Bulut Bilişim Mimarisi ve Güvenliği

Year 2024, Volume: 9 Issue: Issue:1, 62 - 71, 06.06.2024

Kemal Yigit , Faruk Ayata

https://doi.org/10.53070/bbd.1448462

Abstract

Bulut bilişim, depolama, işleme, ağ oluşturma ve yazılım gibi çeşitli hizmetlerin internet üzerinden sunulmasını sağlayan sistemlerdir. Bulut bilişim, ölçeklenebilirlik, esneklik, maliyet verimliliği ve erişilebilirlik avantajları nedeniyle son yıllarda büyük ilgi görmektedir. Ancak bulut bilişim aynı zamanda veri ihlalleri, yetkisiz erişim, hizmet reddi ve kötü niyetli saldırılar gibi önemli güvenlik sorunlarını da beraberinde getirmektedir. Bu nedenle bulut hizmetlerinin ve verilerinin güvenliğinin ve gizliliğinin sağlanması hem bulut sağlayıcıları hem de kullanıcılar için çok önemli bir konu haline gelmektedir.
Bu çalışmada yapay zekanın bulut bilişim güvenliğinde kullanımına ilişkin çalışmalar incelenmektedir. Öncelikle bulut bilişimin ve yapay zekanın temel kavramlarını ve modellerini tanıtılmaktadır, ardından bulut bilişimdeki temel güvenlik zorluklarını ve gereksinimlerini incelenmektedir. Daha sonra, makine öğrenimi, derin öğrenme, doğal dil işleme, bilgisayar görüşü ve uzman sistemler gibi bulut bilişimdeki güvenlik sorunlarını çözebilecek mevcut yapay zekâ tekniklerini ve yöntemlerini incelenmektedir.

Keywords

Bulut Bilişim, Yapay Zeka, Bulut Bilişim Güvenliği, Makine Öğrenmesi

Cloud Computing Architecture and Security

Abstract

Cloud computing is systems that provide various services such as storage, processing, networking and software over the internet. Cloud computing has attracted great attention in recent years due to its scalability, flexibility, cost efficiency and accessibility advantages. However, cloud computing also brings with it significant security problems such as data breaches, unauthorized access, denial of service and malicious attacks. Therefore, ensuring the security and privacy of cloud services and data becomes a very important issue for both cloud providers and users.
In this study, studies on the use of artificial intelligence in cloud computing security are examined. First, the basic concepts and models of cloud computing and artificial intelligence are introduced, and then the main security challenges and requirements in cloud computing are examined. Then, existing artificial intelligence techniques and methods that can solve security problems in cloud computing, such as machine learning, deep learning, natural language processing, computer vision and expert systems, are examined.

Keywords

Cloud Computing, Artificial Intelligence, Cloud Computing Security, Machine Learning

