International Journal for Global Academic & Scientific Research
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64 research outputs found
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Cybersecurity Management: Developing Robust Strategies for Protecting Corporate Information Systems
Full text linkThis growing complexity and sophistication of cyber threats call for a sea change concerning how organizations handle cybersecurity. Traditional isolated, reactive security models no longer protect against evolving digital risk. This abstract provides an innovation-oriented comprehensive methodology for completely transforming the approach of organizations to the protection of their critical information assets. At the heart of the method lies a recognition of the fact that cybersecurity is not strictly a technological challenge but has multifaceted elements that have to be aligned with the overall business objectives operational constraints, and risk tolerance of the organization. One of the crucial innovations is the integration of advanced analytics, blockchain technology, and machine learning techniques that will enable any organization to create a much more accurate and proactive perspective related to its vulnerability to cyber threats. This holistic cybersecurity methodology can transform security posture, strengthen collaborative capabilities, and build a resilient cybersecurity ecosystem through effective implementation and validation. These insights and lessons learned will, no doubt, inspire and guide other organizations toward a more robust, adaptive, and collaborative approach to cybersecurity management as the organization continues to improve and further innovate in the field of best security practices
The Role of Internet of Things (IoT) in Transforming Facilities Management in Smart Cities
Full text linkThe shift in urban foundation and administrations inside keen cities requests a comprehensive, innovative, and user-centric strategy that continues coordinating cutting-edge advances. This paper presents a spearheading approach that leverages the control of the Web of Things (IoT), Counterfeit Insights (AI), and Machine Learning (ML) to revolutionize the way shrewd city offices are overseen. At the centre of this strategy is the improvement of a centralized, cloud-based Offices Administration Stage (FMP) that serves as the spine for keen city operations. The FMP acts as an integrated hub, drawing together information from numerous IoT sensors, building automation systems, and other urban infrastructure. The policy also encourages user-centred design in light of improving occupant comfort, productivity, and well-being. Backed by IoT sensors and AI-driven building computerization frameworks, robust natural condition control and vitality utilization streamlining of the FMP can assist in conveying a predominant client involvement inside savvy city office
Dynamic Data Scaling Techniques for Streaming Machine Learning
Full text linkThis research delves into innovative dynamic data scaling techniques designed for streaming machine learning environments. In the realm of real-time data streams, conventional static scaling methods may encounter challenges in adapting to evolving data distributions. To overcome this hurdle, our study explores dynamic scaling approaches capable of adjusting and optimizing scaling parameters dynamically as the characteristics of incoming data shift over time. The objective is to augment the performance and adaptability of machine learning models in streaming scenarios by ensuring that the scaling process remains responsive to changing patterns in the data. Through empirical evaluations and comparative analyses, the study aims to showcase the efficacy of the proposed dynamic data scaling techniques in enhancing predictive accuracy and sustaining model relevance in dynamic and fast-paced streaming environments. This research contributes to the advancement of scalable and adaptive machine learning methodologies, particularly in applications where timely and accurate insights from streaming data are crucial
How Credit Risk Management in Australia Can Affect Financial Institutions Growth: A Study
Full text linkIneffective credit risk management methods were largely responsible for the collapse, as well as financial problems, of many financial institutions. This particular research is designed to evaluate how insufficient credit risk management brought about the banking crisis of Australia in 2003/2004 determine other contributing factors. It found that inability to effectively manage credit risk was the most important element in the crisis, leading to ineffective management, insufficient risk control, poorly designed strategies for business expanding, persistent liquidity issues, external currency deficiency, as well as diversion from core banking pursuits to speculative non-banking activities. It suggests banks develop and implement credit scoring and assessment methods, update insider lending practices, and adopt prudential business governance methods
ICT\u27s Impact on SMEs in Zanzibar: A 360-Degree Appraisal
No full textThe integral role of Information and Communications Technology (ICT) in global socio-economic growth is universally acknowledged. Zanzibar, too, recognizes ICT\u27s potential to foster enterprise development.This study conducts a focused analysis of the symbiotic relationship between ICT and small and medium enterprises (SMEs) in Zanzibar, encompassing ICT\u27s significance, adoption challenges, and its impact on SMEs\u27 growth. Employing a descriptive research design, data collection involved a structured questionnaire distributed to a random sample of 100 respondents. Analysis was conducted using the Statistical Package for Social Science (SPSS), yielding insights communicated through percentages, tables, and graphs.
