize the transformative impact of digital technologies on governance structures, policy-making processes, and public engagement. Revealing that the databased, more transparent and participatory nature of public administration has increased, the study not only maps the thematic evolution of public administration but also discusses the consequences of these transformations for policy makers and public administrators. Integrating digital tools has enhanced service delivery and operational efficiency but also presents challenges, such as the need for comprehensive cybersecurity strategies and continuous adaptation to technological advancements.

Cybersecurity strategy: future proof cybersecurity for small to medium enterprises in South Africa

Technological development has witnessed tremendous and an increase in business interactions as they execute their daily business. Information technology and broadband are significant drivers of productivity and efficiency growth for small firms as they expand their market. This development has raised growing concerns as it relates to data and information security, infrastructure, and related resources due to an increase in cybersecurity hazards faced by Small to Medium Enterprises globally. In South Africa, although, during the first four months of 2022, cyber-attacks decreased by 13% to account for 419506 internet attacks, this statistic remains high enough for concern. To counter escalating cybersecurity risks, organizations must have a cybersecurity strategy to safeguard their operations, clients, data, and infrastructure. The threat landscape is changing over time, and despite ongoing attempts to strengthen security, they don't appear to be enough to prevent evolving cyberattacks. The study aims to identify cybersecurity threats facing Small to Medium Enterprises in South Africa by reviewing the literature and identifying key Cybersecurity challenges. It also examines the strategies, resources, and techniques used in South Africa to reduce cybersecurity threats. Lastly, the paper recommends adopting a comprehensive Cybersecurity strategy to build future-proof cybersecurity for Small to Medium Enterprises in South Africa.

Simplifying security processes in large organizations while maintaining an appropriate level of security

This paper presents an approach to simplifying security in large organizations, ensuring that the work of ordinary employees is more accessible without negatively impacting the organization's security. Access to the Internet is becoming increasingly important in various aspects of human life, including interpersonal communication, professional work, and business operations. Enterprises have digitized information on their devices, which can be of interest to attackers. Incorrect security measures can expose companies to various losses, such as financial costs or image losses. As the number of enterprises connected to the Internet grows, IT system security is gaining importance. Cyberattacks are malicious actions by individuals or organized groups with motives such as financial gain, employee dissatisfaction, or government interference. Attackers aim to access financial data, customer lists, financial data, and customer databases. Cybersecurity should be the basis of every organization, regardless of its size. The number of attacks each year is related to increased investments in cybersecurity strategies and focusing on finding and stopping hackers. Information security protects information to prevent unauthorized access, use, and disclosure. It includes implementing policies and procedures to protect information and prevent data loss or theft. However, implementing security measures can be challenging for ordinary employees, leading to decreased security.

Navigating Cyber Perils in Bhutan: Challenges and Opportunities

Over a decade, Bhutan witnessed massive digital transformation in various sectors offering numerous opportunities, but at the same time, this has also brought in a considerable share of cybersecurity threats and challenges. By reviewing and analysing information related to cybersecurity from various sources, such as journals, news articles, press releases, websites, and annual reports of government agencies related to Bhutan’s cybersecurity, this study identified the prominent vulnerabilities, challenges, and opportunities, and explored the mitigation strategies. It was determined that the cybersecurity threat landscape of Bhutan is dynamic and multifaceted, ranging from online scams, phishing attacks, malware infections, vulnerabilities in systems, and a lack of security awareness among the general population. Bhutan has made noticeable efforts towards cyber threat mitigation which includes improving cybersecurity awareness at various levels, collaborating with stakeholders both at national and international levels, and implementing guiding strategies. However, there are still significant challenges being faced in terms of limited allocations of budget for infrastructure and human resource development and management. In addition, penetrating security awareness at the grassroots level is a prominent challenge. There are also opportunities to work towards maintaining and retaining a technical talent pool and implementing the national cybersecurity strategy. This article provides insights into Bhutan’s cybersecurity landscape and offers recommendations for addressing current challenges and building capabilities to combat cyber threats effectively.

