Graph-Based Models for Multi-Tenant Security in Cloud Computing
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Multi-tenant cloud computing scenarios have a high level of security risks because tenants share the same hardware and network. Control of data privacy, access to resources and isolation of these resources pose a significant challenge. Therefore, the security challenges above can be addressed by employing the relatively new and exciting graph-based models that enable a more structured and reasoned representation of the relationships and interactions of tenants, resources, and services. In this paper, graph theory for managing multi-tenant cloud environments has been discussed to improve the security of the cloud environments through the sophisticated control of access, detection of anomalies, and risk assessments. These transformed cloud resources and tenant interaction can be modeled by graphs to build security models that are effective in monitoring risks, detecting pre-identified abnormalities and controlling for them where necessary. Further, the paper presents different graph-based approaches and methods including graph search, community identification and machine learning for anomaly detection for enhancing security of multi-tenanted cloud environments. These models prove to be useful for avoiding cross-tenancy data breaches, framework invasions, and battles for ambitious resources through realistic cases and concrete examples from VM deployment. The work also expresses the limitations of scaling, privacy issues, and compatibility with traditional security models as well as potential research areas considering the combination with AI and blockchain. In conclusion, graph-based models provide a rather sound approach to providing the specific multi-tenant security in the cloud, further developments of which will be crucial to the further improvement of cloud security.
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1. Alam, K., Mostakim, M. A., & Khan, M. S. I. (2017). Design and Optimization of MicroSolar Grid for Off-Grid Rural Communities. Distributed Learning and Broad Applications in Scientific Research, 3.
2. Integrating solar cells into building materials (Building-Integrated Photovoltaics-BIPV) to turn buildings into self-sustaining energy sources. Journal of Artificial Intelligence Research and Applications, 2(2).
3. Agarwal, A. V., & Kumar, S. (2017, November). Unsupervised data responsive based monitoring of fields. In 2017 International Conference on Inventive Computing and Informatics (ICICI) (pp. 184-188). IEEE.
4. Agarwal, A. V., Verma, N., Saha, S., & Kumar, S. (2018). Dynamic Detection and Prevention of Denial of Service and Peer Attacks with IPAddress Processing. Recent Findings in Intelligent Computing Techniques: Proceedings of the 5th ICACNI 2017, Volume 1, 707, 139.
5. Mishra, M. (2017). Reliability-based Life Cycle Management of Corroding Pipelines via Optimization under Uncertainty (Doctoral dissertation).
6. Agarwal, A. V., & Kumar, S. (2017, October). Intelligent multi-level mechanism of secure data handling of vehicular information for post-accident protocols. In 2017 2nd International Conference on Communication and Electronics Systems (ICCES) (pp. 902-906). IEEE.
7. Malhotra, I., Gopinath, S., Janga, K. C., Greenberg, S., Sharma, S. K., & Tarkovsky, R. (2014). Unpredictable nature of tolvaptan in treatment of hypervolemic hyponatremia: case review on role of vaptans. Case reports in endocrinology, 2014(1), 807054.
8. Shakibaie-M, B. (2013). Comparison of the effectiveness of two different bone substitute materials for socket preservation after tooth extraction: a controlled clinical study. International Journal of Periodontics & Restorative Dentistry, 33(2).
9. Gopinath, S., Janga, K. C., Greenberg, S., & Sharma, S. K. (2013). Tolvaptan in the treatment of acute hyponatremia associated with acute kidney injury. Case reports in nephrology, 2013(1), 801575.
10. Shilpa, Lalitha, Prakash, A., & Rao, S. (2009). BFHI in a tertiary care hospital: Does being Baby friendly affect lactation success?. The Indian Journal of Pediatrics, 76, 655-657.
11. Singh, V. K., Mishra, A., Gupta, K. K., Misra, R., & Patel, M. L. (2015). Reduction of microalbuminuria in type-2 diabetes mellitus with angiotensin-converting enzyme inhibitor alone and with cilnidipine. Indian Journal of Nephrology, 25(6), 334-339.
12. Gopinath, S., Giambarberi, L., Patil, S., & Chamberlain, R. S. (2016). Characteristics and survival of patients with eccrine carcinoma: a cohort study. Journal of the American Academy of Dermatology, 75(1), 215-217.
13. Lin, L. I., & Hao, L. I. (2024). The efficacy of niraparib in pediatric recurrent PFA⁃ type ependymoma. Chinese Journal of Contemporary Neurology & Neurosurgery, 24(9), 739.
14. Swarnagowri, B. N., & Gopinath, S. (2013). Ambiguity in diagnosing esthesioneuroblastoma--a case report. Journal of Evolution of Medical and Dental Sciences, 2(43), 8251-8255.
15. Swarnagowri, B. N., & Gopinath, S. (2013). Pelvic Actinomycosis Mimicking Malignancy: A Case Report. tuberculosis, 14, 15.
