Academic literature on the topic 'International Journal of Computer Science and Information Security (IJCSIS)'

Throughout the previous few years, Computer systems were principally utilized by association for correspondence between various divisions. Under these conditions security was not a significant concern and it didnt get part of consideration. Be that as it may, presently, there is an extraordinary effect of between organize job in every single residents life, from Banking – Hospitals Education Transportation and so forth. However, presently arrange has sprouted different security concerns. In any case, presently with the expanding utilization of Computer in everyday action there is a serious requirement for robotized devices for securing touchy information and data put away on the Computer. Especially for the situation for a mutual framework, for example, time sharing framework and where the need is significantly increasingly intense for frameworks that is available for an open phone or an information organize. The standard name for the assortment of devices to ensure information and to forestall Hackers is Computer Security . This proposition talk about and depicts spoofing , which is if an aggressor can tune in for a customers ask for and imitate an answer before the genuine location server can, at that point the customer will utilize the data gave by the hacker. This is known as spoofing. Siddiqui Sana Afreen "Analytical Study on Network Security Breach’s" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30403.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/30403/analytical-study-on-network-security-breach%E2%80%99s/siddiqui-sana-afreen

<strong>Abstract</strong><strong>:</strong> In this research, we presented an explanation of the definition of cybersecurity, its importance, and its types. We also explained the difference between information security and cybersecurity, as well as the importance of both. we also mentioned how cyber security is important in the education sector and the Role of training and education in enhancing Cybersecurity. <strong>Keywords:</strong> cybersecurity, information security, education sector. <strong>Title:</strong> Cybersecurity In Education <strong>Author:</strong> Jumanah Hasan AlSanad <strong>International Journal of Computer Science and Information Technology Research</strong> <strong>ISSN 2348-1196 (print), ISSN 2348-120X (online)</strong> <strong>Vol. 12, Issue 2, April 2024 - June 2024</strong> <strong>Page No: 51-61</strong> <strong>Research Publish Journals</strong> <strong>Website: www.researchpublish.com</strong> <strong>Published Date: 27-June-2024</strong> <strong>DOI: https://doi.org/10.5281/zenodo.12566761</strong> <strong>Paper Download Link (Source)</strong> <strong>https://www.researchpublish.com/papers/cybersecurity-in-education</strong>

