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BULUT BİLİŞİM ORTAMINDAKİ YBS İÇİN SALDIRI TESPİT VE ÖNLEME SİSTEMLERİ ÜZERİNDE BİR DEĞERLENDİRME

Year 2020, Volume: 6 Issue: 2, 1 - 28, 30.12.2020

Abstract

Bulut bilişim (CC), talep üzerine kaynakları paylaşmak için ağ erişimine izin veren ve Yönetim Bilgi Sistemleri (YBS) tarafından uzaktan kullanılan çeşitli veri ve bilgilerin hesaplanması ve depolanması için kolaylık sağlayan bir hizmet modelidir. Bununla birlikte, güvenlik ve mahremiyet ile ilgili endişeler, kuruluşlar tarafından yaygın olarak benimsenmesinin önündeki başlıca engellerdir. Saldırı Tespit Sistemleri (IDS) ve Saldırı Önleme Sistemleri (IPS), genel olarak BT ve YBS güvenlik ve uyumluluk alıştırması için çeşitli tür tehditlerden veya saldırılardan elde edilebilen bulut kaynaklarını ve hizmetlerini kurtarabilen önemli araçlardır. Türkiye'de, TC Cumhurbaşkanlığı Dijital Ofisi tarafından devlet daireleri için bulut altyapısının kullanılması, doğrulanmış ulusal çözümler hariç olmak üzere 2019 yılından itibaren yasaklanmıştır. Bu araştırmanın amacı, en son bulut bilişim sistemlerinde teknolojik yenilik bakış açısını sunmak ve IDS'nin CC ortamında güvenlik fonksiyonları açısından performansının değerlendirilmesini sağlamaktır. Ayrıca, CC ortamında yer alan işletmeler, kurumlar ve BT şirketleri için önemli güvenlik risklerine karşı makul önlemler geliştirmeye çalışıyoruz.

