IT Environment Research Articles

Five Dimensions of AI Readiness (AIR-5D) Framework- A Preparedness Assessment Tool for Healthcare Organizations

Background: Artificial Intelligence (AI) has transformative potential in healthcare, and it is very useful in areas such as drug discovery, diagnostics, and patient management. However, there is a lack of tools to assess healthcare organizations’ readiness to adopt AI technologies. This study introduces the AI Readiness Five Dimension (AIR-5D) framework, addressing this gap. Methods: The AIR-5D framework was developed using a two-step process: identifying dimensions of AI readiness from literature and weighing these dimensions through expert focus groups. The Analytical Hierarchy Process (AHP) was employed to calculate weights, ensuring consistency and reliability. Results: The results identified five key dimensions: Opportunity Discovery (0.44), Data Management 90.22), IT Environment and Security (0.194), Risk Privacy and Governance (0.101), and Adoption of Technology (0.043). “Opportunity Discovery” was the most critical dimension, while “Adoption of Technology” ranked lowest. Six case studies demonstrated varying AI readiness (score between 3 and 4 on a scale of 5), highlighting challenges in moving beyond AI collaboration to optimization. Conclusions: The AIR-5D framework offers a structured approach for healthcare organizations to assess and enhance their AI readiness. It emphasizes the importance of understanding value, robust data management, and strategic alignment in successful AI adoption.

Agentic AI in Predictive AIOps: Enhancing IT Autonomy and Performance

The integration of Agentic Artificial Intelligence (AI) within Predictive AIOps (Artificial Intelligence for IT Operations) is revolutionizing the management of IT systems, significantly enhancing IT autonomy and performance (Smith & Johnson, 2023). This article explores the potential of Agentic AI to empower AIOps platforms in proactively predicting, identifying, and resolving system issues. By leveraging predictive analytics and machine learning, AIOps not only enhances operational efficiency but also minimizes downtime and supports autonomous decision-making in complex IT environments (Lee et al., 2022). We examine the key roles that Agentic AI plays in improving performance metrics, optimizing resource allocation, and reducing the reliance on human intervention in critical system operations (Garcia & Patel, 2024). Additionally, this study investigates the implications for IT infrastructure scalability, long-term resilience, and the evolution toward self-governing systems (Chen, 2023). The findings underscore the transformative impact of Agentic AI on future IT operations, showcasing its potential to foster higher levels of automation and operational intelligence.

Nist Aal Adaptive Security Framework

In our digitally evolving security world, adaptive and risk - based authentication methods are the key countermeasures responding to the current rising cyber risks. The National Institute of Standards and Technology (NIST) Authenticator Assurance Levels (AAL) framework offers a specific guidance on the implementation of adaptive security measures. The study is designed to put the "NIST AAL Adaptive Security Framework" into practice by using technologies such as Ping Federate and Ping Davinci systems for the timely risk analysis of IT environments and advanced MFA approaches against emerging threats. AAL model can define authentication procedures customized as per the level of risk, requirements and compliance regulations of the organization. It is essential to classify authentication into separate assurance level (AAL1, AAL2 and AAL3) as it helps to make modifications according to contextual factors like perceived risk and user's behaviour. This is vital as it enhances security while it optimizes user experience. This study examines the proposed framework’s efficacy in reducing cyber - threats and strengthening security posture of organizations.

AGILE PROJECT MANAGEMENT: ANALYZING THE EFFECTIVENESS OF AGILE METHODOLOGIES IN IT PROJECTS COMPARED TO TRADITIONAL APPROACHES

This systematic review examines the comparative effectiveness of Agile and traditional project management methodologies, focusing on their application in dynamic IT environments and well-defined industries. Utilizing the PRISMA guidelines, a total of 45 peer-reviewed studies published between 2005 and 2023 were analyzed. The review found that Agile methodologies consistently outperformed traditional approaches in dynamic settings, offering greater flexibility, faster project delivery, and higher customer satisfaction through iterative cycles and continuous stakeholder engagement. However, traditional methods, such as Waterfall, were found to be more effective in projects with fixed scopes and stringent regulatory requirements, providing better control and predictability. The review also highlights the growing adoption of hybrid project management models, which combine Agile’s adaptability with the structure of traditional methods, particularly in large or complex projects. The findings underscore the importance of selecting the appropriate methodology based on project-specific factors, with Agile excelling in fast-changing environments and traditional methods being more suitable for regulated industries. Further research is recommended to explore Agile’s applicability in non-IT sectors and the long-term effectiveness of hybrid models.