Exploring GRU-based approaches with attention mechanisms for accurate phishing URL detection

In the dynamic realm of digital advancements, the persistent menace of phishing attacks continues to jeopardize the security landscape for both individuals and organizations. As cyber attacks continue to proliferate, URL-based phishing attacks are growing rapidly. This paper presents an exploratory study aimed at enhancing cybersecurity measures through the detection of phishing URLs. Our approach involves exploring the integration of Gated Recurrent Units (GRU) with various attention mechanisms to bolster accuracy in discerning between legitimate and phishing URLs. Notably, our study reveals that the implementation of the Bahdanau attention mechanism with GRU yields remarkable results, achieving an accuracy of 98.14%. We conducted experiments on a comprehensive dataset comprising 95,913 URLs. Our primary objectives include fortifying cybersecurity defenses against phishing threats, innovating through the integration of diverse attention mechanisms with GRU, and substantiating the efficacy of our model through rigorous evaluation metrics. As the realm of cybersecurity confronts escalating challenges, our research not only offers valuable insights but also charts a promising trajectory for future advancements in cybersecurity strategies.

Cyber Security Incident Response

In response to the growing cyber-attack threat, incident response teams have become a critical component of an organization's cybersecurity strategy. These teams are responsible for detecting, analyzing, and responding to security incidents promptly and effectively. However, detecting code injection attacks can be particularly challenging, as they can be difficult to detect and often go unnoticed until it is too late. Cybersecurity professionals use detection tools to detect and respond to DLL injection attacks that monitor system activity and detect unusual behavior. A large portion of the related literature focuses on the use of commercial DLL injection tools. In contrast, little attention has been paid to the effectiveness of using open-source DLL injection detection tools. Thus, this research project aims to evaluate the effectiveness of three widely used open-source tools, VirusTotal, Sysinternals, and Yara, in detecting DLL injection incidents. This study's findings highlight each tool's strengths and limitations, which in turn enables cybersecurity professionals to make informed decisions when selecting the most suitable tool for DLL injection detection. Furthermore, the study emphasizes the importance of continuous tool development and updates to keep pace with evolving malware techniques and emerging threats. By highlighting the effectiveness of the tools, this research enhances the overall security posture of organizations and individuals, empowering them to mitigate the risks associated with DLL injection attacks proactively. The outcomes of this research project also underscore the significance of leveraging advanced tools to fortify cybersecurity defenses and safeguard critical systems and data.

Harnessing adversarial machine learning for advanced threat detection: AI-driven strategies in cybersecurity risk assessment and fraud prevention

The abstract is "The rapid evolution of cyber threats necessitates innovative defenses, particularly in the domains of risk assessment and fraud detection. This paper explores the integration of Artificial Intelligence (AI) and Adversarial Machine Learning (ML) techniques as a formidable strategy against increasingly sophisticated cyber-attacks. We present a comprehensive framework that leverages AI to dynamically assess cybersecurity risks and detect fraudulent activities with unprecedented accuracy and speed. Firstly, we delve into the foundational principles of adversarial machine learning, outlining how these techniques can be employed to simulate potential cyber threats, thereby enabling the development of more resilient AI-driven cybersecurity systems. We highlight the dual role of adversarial ML in both enhancing security defenses and potentially serving as a vector for sophisticated attacks, underscoring the importance of developing robust, adversarial-resistant models. Subsequently, we introduce a novel adaptive risk assessment methodology that incorporates real-time data analysis, machine learning algorithms, and predictive modeling to accurately identify and prioritize threats. This method adapts to the evolving digital landscape, ensuring that cybersecurity measures are always one step ahead of potential attackers. In the context of fraud detection, we explore -how AI algorithms can sift through vast datasets to detect anomalies and patterns indicative of fraudulent behavior. Through case studies and empirical analysis, we demonstrate the effectiveness of AI in identifying fraud across various sectors, from financial transactions to online identity verification processes. Our research contributes to the cybersecurity field by providing a detailed examination of how AI and adversarial ML can be harnessed to fortify digital defenses, improve risk assessment techniques, and enhance fraud detection capabilities. The insights garnered from this study not only advance theoretical understanding but also offer practical guidance for organizations seeking to implement AI-driven security solutions. As cyber threats continue to evolve, the integration of AI and adversarial ML in cybersecurity strategies will be paramount in safeguarding digital assets and maintaining the integrity of online systems."

A STUDY ON THE EMPLOYEE’S OPINION TOWARDS EFFECTIVENESS OF CYBER SECURITY MEASURES IN OMEGA HEALTHCARE

The study examines employee satisfaction and perceptions regarding cybersecurity measures at Omega Healthcare. It aims to assess management support, factors affecting security training, challenges in policy adherence, and suggests improvements. Using a mixed-methods approach, it combines surveys and interviews with a diverse sample of employees. Surveys gauge satisfaction levels and policy adherence, while interviews delve into experiences and suggestions. The findings aim to inform Omega Healthcare's cybersecurity strategy, promoting a culture of security awareness and compliance.