References

• Abiodun M. K., Chioma U., Imoize A. L., Awotunde J. B., Lee C.-C., Adeniyi A. E., Li C.-T. (2023). Analysis of a Double-stage Encryption Scheme Using Hybrid Cryptography to Enhance Data Security in Cloud Computing Systems. Journal of Library and Information Studies.
• Aboukadri S., Ouaddah A., Mezrioui A. (2024). Machine learning in identity and access management systems: Survey and deep dive. Computers Security.
• Almorsy M., Grundy, J., Müller I. (2016). An Analysis of the Cloud Computing Security Problem. Communication Technologies.
• Alrasheed S. H., Aied alhariri M., Adubaykhi S. A., El Khediri S. (2022). Cloud Computing Security and Challenges: Issues, Threats, and Solutions. In 2022 5th Conference on Cloud and Internet of Things.
• Amalarethinam D. I. G., Rajakumari S. E. J. (2019). A Survey on Security Challenges in Cloud Computing. Journal of Physical Sciences.
• Amara N., Huang Z., Ali A. (2017). Cloud Computing Security Threats and Attacks with Their Mitigation Techniques. In 2017 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery.
• Amira A., Derhab A., Karbab E. B., Nouali O. (2024). A Survey of Malware Analysis Using Community Detection Algorithms. ACM Computing Surveys.
• Bohn R. B., Messina J., Liu F., Tong J. (2011). NIST Cloud Computing Reference Architecture. In 2011 IEEE World Congress on Services.
• Bouayad A., Blilat A., Mejhed N. E. H., El Ghazi M. (2012). Cloud computing: Security challenges. In 2012 Colloquium in Information Science and Technology.
• Dawood M., Tu S., Xiao C., Alasmary H., Waqas M., Rehman S. U. (2023). Cyberattacks and Security of Cloud Computing: A Complete Guideline. Symmetry, November 2023.
• Du J. (2022). Analysis of a Joint Data Security Architecture Integrating Artificial Intelligence and Cloud Computing in the Era of Big Data. In 2022 4th International Conference on Smart Systems and Inventive Technology.
• Dwivedi R. K., Saran M., Kumar R. (2019). A Survey on Security over Sensor-Cloud. Başlık. 2019 9th International Conference on Cloud Computing, Data Science Engineering (Confluence).
• Guo J., Lei Z. (2011). A kind of wormhole attack defense strategy of WSN based on neighbor nodes verification. 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN).
• Hasimi L., Zavantis D., Shakshuki E., Yasar A. (2024). Cloud Computing Security and Deep Learning: An ANN approach. Procedia Computer Science.
• Isharufe W., Jaafar F., Butakov S. (2020). Study of Security Issues in Platform-as-a-Service (PaaS) Cloud Model. In 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE).
• Jangjou, M., Sohrabi, M. K. (2022). A Comprehensive Survey on Security Challenges in Different Network Layers in Cloud Computing. Archives of Computational Methods in Engineering: State of the Art Reviews.
• Khorshed M. T., Ali A. B. M. S., Wasimi S. A. (2012). A survey on gaps, threat remediation challenges and some thoughts for proactive attack detection in cloud computing. Future Generation Computer Systems - The International Journal of Grid Computing and eScience.
• Krishna B. H., Kiran S., Murali G., Reddy R. P. K. (2016). Security Issues in Service Model of Cloud Computing Environment. Procedia Computer Science.
• Kumar A., Bhardwaj A., Singh A. (2023). A Review of Data Security in Cloud Computing. In 2023 14th International Conference on Computing Communication and Networking Technologies.
• Kumar M. (2016). An Incorporation of Artificial Intelligence Capabilities in Cloud Computing. International Journal Of Engineering And Computer Science.
• Kumari S., Solanki K., Dalal S., Dhankhar A. (2022). Analysis Of Cloud Computing Security Threats and Countermeasures. In 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions).
• Liu B., Xu E., Wang J., Wei Z., Xu L. Z., Zhao B., Su J. (2011). Thwarting audio steganography attacks in cloud storage systems. In 2011 International Conference on Cloud and Service Computing.
• Luo S., Lin Z., Chen X., Yang Z., Chen J. (2011). Virtualization Security for Cloud Computing Service. 2011 International Conference on Cloud and Service Computing.
• Malik T. S., Siddiqui M. N., Mateen M., Malik K. R., Sun S., Wen J. (2022). Comparison of Blackhole and Wormhole Attacks in CloudMANET Enabled IoT for Agricultural Field Monitoring. SECURITY AND COMMUNICATION NETWORKS.
• Mell P., Grance T. (2010). The NIST Definition of Cloud Computing. Communications of the ACM.
• Mohammed S., Fang W. C., Ramos C. (2023). Special issue on ‘‘artificial intelligence in cloud computing’’. Computing.
• Patel A.,Taghavi M., Bakhtiyari K., J Joaquim. (2012). An Intrusion Detection And Prevention System In Cloud Computing: A Systematic Review. Journal of Network and Computer Applications. 36. 10.1016/j.jnca.2012.08.007.
• Popli M., Gagandeep. (2019). A Survey on Cloud Security Issues and Challenges. In 2019 6th International Conference on Computing for Sustainable Global Development.
• Raghav; Andola N.; Verma K.; Venkatesan S.; Verma Ş. (2023). Multi-Keyword Searchable and Verifiable Attribute-Based Encryption Over Cloud Data. IEEE Transactions on Cloud Computing.
• Ramanathan S., Goel S., Alagumalai S. (2011). Comparison of Cloud database: Amazon's SimpleDB and Google's Bigtable. In 2011 International Conference on Recent Trends in Information Systems.
• Sikarwar S., Jeyanthi N., Thandeeswaran R., Mcheick H. (2024). SDS-IAM: Secure Data Storage with Identity and Access Management in Blockchain. International Journal of Performability Engineering.
• Singh A. (2022). Blockchain Implication for Cloud Computing Security in the Digital Era. Pranjana: The Journal of Management Awareness.
• Singh A., Battra J. (2023). Strategies for Data Backup and Recovery in the Cloud. International Journal of Performability Engineering.
• Surya L. (2018). Streamlining Cloud Application with AI Technology. International Journal of Innovations in Engineering Research and Technology.
• Tadeo D. A. G., John S. F., Bhaumik A., Neware R., Yamsani N., Kapila D. (2021). Empirical Analysis of Security Enabled Cloud Computing Strategy Using Artificial Intelligence. In 2021 International Conference on Computing Sciences.
• Teegala S. P., Vijai C., Nagpal A., Anuradha R., Aljbori A., Swathi B. (2023). Enhanced Authentication Methods for Access and Control Management in Cloud Computing. 10th IEEE Uttar Pradesh Section International Conference on Electrical.
• Thatte G., Mitra U., Heidemann J. (2011). Parametric Methods for Anomaly Detection in Aggregate Traffic. IEEE/ACM Transactions on Networking, 2011.
• Vasiljeva T., Shaikhulina S., Kreslins K. (2017). Cloud Computing: Business Perspectives, Benefits and Challenges for Small and Medium Enterprises (Case of Latvia). Procedia Engineering.
• Yan Q., Yu F. R. (2015). Distributed denial of service attacks in software-defined networking with cloud computing. IEEE Communications Magazine.
• Zawaideh F. H., Ghanem W. A. H. M., Yusoff M. H., Saany S. I. A., Jusoh J. A., El-Ebiary Y. A. B. (2022). The Layers of Cloud Computing Infrastructure and Security Attacking Issues. Journal of Pharmaceutical Negative Results, Special Issue.
• Zhou Y., Zhao G., Alroobaea R., Baqasah A. M., Miglani R. (2022). Research on data mining method of network security situation awareness based on cloud computing. Journal of Intelligent Systems.