Planning and Preparation of Cybersecurity

In today's digital environment characterized by fast-evolving adversaries, expanded attack surfaces, and complex IT environments, having a formidable plan and being prepared could create a world of difference when faced with a potential cyber-attack. Cyber threats are growing risks to everyone and any institution. Cybercriminals target individuals and companies of all sizes. Today's attacks are agile and sophisticated. Ransom demands are elevating and advancing rapidly while attackers drill down their focus to specific victims like critical infrastructure businesses, which can spend millions of dollars in losses from cyber disasters since such companies have less tolerance for downtime. The evolution of artificial intelligence technology, which is more interesting and scarier at the same time, is impacting the field of cybersecurity. The negative side of AI is that it has enabled threat actors to blend new data theft-based extortion techniques into ransomware. Attackers can steal companies' sensitive data or even encrypt the data and demand ransom for the decryption key failure, to which they threaten the company to expose the data to the public or even trade in the dark web. The intelligent techniques and tactics utilized by threat actors are a clarion call for organizations to proactively plan and prepare adequately by developing a cybersecurity strategy as a countermeasure. A cybersecurity strategy is a comprehensive plan that stipulates an organizational approach to secure its IT infrastructure against cyber threats. The common cybersecurity strategy various organizations use to plan and prepare for inevitable attacks is the incidence response plan. Incidence response is the processes and technologies organizations use to detect and respond to cyber threats, security breaches, or cyberattacks within an organization. Developing and implementing a formal incident response plan allows organizations to minimize and prevent damage. This research paper focuses on the primary goal of the incident response of preventing cyberattacks prior to occurring and reducing the cost and business disruption emanating from cyberattacks that happen. Keywords – incident response, threats, Artificial intelligence, cybersecurity, threat attacks, plan, preparation.

Numerical analysis of rack-based data center cooling with rear door heat exchanger (RDHx): Interrelationship between thermal performance and energy efficiency

This study presents a comprehensive numerical analysis of thermal performance and energy efficiency, IT operating environment, and thermal performance of the RDHx system, a rack-based cooling solution for high-density IT power using air-cooled equipment. A 150 kW IT module and RDHx cooling system were designed and evaluated, and CFD numerical analysis confirmed that RDHx maintains a stable IT environment within ASHRAE standards at a supply air temperature of 24 °C. Additionally, the chilled water supply temperature for the secondary CDU can be increased to 14 °C, and for the primary chiller to 12 °C. A central chilled water system for a 30 MW reference data center was designed and analyzed, showing increased efficiency with a 12 °C supply temperature and varying condenser water return temperatures in winter, resulting in an annual PUEcooling range of 1.25–1.33, with an average of 1.27. The annual energy consumption distribution for rack-based cooling is approximately 46 % from chillers, 21 % from fans, and 33 % from pumps. These results provide crucial insights into data center cooling and support the application of the RDHx system in high-density data centers, with future validation involving a field mock-up test of a 150 kW IT module.

A novel approach for application classification with encrypted traffic using BERT and packet headers