The Cybersecurity Strategy of the Republic of Poland as a Source of Internal Law

The Cybersecurity Strategy of the Republic of Poland as a Source of Internal Law

Cybersecurity in Healthcare: Need of the Hour

Data is said to be the new oil which has the highest value in the black market and the healthcare sector has the highest amount of data in the form of patient information. The healthcare sector is poor in securely managing the data and cyber attackers leverage on this information to steal the data through phishing, ransomware and other methods. Phishing is the most common cybercrime in healthcare. In ransomware attacks, malware is injected into a system through phishing emails to encrypt sensitive data and demand ransom to restore access to the system. Insider threats are very tough to detect and prevent. The healthcare institutions have now realised there shortcomings and have adopted various cybersecurity methods and frameworks to protect them from heavy loss. Cybersecurity in healthcare can be improved by various ways such as encryption, network segmentation, employee training and regular security assessment. All cybersecurity strategies should incorporate the 5 C’s – change, compliance, cost, continuity, coverage. Cybersecurity frameworks provide a structured approach to managing and mitigating cyber risks. During COVID 19 the healthcare sector was affected both workwise and digitally because of increased cyber attacks.

Security Information Event Management data acquisition and analysis methods with machine learning principles

In the face of increasing global disruptions, the cybersecurity field is confronting rising threats posed by offensive groups and individual hackers. Traditional security measures often fall short in detecting and mitigating these sophisticated attacks, necessitating advanced intrusion detection methods. The goal of our study is to develop robust network intrusion detection methods using machine learning techniques. In addition, we evaluate the effectiveness of various machine learning models in detecting network intrusions. Model performances are optimized through hyperparameter tuning and feature selection. A range of classification and clustering models have been employed. Data from SIEM systems capturing real-time statistics from cloud-hosted Windows virtual machines has been gathered and augmented with web attack logs from CICIDS2017, each comprising approximately fifteen thousand rows. Hyperparameter tuning, data normalization, standardization and feature selection techniques for model optimization have been used in our study. The research showcases the potential of machine learning in enhancing network intrusion detection capabilities. The findings underscore the effectiveness of the Random Forest Classifier (0.97) and highlight the importance of utilizing diverse datasets and advanced optimization techniques. This study offers valuable insights and sets a foundation for future advancements in cybersecurity strategies and intrusion detection systems.

Cyber Threat Intelligence: A Comprehensive Overview and Practical Implementation

Cyber Threat Intelligence (CTI) has emerged as a critical component in modern cybersecurity strategies. CTI encompasses the proactive gathering, analysis, and dissemination of information about potential cyber threats, including threat actors, tactics, techniques, and procedures (TTPs), vulnerabilities, and indicators of compromise (IOCs). By harnessing a combination of technology, human expertise, and collaborative partnerships, CTI enables organizations to enhance their ability to detect, prevent, and respond to cyber attacks effectively. This paper provides a comprehensive examination of CTI, including its definition, importance, lifecycle, sources, and practical implementation strategies. By exploring various CTI frameworks, methodologies, and tools, organizations can effectively leverage threat intelligence to enhance their security posture and proactively defend against cyber threats

Securing the Digital Frontier: Strategies for Cloud Computing Security, Database Protection, and Comprehensive Penetration Testing

This research paper explores the effectiveness of integrated cybersecurity strategies, focusing on the amalgamation of cloud computing security, database protection, and penetration testing into a unified risk management framework. The primary aim is to evaluate how such integration impacts the overall cybersecurity posture of organizations, offering insights into mitigating cyber threats, unauthorized access, and data breaches. Employing a survey-based methodology, the study gathered data from 365 professionals across cloud computing, database administration, and cybersecurity fields. Through descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM), the research explored the interrelations between various cybersecurity strategies and their collective influence on organizational resilience against cyber threats. The findings underscore the significant benefits of a holistic cybersecurity approach, revealing that penetration testing, robust database security measures, and strict adherence to cloud computing security requirements significantly reduce vulnerabilities and incidents of data breaches. Moreover, the study established that a unified risk management framework substantially enhances an organization's cybersecurity posture, highlighting the critical role of integrated security measures in fostering organizational resilience. The research confirms the hypothesis that incorporating cybersecurity strategies across different domains leads to a synergistic enhancement of security defenses, offering a more robust mechanism against the multifaceted nature of cyber threats. In conclusion, the study advocates for the adoption of a comprehensive, integrated approach to cybersecurity, emphasizing regular penetration testing, stringent database security protocols, and adherence to cloud computing security standards as essential components of a robust cybersecurity framework. This approach not only mitigates the risk of cyber threats but also strengthens organizational resilience, ensuring a secure digital environment for future challenges.