References

  • Alharkan T. and Martin P., (2012), “IDSaaS: Intrusion Detection System as a Service in Public Clouds,” Proceedings of the 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 686-687.
  • Al-Shdaifat B., Alsharafat W.S. and El-bashir M., (2015), “Applying Hopfield Artificial Network and Simulating Annealing for Cloud Intrusion Detection,” Journal of Information Security Research ,vol. 6, pp.49-53. Ambikavathi C. and Srivatsa S.K., (2015), “Improving virtual machine security through intelligent intrusion detection system,” Indian Journal of Computer Science and Engineering (IJCSE), vol. 6, , pp.39.
  • CloudControls, Cloud Control Framework (Controls, Risks and Customer Questions), Cloud Controls Project, Netherlands, (online) (last accessed on 7th March, 2014).
  • Cooper S., (2019) “Best Intrusion Detection Systems (10+ IDS Tools Reviewed)” VPN News, [Online]. February 27, https://www.comparitech.com/net-admin/network-intrusion-detection-tools/
  • CSA, Security Guidance, v3, Cloud Security Alliance, November 2011.
  • CSA, Cloud Controls Matrix, v1.4, Cloud Security Alliance, March 2013.
  • EC, European Commission, Report, (2012), “Unleashing the Potential of Cloud Computing in Europe” [Online]. 27 oct., https://www.pdpjournals.com/docs/88053.pdf
  • Ghosh P., Mandal A.K. and Kumar R., (2015), “An Efficient Network Intrusion Detection System,” Chapter Information Systems Design and Intelligent Applications, vol. 339 of the series Advances in Intelligent Systems and Computing, pp91-99.
  • Gupta S. and Kumar P., (2015), “Immediate System Call Sequence Based Approach for Detecting Malicious Program Executions in Cloud Environment,” Wireless Personal Communications, vol. 81, pp.405-425.
  • Kaliyamurthie K. P., Suresh R. M., (2012) “Artificial Intelligence Technique Applied to Intrusion Detection”, International Journal of Computer Science and Telecommunications, Vol. 3, No. 4, pp. 20- 25.
  • Kaspersky (August 4, 2015) “DDoS Intelligence Report Q2 2015”, By Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-q1& q2-2015/71663/
  • Kaspersky , (April 28, 2016), “DDoS Intelligence Report for Q1 2016”, Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-for-q1-2016/74550/
  • Kaspersky, ( November 3, 2015) “DDoS Intelligence Report Q3 2015”, By Kaspersky Lab [Online]., https://securelist.com/kaspersky-ddos-intelligence-report-q3-2015/72560/ Kaspersky, (August 1, 2016), “DDoS Intelligence Report for Q2 2016”, Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-for-q2-2016/75513/
  • Kaspersky, (January 28, 2016), “DDoS Intelligence Report for Q4 2015”, By Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-for-q4-2015/73414/
  • Kene S.G., Theng D.P., (2015), “A review on intrusion detection techniques for cloud computing and security challenges,” IEEE 2nd International Conference on Electronics and Communication Systems (ICECS), 2015, pp.227-323.
  • Khaldi A., Karoui K. and Ghezala H. B., (2014), “Framework to detect and repair distributed intrusions based on mobile agent in hybrid cloud,” Inter. Conf. Par. and Dist. Proc. Tech. and Appl. (PDPTA'14), pp.471-476.
  • Khaldi A., Karoui K. and Ghezala H. Ben, (2014) “Framework to detect and repair distributed intrusions based on mobile agent in hybrid cloud,” Inter. Conf. Par. and Dist. Proc. Tech. and Appl. (PDPTA'14), pp.471-476.
  • Khalimonenko A, Kupreev O, (2017), “DDOS attacks in Q1 2017” [Online]., https://securelist.com/ddos-attacks-in-q12017/78285/
  • Khalimonenko A, Kupreev O, Ilganaev K (2018) “DDoS attacks in Q4 2017” [Online]., Feb 6, https://securelist.com/ddos-attacks-in-q4-2017/83729
  • Khalimonenko A, Kupreev O, Ilganaev K (2017) “DDoS attacks in Q3 2017”, [Online]. November 6,, , https://securelist.com/ddos-attacks-in-q3-2017/83041/
  • Khalimonenko A, Strohschneider J, Kupreev O, (2017), “DDoS attacks in Q4 2016” [Online]. February 2, https://securelist.com/ddos-attacks-in-q4-2016/77412/
  • Khatri J.K., Khilari G., (2015), “Advancement in Virtualization Based Intrusion Detection System in Cloud Environment,” International Journal of Science, Engineering and Technology Research (IJSETR), vol. 4, pp.1510-1514.
  • Kolahi .S, K, Sarrafpour. B. (2015 ), “Analysis of UDP DDoS Flood Cyber Attack and Defense Machanics on Web Service with Linux Ubuntu 13”. New Zealand, 978-1-4799-6532-8/15: Department of computing Unitec Institute of Technology. Auckland, IEEE.
  • Kupreev O, Strohschneider J, Khalimonenko A. Kaspersky, (2016) “DDOS intelligence report for Q3 2016” [Online]. October 31,,https://securelist.com/kaspersky-ddos-intelligence-report-for-q3-2016/76464/
  • Madhavi, M. (2012), "An Approach For Intrusion Detection System In Cloud Computing", International Journal of Computer Science and Information Technologies, 3(5), 5219–5222. 2012
  • Manthira S.M. and Rajeswari M., (2014), “Virtual Host based Intrusion Detection System for Cloud,” International Journal of Engineering and Technology (IJET), vol. 5, pp. 5023- 5029.
  • Messier R., (2014) “Collaboration with cloud computing security, social Media, and Unified communications” Elsevier.
  • Modi C.N, D. Patel, (2013), “A novel Hybrid-Network Intrusion Detection System (H-NIDS) in Cloud Computing,” IEEE Symposium on Computational Intelligence in Cyber Security (CICS), pp. 23-30.
  • Modi C.N. and Patel D., (2013), “A novel Hybrid-Network Intrusion Detection System (H-NIDS) in Cloud. Computing,” IEEE Symposium on Computational Intelligence in Cyber Security(CICS), pp. 23-30.
  • Modi C.N., Patel D.R., Patel A. and Rajarajan M., (2012 ), “Integrating signature A priori based network intrusion detection system (NIDS) in cloud computing,” 2nd International Conference on Communication, Computing and Security, pp.905–912.
  • Muthukumar B. B. and Rajendran P.K., (2015 ), “Intelligent Intrusion Detection System for Private Cloud Environment,” Communications in Computer and Information Science , vol. 536, pp.54-65.
  • NIST, Guidelines on Security and Privacy in Public Cloud Computing, National Institute of Standards and Technology, Draft Special Publication 800-144, USA.
  • Pandeeswari N. and Kumar G., (2015), “Anomaly Detection System in Cloud Environment Using Fuzzy Clustering Based ANN,” Mobile Networks and Applications, pp.1-12.
  • Patel A., Taghavi M., Bakhtiyari K., Junior J.C., (2013 ), “An Intrusion Detection and Prevention System in Cloud Computing: A Systematic Overview,” Journal of Network and Computer Applications, vol. 36, pp.25–41.
  • Peng T, Leckie C, Ramamohanarao K. (2006), “Survey of Network-based Defense Mechanisms Countering the DoS and DDoS Problems.” ACM Transactions on Computational Logic ,1-0.
  • Robinson T., (2015), “Series of DDoS Attacks plague linode data centers, infrastructure”. SC Magazine.
  • Sangeetha S., Devi B.G., Ramya R., Dharani M.K. and Sathya P., (2015), “Signature Based Semantic Intrusion Detection System on Cloud,” Chapter 66 of the book “Information Systems Design and Intelligent Applications”, vol. 339 of the series Advances inIntelligent Systems and Computing, pp. 657 666
  • Singh D., Patel D., Borisaniya B., Modi C., (2016), “Collaborative IDS framework for cloud,” International Journal of Network Security, vol.18, pp.699-709.
  • Stephen M. Specht, Ruby B. Lee. (2004), “Distributed Denial of Service: Taxonomies of Attacks, Tools and Countermeasures”. International Workshop on Security in Parallel and Distributed Systems pp. 543-550, September.
Year 2020, Volume: 6 Issue: 2, 1 - 28, 30.12.2020

