Business Management

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  A DUAL-LAYER HYBRID SECURITY FRAMEWORK: ANALYZING DIGITAL MODELS TO ENHANCE CYBERSECURITY MANAGEMENT FOR START-UPS AND SMES

  The rapid evolution of generative AI is transforming cybersecurity practices by providing advanced capabilities for threat detection and response. For start-ups and SMEs, these technologies offer a cost-effective way to defend against sophisticated online threats without the need for massive capital investment. While AI facilitates the ... The rapid evolution of generative AI is transforming cybersecurity practices by providing advanced capabilities for threat detection and response. For start-ups and SMEs, these technologies offer a cost-effective way to defend against sophisticated online threats without the need for massive capital investment. While AI facilitates the identification of anomalies and malicious behavior, it also introduces new risks, such as deepfakes, zero-day exploits, and the potential for attackers to manipulate AI models themselves. The study examines the impact of large language models and artificial intelligence on the software and architecture of cybersecurity systems. The main types of attacks on artificial intelligence systems and the changes in the software development paradigm that result from them are being considered. To address the evolving threat landscape, this study proposes a Dual-Layer Hybrid Security Framework that integrates high-speed algorithmic detection with cognitive analysis. We present an algorithm for building a security system using LLM models. We also propose a software application tailored explicitly for the comprehensive analysis of network traffic while detecting cybersecurity incidents using Python and the Pandas library. Furthermore, it leverages artificial intelligence to provide a comprehensive approach to detecting and mitigating cybersecurity threats. This will enable start-ups and small businesses to manage their cybersecurity in-house.

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  ANALYSIS OF EMPLOYEE SATISFACTION IN THE NIGERIAN HEALTHCARE AND IT SECTORS

  This study explores the determinants of job satisfaction among professionals in Nigeria's healthcare and information technology sectors, with particular emphasis on the roles of supervisor support, compensation, benefits and workload. Data was collected through a questionnaire survey administered to a sample of 195 professionals, and analysed ... This study explores the determinants of job satisfaction among professionals in Nigeria's healthcare and information technology sectors, with particular emphasis on the roles of supervisor support, compensation, benefits and workload. Data was collected through a questionnaire survey administered to a sample of 195 professionals, and analysed using Pearson correlation coefficients to assess the strength and direction of relationships among the examined variables. The findings reveal a significant positive correlation between supervisor support and job satisfaction (r = 0.540), underscoring the critical role of effective leadership in enhancing employee morale. Furthermore, satisfaction with salary and benefits exhibits a strong positive association with overall job satisfaction (r = 0.629), highlighting the importance of offering competitive remuneration packages. Contrary to conventional assumptions, the study also identifies a positive correlation between increased workload and job satisfaction (r = 0.572), suggesting that higher job demands may, under certain conditions, contribute positively to employee engagement and fulfilment. These insights offer valuable implications for organisational policy and human resource management within high-demand professional environments.

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  DIGITAL TRANSFORMATION OF REPORTING-RELATED PROCESSES IN BULGARIAN ENTERPRISES (CONCEPTS AND REALITIES)

  The study presents the use of digital technologies to improve the accuracy, efficiency, and accessibility in the context of the digital transformation of reporting-related processes in enterprises in the Republic of Bulgaria. This transformation includes automating data entry, using advanced analytics, and leveraging artificial intelligence-driven ... The study presents the use of digital technologies to improve the accuracy, efficiency, and accessibility in the context of the digital transformation of reporting-related processes in enterprises in the Republic of Bulgaria. This transformation includes automating data entry, using advanced analytics, and leveraging artificial intelligence-driven tools to optimize workflows. This changes both the way enterprises collect and analyze data and the way they report, which in turn leads to improved decision-making. The aim of the study is to examine the current state of the use of digital technologies in reporting activities of Bulgarian enterprises and the attitudes towards the implementation of new technologies in their reporting activities. The methods of analysis and synthesis, scientific observation, induction, deduction, structured interview, Crosstabs, SWOT Analysis, etc. were used in conducting the study. The strengths, weaknesses, opportunities and threats of digital transformation of processes related to reporting are highlighted. Based on the analysis of the results of structured interviews, the problems in the implementation and use of digital technologies in reporting activities and the attitudes of small, medium and large enterprises in Bulgaria are outlined.