Recent years have seen substantial advancements in Internet technology along with environmental changes, which have led to the emergence of various security issues. There is also a trend of explosive growth in applications that encrypt network traffic for various types of services. Therefore, the classification of applications within encrypted traffic represents an important research issue for both secure network management and efficient bandwidth management. In such encrypted traffic, the payload itself is encrypted, and it is no longer viable to classify applications based on signatures extracted from plaintext. Most applications in public datasets for encrypted traffic classification are collected with the same IP address and port number, which makes the 5-tuple information a strong identifier. However, this 5-tuple contains many characteristics related to both the traffic collection environment and user-specific traits, rather than intrinsic features of the applications themselves. Therefore, when addressing the problem of encrypted traffic application classification, it is advisable to utilize header information excluding the 5-tuple and payload. Therefore, this paper proposes a novel service type and application classification system based on the Bidirectional Encoding Representation Transformer (BERT), which utilizes packet header information from encrypted traffic. The proposed system ensures the accuracy and generalization performance of the classification model by using only the header information from traffic packets, excluding the 5-tuple and payload. Further, to preserve the characteristics and semantic meaning of an encrypted traffic packet, sentences embedded with 2-byte tokens were used as input for BERT. The proposed system was designed to exclude labeling information from all sentences during the pre-training phase before proceeding with training. Fine-tuning was then conducted to align the system with the objectives of the service type and application classification. This experiment utilized the publicly available ISCX VPN-nonVPN dataset, and the proposed model achieved remarkable accuracy in the key performance measure, i.e., F1-scores, with values of 99.24 % in service type classification and 98.74 % in application classification. This capability can be used in maintaining the confidentiality of encrypted traffic, network security monitoring, Quality of Service (QoS), and traffic management in complex IT environments.

Continuous Service Improvement in IT Operations through Predictive Analytics

In the evolving landscape of IT operations, continuous service improvement is essential for maintaining high performance, reliability, and customer satisfaction. Predictive analytics, leveraging advanced data analysis techniques and machine learning algorithms, offers a transformative approach to enhancing IT service management. This research paper explores the integration of predictive analytics into IT operations to drive continuous service improvement. It investigates how predictive models can forecast potential issues, optimize resource allocation, and enhance decision-making processes, ultimately leading to improved operational efficiency and service quality. The study begins with an overview of traditional IT service management practices and the limitations they face in adapting to dynamic and complex IT environments. Conventional approaches often rely on reactive problem-solving and periodic reviews, which can lead to inefficiencies and missed opportunities for proactive intervention. Predictive analytics offers a paradigm shift by utilizing historical data and real-time information to predict future outcomes, enabling organizations to address potential problems before they impact operations.

Balancing Agility and Control: A Comparative Analysis of Change Management in ServiceNow and BMC Helix

Abstract: This research paper presents a comprehensive comparison of the Change Management applications offered by ServiceNow and BMC Helix. The study examines key features, risk assessment capabilities, approval workflows, integration with other ITSM processes, and reporting tools of both solutions. By evaluating their strengths and weaknesses in managing IT changes, this paper aims to provide insights for organizations seeking to optimize their change management processes in increasingly dynamic IT environments.

Illuminating IT Landscapes: A Comparative Analysis of Discovery in ServiceNow and BMC Helix

Abstract: This research paper presents a comprehensive comparison of the Discovery applications offered by ServiceNow and BMC Helix. The study examines key features, discovery mechanisms, data collection capabilities, integration with CMDB, automation features, and analytics tools of both solutions. By evaluating their strengths and weaknesses in discovering and mapping IT assets and relationships, this paper aims to provide insights for organizations seeking to enhance their visibility into complex IT environments and improve overall IT service management.

Continuous Service Improvement in IT Operations through Predictive Analytics

In the evolving landscape of IT operations, continuous service improvement is essential for maintaining high performance, reliability, and customer satisfaction. Predictive analytics, leveraging advanced data analysis techniques and machine learning algorithms, offers a transformative approach to enhancing IT service management. This research paper explores the integration of predictive analytics into IT operations to drive continuous service improvement. It investigates how predictive models can forecast potential issues, optimize resource allocation, and enhance decision-making processes, ultimately leading to improved operational efficiency and service quality. The study begins with an overview of traditional IT service management practices and the limitations they face in adapting to dynamic and complex IT environments. Conventional approaches often rely on reactive problem-solving and periodic reviews, which can lead to inefficiencies and missed opportunities for proactive intervention. Predictive analytics offers a paradigm shift by utilizing historical data and real-time information to predict future outcomes, enabling organizations to address potential problems before they impact operations.

