Long-Term Strategy for Smart Cities Governance Projects across Europe
In the context of our rapidly evolving word, where pressing issues like anthropogenic climate change and accelerating urbanization demand innovative solutions, a critical evaluation of the potential and impact of digital technologies is necessary. Climate-neutral governance entails the implementation of governmental instruments and tools designed and used to harmonize short-term policy actions with a long-term vision of achieving a climate-neutral state. This fact aims to facilitate evidence-based decision-making, foster inter-sectoral coordination, enhance transparency, and cultivate public legitimacy for climate mitigation and adaptation measures. This paper presents a focused analysis of SmartCities projects and their implementation across diverse urban centers and nations. Our objective is to provide a comprehensive overview, highlighting recent advancements in the realm of smart and climate-neutral city governance. Furthermore, we conduct a comprehensive inquiry into Romania's legislative framework, encompassing the regulations and strategies pertaining to energy, climate change, and urban development. This analysis is complemented by an exploration of the evolving perspectives and legislative proposals that are likely to shape the future course of action in these domains.
Keywords: Smart Cities, Governance, Digital Twin, Long Term Strategy  (LTS), Europe LTS, Romania LTS

Overview of Security Information and Event Management Systems
Organizations face continuous risks of cybersecurity breaches and malicious activities. Reviewing logs is a critical activity to identify these threats, but the large volume of systems and data often presents an insurmountable challenge. As IT infrastructures expand, logs multiply exponentially, making the traditional manual log analysis extremely difficult and prone to missing key events. Also, this high volume of information combined with the uncorrelation of logs makes traditional approaches ineffective, especially in detecting sophisticated attacks. The solution to this challenge is deploying a Security Information and Event Management (SIEM) system, who collects, correlates, and analyze disparate logs from various sources in real-time, offering a complete overview of the organization's security. By automating the log review and providing detailed information, SIEM not only resolves the problem of log overload but also significantly improves threat detection and incident re-sponse capabilities. This paper presents the overview of SIEM systems and highlights the ways in which they can overcome these issues.
Keywords: SIEM, Security Event Management, Cybersecurity, Information Security, Security Logs analysis

Empowering Local Image Generation: Harnessing Stable Diffusion for Machine Learning and AI
Ahmed Imran KABIR, Limon MAHOMUD, Abdullah Al FAHAD, Ridwan AHMED 25
This paper examines the ability to use Stable Diffusion's diffusion models to get state-of-the-art synthesis results on image data and other types of data. Also, a guiding interface can be used to control the process of making images by converting text to images and image to image. But because these models usually work directly in pixel space, optimizing strong DMs often needs more GPU VRAM to run. Using Stable Diffusion and diffusion models on local hardware like this lets more information and depth be added while generating images, which greatly improves the quality detail of the image. By combining diffusion models to model architecture, I have made diffusion models into powerful and flexible producers for general conditioning inputs, such as when using XL-XDXL 1.0 and LoRA models. Overall, the paper highlights how a normal person can run their own Midjourney like AI image generation with the help of machine learning and generative AI.
Keywords: Stable Diffusion, Machine Learning, Image generation, generative AI, VRAM, GPU, Diffusion Models, Prompt

Unveiling the Evolutionary Impact of Artificial Intelligence on the Workforce
Muhammed MIAH 39
Artificial Intelligence (AI) is poised to transform industries, reshaping the workforce and societal structures. This research article explores AI's implications, economic impact, industry influence, job creation, job displacement, and ethical considerations. AI revolutionizes operations across diverse sectors, from IT and finance to healthcare and transportation. It enhances processes, security measures, customer engagement, and efficiencies, reshaping the key industries. However, certain sectors like the Chemical and Natural Resources, Fashion, Food, Education, Creative, and Personal Services industries appear less susceptible to AI disruption due to their reliance on human creativity, personalized interactions, and specialized expertise. The article also discusses the future of AI and provides recommendations on how the workers and companies can prepare for AI.
Keywords: Artificial Intelligence, AI, Impact, Workforce

The Use of Artificial Intelligence for Qualitative Data Analysis: ChatGPT
Ion-Dănut LIXANDRU 57
This paper thoroughly investigates the profound and complex impact of tools such as ChatGPT in the analysis of qualitative data. Using a comparative analysis starting from the data obtained in a previous study, the paper highlights the relevance of employing generative artificial intelligence in research. ChatGPT 3.5 was utilized in the analysis process, and the data were extracted from a focus group involving 8 respondents. The conclusions emphasize a significant similarity in data analysis, supporting the idea that artificial intelligence can play a trustworthy role in interpreting qualitative information. The generative artificial intelligence's synthesis capability becomes fundamental, facilitating the efficient handling of complex texts for researchers and analysts. ChatGPT accelerates the analysis process, providing results in a much shorter timeframe compared to traditional methods, an essential characteristic in the current academic and research context.
Keywords: Generative Artificial Intelligence, Qualitative Research, ChatGPT

IoT Security for D-App in Supply Chain Management
Teodor CERVINSKI, Cristian TOMA 68
The fast advance and evolution of technology in Internet of Things (IoT) is a double-edged sword, striking with new performant solutions and backfiring with a lot of unanswered questions. Due to cheap manufacturing costs and large-scale production, sensors, actuators and even microcontrollers are not designed with security on the first place. Also, the IoT market is a new one and that means that it is still unregulated and there isn’t a well-defined set of standards to control and manage better these problems. The IoT ascent has impacted many industries, but probably the most changes were made to the Supply Chain Management (SCM) industry. The forementioned question of cheap devices that need to be manufactured with a minimum of costs, very fast and ready to be deployed, is digging a big security hole in this kind of ecosystems. This paper aims to discuss the challenges involved in hardening de security in embedded devices, protecting the data and the communication channels between an IoT node and an IoT gateway and finally, assuring the persistence of data and its security after is stored. All these matters are addressed with privacy and security in design. Because SCM is a multi-party ecosystem that involves many different actors each with its tasks and data handling components, it is important to assure the fact that they will not interfere, tamper, or profit in a bad manner of each other. One solution for this problem is decentralization that comes with strings attached. Finally, and on short, this paper will try to describe a security model based on decentralization in a SCM flow, addressing its threats and how they can be overcome.
Keywords: IoT, Blockchain, Security, Cryptography, Decentralization, Supply Chain Management

The 23rd International Conference on Informatics in Economy, IE 2024 78

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INFOREC Association 81

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