Estimating Malware Impact on Network Traffic Analysis by Using Wireshark

With the increasing prevalence of advanced cyber threats, there is a growing need for effective cybersecurity measures that can detect and visualize malware attacks. This research introduces an integrated approach that combines malware detection techniques with geospatial visualization methods to enhance the identification and analysis of cyber-attacks. By analyzing packets in the HTTP protocol, we identify suspicious file transfers and compute their hash values for further examination. To assess the threat level of these transferred files, we utilize the Virus Total platform to conduct comprehensive scans for malware. At the same time, by utilizing geolocation data, we map out both the origins and destinations of these attacks, providing valuable spatial context for understanding global patterns in cyber threats. In addition to enabling the identification of potentially harmful files, the proposed approach also provides a comprehensive visualization of how these threats are spread geographically. Our findings contribute to advancing cybersecurity strategies by facilitating proactive threat mitigation and enhancing incident response capabilities. The integration of malware detection, hash analysis, and geospatial visualization emphasizes the importance of adopting a multidimensional approach in strengthening network security infrastructure.

Can We Develop Holistic Approaches to Delivering Cyber-Physical Systems Security?

Can We Develop Holistic Approaches to Delivering Cyber-Physical Systems Security?

Implementing SIEM(Security Information and Environment Management) in Microsoft Azure

Abstract: In an increasingly interconnected and digital world, the need for robust cybersecurity measures is paramount. Cyberattacks can therefore occur upon any device at any moment of time in order to steal the sensitive information of the user or can result in identity theft and cyberbullying. There are varieties of attacks that may occur without the user being aware about the same that their computer has been attacked and the hacker has overall access of their data. Also, a user cannot sit in front of their device throughout their life to monitor and protect any type of cyberattack. Therefore, in order to solve the following problems and to enhance the overall security and accuracy of safeguarding the device and its data, we implement our project Security Information and Environment Management (SIEM) system within the Microsoft Azure cloud ecosystem. SIEM plays a critical role in monitoring, detecting, and responding to security threats, making it a crucial component of any organization's cybersecurity strategy. To view the notification of the attack for a user and all its details, we therefore connect the SIEM implementations and logs over Microsoft Azure platform, and generate the same with the help of a command-shell Windows PowerShell.

CYBER SECURITY ATTACK DETECTION MODEL USING SEMI-SUPERVISED LEARNING

The increasing digitalization of our society has brought about numerous benefits, enabling seamless communication, convenient transactions, and efficient operations. However, with this growing reliance on interconnected systems and information technology, the risk of cyber-attacks has also surged. Cyber threats, such as data breaches, ransomware, and sophisticated malware, have become more prevalent, threatening the confidentiality, integrity, and availability of critical data and services. Organizations across industries face the daunting challenge of defending against a wide array of cyber-attacks that continue to evolve in complexity and stealth. In response to this ever-changing cyber threat landscape, Cyber Security Risk Management (CSRM) and attack detection have become critical components of any comprehensive cybersecurity strategy. The ability to identify and mitigate cyber risks and swiftly detect malicious activities is paramount for safeguarding sensitive information, preserving business continuity, and maintaining the trust of customers and stakeholders. A novel approach to Cyber Security Risk Management through an Attack Detection Model that utilizes Semi-Supervised Learning Auto-Encoders in conjunction with Probabilistic Bayesian Networks. The study compares the performance of Multi Connect Variational Auto-Encoder (MC-VAE), Probabilistic Bayesian Networks (PBN), and a combined model of MC-VAE and PBN. The study employs the NUSW-NB15_GT dataset for training and evaluation purposes. Notably, the Semi-Supervised Learning with Probabilistic Bayesian Networks (SSL-PBN) model demonstrates exceptional results, achieving a precision rate of 94% and a recall rate of 90%. The F1 score of 0.9191 highlights the SSL-PBN model's efficacy in achieving a balanced trade-off between precision and recall, critical for minimizing false positives and false negatives...