Agile Project Planning and Execution in Large-Scale IT Projects

Agile methods have changed project management, particularly for major IT projects. This abstract examines Agile project planning and execution in complex IT settings, where size and scope bring distinct problems. Traditional project management methods struggle to handle major IT projects' fast changes and complexity. Agile's focus on flexibility, collaboration, and customer-centricity makes it ideal for these situations due to its adaptability. Agile planning breaks complicated IT project needs into manageable components or iterations in large-scale initiatives. Iterative development keeps projects manageable and adaptable. Agile stresses frequent feedback loops, where each iteration is examined, to help teams change and realign their objectives. Large IT projects need ongoing feedback since mistakes may be costly and team alignment is essential. Cross-functional teams are crucial to Agile in big projects. Agile fosters cross-disciplinary cooperation, which is crucial in big IT environments where development, operations, security, and business teams must collaborate. Teams meet regularly, called'scrums,' to review progress, identify barriers, and plan future actions. With its focus on openness and responsibility, the scrum structure keeps team members aligned and the project on pace. Resource management is another important part of Agile project planning for big IT projects. Agile resource allocation is dynamic, unlike set schedules. Large IT projects, where resource demands vary fast, need this flexibility. Thus, agile techniques reduce waste and ensure teams have what they need at each project stage by optimizing resource utilization. Large Agile project execution involves risk management. Due to Agile's iterative structure, teams may regularly analyze risk and address problems before they become significant. Risks may be exacerbated in big IT projects, thus proactive risk management is crucial. Agile teams see risks as opportunities to improve, promoting continual learning and adaptability.

Defense in Depth Strategies for Zero Trust Security Models

The groundbreaking Zero Trust Security Model challenges perimeter-based protections in cybersecurity. As cyber threats become more sophisticated, corporations are embracing the Zero Trust philosophy of "never trust, always verify." Whether from within or outside the network, this paradigm imposes rigorous access rules and continual authentication. Zero Trust is a strong security foundation, yet it has drawbacks. The Zero Trust paradigm is enhanced by Defense in Depth, which layers several security methods to safeguard assets. This article examines how the Zero Trust Security Model might include Defense in Depth methods for a complete, robust, and adaptable security architecture. Zero Trust requires all users and devices to be verified, approved, and continually vetted before accessing resources, eliminating implicit trust. A typical method employed by attackers after breaching the perimeter is lateral movement inside the network, which this approach mitigates well. However, Defense in Depth—deploying numerous, redundant security measures throughout the IT environment—is a proven method. Defence in Depth and Zero Trust may be combined to strengthen access restrictions, detection, response, and recovery.

Enhancing IoT device security in Kubernetes: An approach adopted for network policies and the SARIK framework

The Internet of Things (IoT) has ushered in an era of connected devices that, while facilitating real-time data collection and sharing, also exposes these devices to significant security risks. This study addresses the challenges of security risks and vulnerabilities by employing the Network Policy in Kubernetes and focusing on the SARIK framework. SARIK is designed to automate the creation and implementation of network policies, with the aim of enhancing the efficiency and strengthening the protection of IoT devices. Experiments conducted in a controlled environment with Minikube in Kubernetes showed that the implementation of SARIK notably improved the security of IoT devices. Key observations included a noticeable reduction in vulnerability to cyberattacks and a significant increase in the overall resilience of the system. In particular, the study revealed improvements in the performance metrics analyzed, which is evidence of SARIK’s effectiveness in real-world scenarios. Compared with existing frameworks - e.g., those of Sysdig -, SARIK is notable for its integration with Kubernetes network policies and its emphasis on automated security management. Although automation is a key factor in related works, SARIK’s unique approach to leveraging the inherent capabilities of Kubernetes offers a distinct advantage in ensuring the security of IoT environments. This aspect, along with its performance benefits, underlines the value of SARIK’s contribution to IoT security. The application of SARIK in protecting IoT devices in Kubernetes environments meets the need for automated and cohesive strategies to tackle current security threats. This study not only highlights the efficiency of SARIK but also emphasizes the need for evolving security strategies, that can be adapted to dynamic threat modeling in complex and interconnected IT environments.