16. Krishnan, S., Shah, K., Dhillon, G., & Presberg, K. (2016). 1995: FATAL PURPURA FULMINANS AND FULMINANT PSEUDOMONAL SEPSIS. Critical Care Medicine, 44(12), 574.
17. Krishnan, S. K., Khaira, H., & Ganipisetti, V. M. (2014, April). Cannabinoid hyperemesis syndrome-truly an oxymoron!. In JOURNAL OF GENERAL INTERNAL MEDICINE (Vol. 29, pp. S328-S328). 233 SPRING ST, NEW YORK, NY 10013 USA: SPRINGER.
18. Krishnan, S., & Selvarajan, D. (2014). D104 CASE REPORTS: INTERSTITIAL LUNG DISEASE AND PLEURAL DISEASE: Stones Everywhere!. American Journal of Respiratory and Critical Care Medicine, 189, 1.
19. Mahmud, U., Alam, K., Mostakim, M. A., & Khan, M. S. I. (2018). AI-driven micro solar power grid systems for remote communities: Enhancing renewable energy efficiency and reducing carbon emissions. Distributed Learning and Broad Applications in Scientific Research, 4.
20. Nagar, G. (2018). Leveraging Artificial Intelligence to Automate and Enhance Security Operations: Balancing Efficiency and Human Oversight. Valley International Journal Digital Library, 78-94.
21. Agarwal, A. V., Verma, N., Saha, S., & Kumar, S. (2018). Dynamic Detection and Prevention of Denial of Service and Peer Attacks with IPAddress Processing. Recent Findings in Intelligent Computing Techniques: Proceedings of the 5th ICACNI 2017, Volume 1, 707, 139.
22. Mishra, M. (2017). Reliability-based Life Cycle Management of Corroding Pipelines via Optimization under Uncertainty (Doctoral dissertation).
23. Agarwal, A. V., Verma, N., & Kumar, S. (2018). Intelligent Decision Making Real-Time Automated System for Toll Payments. In Proceedings of International Conference on Recent Advancement on Computer and Communication: ICRAC 2017 (pp. 223-232). Springer Singapore
24. Gadde, H. (2019). Integrating AI with Graph Databases for Complex Relationship Analysis. International
25. Gadde, H. (2019). AI-Driven Schema Evolution and Management in Heterogeneous Databases. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 10(1), 332-356.
26. Gadde, H. (2019). Exploring AI-Based Methods for Efficient Database Index Compression. Revista de Inteligencia Artificial en Medicina, 10(1), 397-432.
27. Han, J., Yu, M., Bai, Y., Yu, J., Jin, F., Li, C., ... & Li, L. (2020). Elevated CXorf67 expression in PFA ependymomas suppresses DNA repair and sensitizes to PARP inhibitors. Cancer Cell, 38(6), 844-856.
28. Maddireddy, B. R., & Maddireddy, B. R. (2020). Proactive Cyber Defense: Utilizing AI for Early Threat Detection and Risk Assessment. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 64-83.
29. Maddireddy, B. R., & Maddireddy, B. R. (2020). AI and Big Data: Synergizing to Create Robust Cybersecurity Ecosystems for Future Networks. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 40-63.
30. Damaraju, A. (2020). Social Media as a Cyber Threat Vector: Trends and Preventive Measures. Revista Espanola de Documentacion Cientifica, 14(1), 95-112
31. Chirra, B. R. (2020). Enhancing Cybersecurity Resilience: Federated Learning-Driven Threat Intelligence for Adaptive Defense. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 11(1), 260-280.
32. Chirra, B. R. (2020). Securing Operational Technology: AI-Driven Strategies for Overcoming Cybersecurity Challenges. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 11(1), 281-302.
33. Chirra, B. R. (2020). Advanced Encryption Techniques for Enhancing Security in Smart Grid Communication Systems. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 208-229.
34. Chirra, B. R. (2020). AI-Driven Fraud Detection: Safeguarding Financial Data in Real-Time. Revista de Inteligencia Artificial en Medicina, 11(1), 328-347.
35. Goriparthi, R. G. (2020). AI-Driven Automation of Software Testing and Debugging in Agile Development. Revista de Inteligencia Artificial en Medicina, 11(1), 402-421.
36. Goriparthi, R. G. (2020). Neural Network-Based Predictive Models for Climate Change Impact Assessment. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 11(1), 421-421.
37. Reddy, V. M., & Nalla, L. N. (2020). The Impact of Big Data on Supply Chain Optimization in Ecommerce. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 1-20.
38. Nalla, L. N., & Reddy, V. M. (2020). Comparative Analysis of Modern Database Technologies in Ecommerce Applications. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 21-39.
39. JOSHI, D., SAYED, F., BERI, J., & PAL, R. (2021). An efficient supervised machine learning model approach for forecasting of renewable energy to tackle climate change. Int J Comp Sci Eng Inform Technol Res, 11, 25-32.