The digital transformation of healthcare has brought about unprecedented advancements, but it has also introduced significant cybersecurity risks. Cyberattacks targeting sensitive patient data, employee information, and critical operational systems are on the rise, demanding innovative and robust security measures. Enter the powerful duo of Artificial Intelligence (AI) and Machine Learning (ML). These cutting-edge technologies offer a powerful arsenal against these cyber threats. AI algorithms can analyse massive datasets from various sources, such as network traffic, user behaviour, and medical device logs, to identify anomalies and detect malicious activity in real-time. This proactive approach allows security teams to swiftly respond to threats, minimizing the impact of cyberattacks and protecting patient safety. Furthermore, AI can leverage threat intelligence from diverse sources, including cybersecurity feeds, social media, and dark web forums, to proactively identify and mitigate emerging threats. This proactive approach empowers healthcare organizations to stay ahead of the curve, anticipating and neutralizing cyberattacks before they can cause significant damage. However, challenges remain. Implementing and maintaining AI/ML-based security solutions requires significant investment, both in terms of infrastructure and skilled personnel. Concerns surrounding data privacy and the potential for algorithmic bias also need careful consideration. Despite these challenges, the potential benefits of AI and ML in healthcare cybersecurity are undeniable. By embracing these technologies, healthcare organizations can enhance patient safety, improve operational efficiency, and build a more secure and resilient future in the face of evolving cyber threats. References Aarav, M., &amp; Layla, R. (2019). Cybersecurity in the cloud era: Integrating AI, firewalls, and engineering for robust protection. International Journal of Trend in Scientific Research and Development, 3(4), 1892-1899. Abie, H. (2019, May). Cognitive cybersecurity for CPS-IoT enabled healthcare ecosystems. In 2019 13th International Symposium on Medical Information and Communication Technology (ISMICT) (pp. 1-6). IEEE. Aitazaz, F. (2018). Fortifying technology: Computer science solutions for cyber-attacks and cloud security. Alabdulatif, A., Khalil, I., &amp; Saidur Rahman, M. (2020). Security of blockchain and AI-empowered smart healthcare: Application-based analysis. Applied Sciences, 12(21), 11039. Alizai, S. H., Asif, M., &amp; Rind, Z. K. (2021). Relevance of Motivational Theories and Firm Health. Management (IJM), 12(3), 1130-1137. Asif, M. (2021). Contingent Effect of Conflict Management towards Psychological Capital and Employees’ Engagement in Financial Sector of Islamabad. Preston University, Kohat, Islamabad Campus. Bellamkonda, S. (2020). Cybersecurity in critical infrastructure: Protecting the foundations of modern society. International Journal of Communication Networks and Information Security, 12, 273-280. Bibi, P. (2020). AI-powered cybersecurity: Advanced database technologies for robust data protection. Chintala, S. (2020). Data privacy and security challenges in AI-driven healthcare systems in India. Journal of Data Acquisition and Processing, 37(5), 2769-2778. Chirra, D. R. (2021). Mitigating ransomware in healthcare: A cybersecurity framework for critical data protection. Revista de Inteligencia Artificial en Medicina, 12(1), 495-513. Chirra, D. R. (2021). Secure edge computing for IoT systems: AI-powered strategies for data integrity and privacy. Revista de Inteligencia Artificial en Medicina, 13(1), 485-507. Cooper, M. (2020). AI-driven early threat detection: Strengthening cybersecurity ecosystems with proactive cyber defense strategies. Elijah Roy, R. (2021). Harnessing AI and machine learning for enhanced security in cloud infrastructures. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 14-28. Fatima, S. (2020). Fortifying the future: Advanced cybersecurity tactics for cloud platforms and device security. Hussain, A. H., Hasan, M. N., Prince, N. U., Islam, M. M., Islam, S., &amp; Hasan, S. K. (2021). Enhancing cyber security using quantum computing and artificial intelligence: A. Hussain, Z., &amp; Khan, S. (2021). AI and cloud security synergies: Building resilient information and network security circulation ecosystems. IBRAHIM, A. (2019). AI armory: Empowering cybersecurity through machine learning. Jimmy, F. (2021). Emerging threats: The latest cybersecurity risks and the role of artificial intelligence in enhancing cybersecurity defenses. Valley International Journal Digital Library, 564-574. Kasula, B. Y. (2017). Machine learning unleashed: Innovations, applications, and impact across industries. International Transactions in Artificial Intelligence, 1(1), 1-7. Maddireddy, B. R., &amp; Maddireddy, B. R. (2021). Enhancing endpoint security through machine learning and artificial intelligence applications. Revista Espanola de Documentacion Cientifica, 15(4), 154-164. Nimmagadda, V. S. P. (2021). Artificial intelligence and block chain integration for enhanced security in insurance: Techniques, models, and real-world applications. African Journal of Artificial Intelligence and Sustainable Development, 1(2), 187-224. Raza, H. (2021). Proactive cyber defense with AI: Enhancing risk assessment and threat detection in cybersecurity ecosystems. Reddy, A. R. P. (2021). The role of artificial intelligence in proactive cyber threat detection in cloud environments. Neuro Quantology, 19(12), 764-773. Shah, V. (2021). Machine learning algorithms for cybersecurity: Detecting and preventing threats. Revista Espanola de Documentacion Cientifica, 15(4), 42-66. Shukla, A. (2021). Leveraging AI and ML for advance cyber security. Journal of Artificial Intelligence &amp; Cloud Computing. SRC/JAICC-154. DOI: doi.org/10.47363/JAICC/2021 (1), 142, 2-3. Waqas, M., Tu, S., Halim, Z., Rehman, S. U., Abbas, G., &amp; Abbas, Z. H. (2020). The role of artificial intelligence and machine learning in wireless networks security: Principle, practice and challenges. Artificial Intelligence Review, 55(7), 5215-5261. Zygun, D. (2020). Cyber-attack resilience: Fortifying devices and cloud systems with computer science innovations.

Today, with the expansion of semantic web services, the need for search engines to utilize conceptual networks and domain ontologies for logical inference and reasoning from user queries, as well as for optimal (accurate and relevant) retrieval, is increasing. This applied research aims to analyze the structure of the conceptual network in the field of information security, and its domain structure was discovered through combined methods of co-occurrence analysis of keywords and social network analysis. The statistical population of this study consists of 10,227 scientific documents in the field of information security, including books, journal articles, and conference papers at the international level, sourced from the Scopus and Web of Science databases during the years 2013-2017. For preprocessing keywords and tags, the Zotero software was used, while Excel was employed to match them with information security and computer science vocabularies. For visualization and analysis of thematic networks, VosViewer and Gephi were utilized.&nbsp; By examining 19,648 keywords and tags, 207 keywords were extracted based on the latest version of the information security vocabulary. The findings of the study revealed that this network consists of 14 clusters: 5 mature clusters, 7 semi-mature clusters, and 2 immature clusters, indicating that the conceptual network in the field of information security has good coherence and density. The concepts of "security," "information security," "information systems," "privacy," "information," "telecommunications," "cryptography," "encryption," "authentication," "cybersecurity," "network," "cloud computing," "security attacks," "access control," "intrusion detection systems," "security protocols," "risk," "risk management and its frameworks," and "access level agreements" are among the most important concepts in this network, possessing the highest betweenness centrality. The nature of their interconnections and internal links is direct.