Exploring complexities of innovation capability in Vietnam’s IT firms: Insights from an integrated MCDM model-based grey theory

This study addresses the complexities of fostering innovative behavior in Vietnam’s IT firms, a critical aspect of maintaining competitive advantage in the rapidly evolving IT sector. Using an integrated Grey theory incorporating Delphi and Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods, we explore the interdependencies among critical factors driving innovation within organizational contexts. The research draws on a comprehensive literature review and insights from 16 Vietnamese experts, identifying 21 critical factors across five dimensions: leadership and vision, culture and environment, learning and development, management and support, and technological resources. Our findings emphasize the paramount importance of visionary leadership and a risk-taking culture in enhancing innovation capability, with technological infrastructure also playing a significant role. Consequently, we recommend that IT companies prioritize visionary leadership and cultivate a culture that embraces risk to bolster innovation ecosystems. Hence, this study contributes significantly to the theoretical discourse on innovation capabilities within IT environments and offers practical recommendations for organizations in emerging markets like Vietnam.

Transforming business scalability and operational flexibility with advanced cloud computing technologies

In the rapidly evolving landscape of digital transformation, cloud computing has emerged as a pivotal technology enabling businesses to achieve unparalleled scalability and operational flexibility. This review explores the transformative impact of advanced cloud computing technologies on business operations, highlighting key innovations and their implications for organizational growth and efficiency. Cloud computing offers a dynamic and scalable environment where resources can be provisioned and managed on-demand, allowing businesses to respond swiftly to changing market conditions and customer demands. By leveraging cloud infrastructure, companies can scale their operations seamlessly without the need for significant upfront investments in physical hardware. This flexibility not only reduces capital expenditure but also enhances the ability to innovate and adapt in a competitive marketplace. Advanced cloud technologies, such as multi-cloud and hybrid cloud solutions, further augment operational flexibility by enabling organizations to optimize their IT environments. Multi-cloud strategies allow businesses to distribute workloads across multiple cloud providers, mitigating the risks associated with vendor lock-in and ensuring high availability and redundancy. Hybrid cloud solutions, which integrate on-premises infrastructure with public and private clouds, provide a balanced approach to managing sensitive data and workloads while benefiting from the scalability of the cloud. Moreover, cloud-native technologies like containerization and serverless computing have revolutionized application development and deployment. Containers encapsulate applications and their dependencies, ensuring consistency across different computing environments and facilitating rapid deployment. Serverless computing reviews the underlying infrastructure, allowing developers to focus solely on code, thus accelerating the development cycle and reducing operational overhead. The integration of advanced analytics and artificial intelligence (AI) with cloud computing further enhances business capabilities. Cloud platforms offer robust analytics tools and AI services that can process vast amounts of data in real-time, providing actionable insights and enabling predictive decision-making. This integration empowers businesses to optimize operations, improve customer experiences, and drive strategic initiatives with data-driven precision. In conclusion, advanced cloud computing technologies are instrumental in transforming business scalability and operational flexibility. By harnessing the power of the cloud, organizations can achieve greater agility, cost efficiency, and innovation, positioning themselves for sustained growth and competitive advantage in the digital age. As cloud technologies continue to evolve, their potential to redefine business operations and drive economic value will only expand, making cloud adoption a critical imperative for modern enterprises. Keywords: Operational Flexibility, Transforming, Business Scalability, Advanced, Cloud Computing Technologies.

Validation of Sensor Data Integrity in OT Environments Through Multisource Data Sensors

This research paper focuses on detecting cyber threats from the OT environment by combining data from multiple sources. Monitoring cyber security or hybrid threats in an industrial OT environment is difficult due to different equipment, protocols, environments, personnel management and training, etc. However, the OT environment can also be observed with a multisource sensor system, which can be used to collect data. By combining IT and OT data, additional cyber threats can be found. Especially concerning the integrity of OT command-and-control data. We deal with the key concepts and differences of the industrial operating environment, which create challenges compared to the traditional IT environment. This is important because the policies defined at the European level for the NIS2 regulation are coming to touch all member countries, regardless of what the national implementation schedule is. The increased standards for OT environment cyber security implementation and development will also have an impact on the personnel management and training to support the onboarding of the standards in practice. Critical infrastructure protection is important because, without the protection of critical infrastructure, vital functions cease to function. Hostile actors cause security challenges among Western actors. In this study, we delve into whether it is possible to find threats concerning OT command-and-control process. The increased data surface collected from the IT/OT environment improves the capabilities for the system to detect malicious attacks towards the OT system. With the help of test equipment, the goal is to demonstrate that it is possible to find threats by combining data from multiple sources. With the help of test equipment, we find out IT and OT capabilities, which we load with various attacks and anomalies. We produce added value compared to traditional monitoring method test cases by comparing data obtained from different sources. The research paper shows the importance of detecting OT threats. By monitoring IT and OT environments and combining their data, we can find hidden threats. Only one test equipment configuration has been used in the study, but the results can be generalized and classified. The study also provides guidelines for how the detection of cyber threat capabilities should be developed.

