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Space-Based Cyber Threats: Mitigation Strategies and Future Directions
Abstract
As space-based technologies continue to evolve and play an increasingly critical role in various sectors, the risk of cyber threats targeting space-based assets and infrastructure becomes more significant. This paper explores the emerging landscape of space-based cyber threats, identifies key vulnerabilities, and proposes mitigation strategies to safeguard space systems. Through a comprehensive analysis of current threats and challenges, this paper aims to provide insights into the future directions of space-based cybersecurity.
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The processes involved in the supply chain are expected to undergo a radical transformation because of digitalization, which makes use of the technical capabilities of applications for advanced technology. The greater effect of digital technology's use has been largely disregarded owing to a dearth of data pertinent to the topic. This is true even though the technology's advantages to operations are clear. This paper analyses how Char GPT and AI may be used together to increase operational performance, promote sustainable development, and earn money from data that has been acquired. The examples utilized in this study are from the supply chain sector. This project's objective was to conduct an experimental investigation of the tuna fish supply chain in the USA to identify essential end-to-end operations, investigate material and data handling methods, and consider the potential use of artificial intelligence and Chat GPT. Artificial intelligence has the potential to assist in making choices that are data-driven for a wide variety of business problems. Nevertheless, suppose there are problems with the flow of data and information across a supply chain. In that case, the value of AI algorithms may be limited since these algorithms depend on input that is accurate, trustworthy, and timely. Chat GPT can ensure the transparency, accountability, and traceability of such flows because of its potential to act as a hub for the administration and transmission of data and information emanating from a number of sources. The combination of artificial intelligence and chatbots has the potential to assist supply chains in moving beyond the limitations of currently available technology. Then, we can promote operational improvements and implement a dynamic decision-making process by leveraging the complementary effects of these digital technologies. This will allow us to reap the triple-helix sustainability benefits of reducing resource overexploitation, combating fraud, eliminating product recalls, and promoting gender and cultural equality. In the end, the ability to save money and generate more income thanks to data-driven decision-making is a significant boon to the process of monetizing data.
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Cloud computing technology has become a crucial component of IT services utilized in daily living in this era of technology. Website hosting services are gradually migrating to cloud in this regard. This increases the value of cloud-based websites while also creating new risks for those services. A severe threat of this nature is DDoS attack. This research propose novel technique in cloud based DDOS attacks using machine learning architectures. here the input has been collected based on cloud module and it has been processed for dimensionality reduction and noise removal. Then this data feature has been extracted and classified using ResNet-101 based KELM. The experimental analysis has been carried out in terms of data delivery ratio, transmission rate, validation accuracy, training accuracy, end-end delay. the proposed technique attained data delivery ratio of 92%, transaction rate of 82%, validation accuracy of 89%, training accuracy of 96%, end-end delay of 56%