The findings underscore ICT\u27s pivotal role in SME development, with a substantial proportion deriving benefits from its integration. Key variables—ICT\u27s importance, implementation, and influence—are identified as catalysts for improved SME performance. However, challenges persist, including limited expertise, slow internet, setup costs, and security concerns, underscoring the need for refined ICT strategies. Recommendations echo the importance of continuous ICT enhancement, advocating for advanced tools to secure competitive advantages. Moreover, policy interventions by governmental bodies and private entities like the Chamber of Commerce are deemed necessary to facilitate SME education, training, and advisory services. This collective effort promises not only individual business growth but also national economic advancement.In summation, while ICT is a linchpin, factors like technology, customer care, and trust are equally vital. Governmental support for SMEs\u27 effective ICT integration emerges as a core necessity, propelling Zanzibar\u27s SMEs towards amplified growth within an increasingly digital landscape
Knowledge Transfer: A Critical Review of Research Approaches
Full text linkKnowledge transfer occurs when individuals in the organization share knowledge, skills, recommendations, and ideas pertinent to the organization. Individuals, members of one group, or members of different groups communicate. Direct commitment between the broadcaster and receiver is necessary to ensure that knowledge sharing is successful. Knowledge transfer considers sharing information throughout the organization\u27s divisions and employees. There has been tremendous growth in the amount of study done on knowledge generation and transfer. The latter is caused by knowledge development and transfer, both of which increase an organization\u27s competitiveness. Since the beginning of knowledge management research in the middle of the 1990s, the theoretical development of knowledge transfer has continued to grow. The researcher conducted a critical review of the literature to evaluate the various research approaches utilized by past studies. The paper tries to review and summarize the different approaches which will guide future research studies in knowledge transfer
Unleashing the Power of Multi-Agent Deep Learning: Cyber-Attack Detection in IoT
Full text linkDetecting botnet and malware cyber-attacks is a critical task in ensuring the security of computer networks. Traditional methods for identifying such attacks often involve static rules and signatures, which can be easily evaded by attackers. Dl is a subdivision of ML, has shown promise in enhancing the accuracy of detecting botnets and malware by analyzing large amounts of network traffic data and identifying patterns that are difficult to detect with traditional methods.
In order to identify abnormal traffic patterns that can be a sign of botnet or malware activity, deep learning models can be taught to learn the intricate interactions and correlations between various network traffic parameters, such as packet size, time intervals, and protocol headers. The models can also be trained to detect anomalies in network traffic, which could indicate the presence of unknown malware.
The threat of malware and botnet assaults has increased in frequency with the growth of the IoT. In this research, we offer a unique LSTM and GAN-based method for identifying such attacks. We utilise our model to categorise incoming traffic as either benign or malicious using a dataset of network traffic data from various IoT devices. Our findings show how well our method works by attaining high accuracy in identifying botnet and malware cyberattacks in IoT networks. This study makes a contribution to the creation of stronger and more effective security systems for shielding IoT devices from online dangers.
One of the major advantages of using deep learning for botnet and malware detection is its ability to adapt to new and previously unknown attack patterns, making it a useful tool in the fight against constantly evolving cyber threats. However, DL models require large quantity of labeled data for training, and their performance can be affected by the quality and quantity of the data used.
Deep learning holds great potential for improving the accuracy and effectiveness of botnet and malware detection, and its continued development and application could lead to significant advancements in the field of cybersecurity
Data Driven Decision Making in Manufacturing Businesses in China and Asia Pacific
Full text linkThe objective of this study is to investigate the mechanisms of Big data - based business model development in Chinese standard industries. Deductive reasoning as well as case analysis were employed to evaluate manufacturing businesses in China and confirm the devices. This process created an integrated framework with 3 components: Business model perspectives, processes together with big data driven company model advancements. Three Chinese businesses put the framework on revealing that business model development is a constant and growing process impacted by big data. Nevertheless, the study shows that limitations have a small sample size, that is typical in qualitative studies. Ideally, businesses will develop a solid infrastructure that combines the internet of things, traditional manufacturing methods and front end buyers. Furthermore, management must make sure that their organizational structure, climate, and human resources are well prepared for the transformation
Structural Analysis of Tunnel using FEA
Full text linkTunnels are typically built for transportation, such as roads, railways, or canals, but they can also be used for other purposes, such as mining, sewerage, or water supply. Tunnels allow us to travel safely and efficiently through difficult terrain, and they provide us with access to essential resources such as water and energy. The objective of current research is to evaluate the structural characteristics of tunnel structure under geo-mechanical loading conditions. The structural analysis of tunnel is conducted using techniques of FEA. The CAD modelling and FEA simulation of tunnel is conducted using ANSYS simulation package. The shear stress, normal stress and deformation data are generated. From the generated data, the critical regions are identified and the lateral zone of tunnel is one of them. This region is likely to induce damage in the form of crack
Role of Analytics and Accounting Information Systems in Profitability
Full text linkThe use of accounting information systems by small businesses has resulted in time savings, as well as increased reliability and security due to the availability of backups. This has allowed for the recognition of profits in both the short and long term, ensuring the continued operation of the business. However, small businesses often neglect profitability ratios, such as returns on product sales or profit margins, due to a lack of technical knowledge. Additionally, they struggle with performance comparisons and assessing their competitiveness with other companies. Standard costing methods and financial order inventory models have also been found to be ineffective for small businesses. Policy and government decision makers will need to devise policies and regulations that will facilitate the introduction of these devices into the corporate environment. This type of policy could include tax exemptions or even tax relief for devices used in these ways