Improving Detection Capabilities in OT Environments Through Multisource Data Sensors

This research focuses on implementing cyber threat detection in OT environments by combining data from IT and OT sensors and logs to enhance SOC's situational awareness. OT environment is challenging to monitor and includes various sensors. We deal with the key concepts and differences of the industrial operating environment, which create challenges compared to the traditional IT environment. This is important because the policies defined at the European level for the NIS2 regulation will affect all member countries. Hostile actors cause security challenges highlighting the importance of critical infrastructure protection. Cyber security solutions have often solely focused on IT threats, but similar investments have yet to be made in response to the challenges of the OT environment. The security solutions of OT operators rely heavily on solutions from the IT side. Here, we delve into whether it is possible to find threats in the IT/OT ecosystem by combining data from the IT and OT sides. All threats are not found by monitoring data separately from IT or OT sources but we identified hidden threats by monitoring and comparing IT and OT data. This paper shows the importance of detecting OT threats. The study proposes how the detection of cyber threat capabilities should be developed.

Designing an Alternative Typeface to Reflect the Identity of the ITS Campus

This research aims to design a new typeface that reflects the characteristics of the Institut Teknologi Sepuluh Nopember (ITS) campus and can be used in a variety of contexts. The new typeface, ITS-Artistech, was created by synthesizing key features into the anatomy of Latin letters, which were extracted from the key characteristics and images of the ITS campus. The typeface is intended to be one of several typographic options that reflect ITS and to pioneer typeface production at ITS, contributing to the theoretical and practical body of knowledge on designing typefaces that reflect campus identity. The research method involved collecting data on the use of typefaces in the ITS environment and ITS profile, conducting perceptual studies to know how people perceive the images and characteristics of the ITS campus, and developing the typeface through a series of iterative refinement steps. The new typeface is a valuable resource for the ITS community, as it helps to promote the university's brand, foster a sense of community, and support the creative process and the research of typeface design. It is also a unique and distinctive typeface that is not based on any preexisting letters. The typeface is available as a digital letterform (font) that can be installed and used for a variety of purposes, including digital and print promotional materials.

Improving IT Control Compliance using Artificial Intelligence

In an era where digital transformations are not just trends but necessities, the reliability and security of information systems have become paramount. The complexity of modern IT environments, coupled with increasing regulatory demands, poses significant challenges for organizations worldwide. IT control compliance, particularly in the context of Sarbanes-Oxley Act (SOX) IT General Controls (ITGC), requires rigorous and continuous monitoring to ensure that financial reporting and data integrity are maintained. However, traditional compliance efforts are often hampered by manual processes that are both time-consuming and error-prone. These methods struggle to keep pace with the dynamic nature of IT advancements and the evolving landscape of cyber threats. This gap not only increases the risk of non-compliance but also places a heavy burden on the resources of the organization. With the advancement of Artificial Intelligence (AI), there is promising potential to revolutionize these processes. AI technologies, through their capability to analyze large volumes of data and recognize patterns quickly, can automate complex tasks, enhance decision-making, and significantly improve the efficiency and effectiveness of compliance systems. By integrating AI into IT control frameworks, organizations can address the perennial challenges of compliance more effectively. AI-driven systems can reduce human error, streamline control processes, and ensure more robust governance and risk management frameworks. This paper explores the integration of AI technologies into IT control frameworks. It discusses how leveraging AI not only aids in maintaining compliance with existing regulations but also enhances the organization’s ability to adapt to new regulatory changes swiftly, thus safeguarding against compliance risks and fostering a culture of continuous improvement in governance practices.