40. Joshi, D., Sayed, F., Saraf, A., Sutaria, A., & Karamchandani, S. (2021). Elements of Nature Optimized into Smart Energy Grids using Machine Learning. Design Engineering, 1886-1892.
41. Joshi, D., Parikh, A., Mangla, R., Sayed, F., & Karamchandani, S. H. (2021). AI Based Nose for Trace of Churn in Assessment of Captive Customers. Turkish Online Journal of Qualitative Inquiry, 12(6).
42. Khambati, A. (2021). Innovative Smart Water Management System Using Artificial Intelligence. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(3), 4726-4734.
43. Khambaty, A., Joshi, D., Sayed, F., Pinto, K., & Karamchandani, S. (2022, January). Delve into the Realms with 3D Forms: Visualization System Aid Design in an IOT-Driven World. In Proceedings of International Conference on Wireless Communication: ICWiCom 2021 (pp. 335-343). Singapore: Springer Nature Singapore.
44. Doddipatla, L., Ramadugu, R., Yerram, R. R., & Sharma, T. (2021). Exploring The Role of Biometric Authentication in Modern Payment Solutions. International Journal of Digital Innovation, 2(1).
45. Singu, S. K. (2021). Real-Time Data Integration: Tools, Techniques, and Best Practices. ESP Journal of Engineering & Technology Advancements, 1(1), 158-172.
46. Singu, S. K. (2021). Designing Scalable Data Engineering Pipelines Using Azure and Databricks. ESP Journal of Engineering & Technology Advancements, 1(2), 176-187.
47. Roh, Y. S., Khanna, R., Patel, S. P., Gopinath, S., Williams, K. A., Khanna, R., ... & Kwatra, S. G. (2021). Circulating blood eosinophils as a biomarker for variable clinical presentation and therapeutic response in patients with chronic pruritus of unknown origin. The Journal of Allergy and Clinical Immunology: In Practice, 9(6), 2513-2516
48. Khambaty, A., Joshi, D., Sayed, F., Pinto, K., & Karamchandani, S. (2022, January). Delve into the Realms with 3D Forms: Visualization System Aid Design in an IOT-Driven World. In Proceedings of International Conference on Wireless Communication: ICWiCom 2021 (pp. 335-343). Singapore: Springer Nature Singapore.
49. Maddireddy, B. R., & Maddireddy, B. R. (2021). Evolutionary Algorithms in AI-Driven Cybersecurity Solutions for Adaptive Threat Mitigation. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 17-43.
50. Maddireddy, B. R., & Maddireddy, B. R. (2021). Cyber security Threat Landscape: Predictive Modelling Using Advanced AI Algorithms. Revista Espanola de Documentacion Cientifica, 15(4), 126-153.
51. Maddireddy, B. R., & Maddireddy, B. R. (2021). Enhancing Endpoint Security through Machine Learning and Artificial Intelligence Applications. Revista Espanola de Documentacion Cientifica, 15(4), 154-164.
52. Damaraju, A. (2021). Mobile Cybersecurity Threats and Countermeasures: A Modern Approach. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 17-34.
53. Damaraju, A. (2021). Securing Critical Infrastructure: Advanced Strategies for Resilience and Threat Mitigation in the Digital Age. Revista de Inteligencia Artificial en Medicina, 12(1), 76-111.
54. Chirra, B. R. (2021). AI-Driven Security Audits: Enhancing Continuous Compliance through Machine Learning. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 12(1), 410-433.
55. Chirra, B. R. (2021). Enhancing Cyber Incident Investigations with AI-Driven Forensic Tools. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 157-177.
56. Chirra, B. R. (2021). Intelligent Phishing Mitigation: Leveraging AI for Enhanced Email Security in Corporate Environments. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 178-200.
57. Chirra, B. R. (2021). Leveraging Blockchain for Secure Digital Identity Management: Mitigating Cybersecurity Vulnerabilities. Revista de Inteligencia Artificial en Medicina, 12(1), 462-482.
58. Gadde, H. (2021). AI-Driven Predictive Maintenance in Relational Database Systems. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 12(1), 386-409.
59. Goriparthi, R. G. (2021). Optimizing Supply Chain Logistics Using AI and Machine Learning Algorithms. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 279-298.
60. Goriparthi, R. G. (2021). AI and Machine Learning Approaches to Autonomous Vehicle Route Optimization. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 12(1), 455-479.
61. Nalla, L. N., & Reddy, V. M. (2021). Scalable Data Storage Solutions for High-Volume E-commerce Transactions. International Journal of Advanced Engineering Technologies and Innovations, 1(4), 1-16.
62. Reddy, V. M. (2021). Blockchain Technology in E-commerce: A New Paradigm for Data Integrity and Security. Revista Espanola de Documentacion Cientifica, 15(4), 88-107.
63. Reddy, V. M., & Nalla, L. N. (2021). Harnessing Big Data for Personalization in E-commerce Marketing Strategies. Revista Espanola de Documentacion Cientifica, 15(4), 108-125.
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