Abstract

References

  • Alharkan T. and Martin P., (2012), “IDSaaS: Intrusion Detection System as a Service in Public Clouds,” Proceedings of the 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 686-687.
  • Al-Shdaifat B., Alsharafat W.S. and El-bashir M., (2015), “Applying Hopfield Artificial Network and Simulating Annealing for Cloud Intrusion Detection,” Journal of Information Security Research ,vol. 6, pp.49-53. Ambikavathi C. and Srivatsa S.K., (2015), “Improving virtual machine security through intelligent intrusion detection system,” Indian Journal of Computer Science and Engineering (IJCSE), vol. 6, , pp.39.
  • CloudControls, Cloud Control Framework (Controls, Risks and Customer Questions), Cloud Controls Project, Netherlands, (online) (last accessed on 7th March, 2014).
  • Cooper S., (2019) “Best Intrusion Detection Systems (10+ IDS Tools Reviewed)” VPN News, [Online]. February 27, https://www.comparitech.com/net-admin/network-intrusion-detection-tools/
  • CSA, Security Guidance, v3, Cloud Security Alliance, November 2011.
  • CSA, Cloud Controls Matrix, v1.4, Cloud Security Alliance, March 2013.
  • EC, European Commission, Report, (2012), “Unleashing the Potential of Cloud Computing in Europe” [Online]. 27 oct., https://www.pdpjournals.com/docs/88053.pdf
  • Ghosh P., Mandal A.K. and Kumar R., (2015), “An Efficient Network Intrusion Detection System,” Chapter Information Systems Design and Intelligent Applications, vol. 339 of the series Advances in Intelligent Systems and Computing, pp91-99.
  • Gupta S. and Kumar P., (2015), “Immediate System Call Sequence Based Approach for Detecting Malicious Program Executions in Cloud Environment,” Wireless Personal Communications, vol. 81, pp.405-425.
  • Kaliyamurthie K. P., Suresh R. M., (2012) “Artificial Intelligence Technique Applied to Intrusion Detection”, International Journal of Computer Science and Telecommunications, Vol. 3, No. 4, pp. 20- 25.
  • Kaspersky (August 4, 2015) “DDoS Intelligence Report Q2 2015”, By Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-q1& q2-2015/71663/
  • Kaspersky , (April 28, 2016), “DDoS Intelligence Report for Q1 2016”, Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-for-q1-2016/74550/
  • Kaspersky, ( November 3, 2015) “DDoS Intelligence Report Q3 2015”, By Kaspersky Lab [Online]., https://securelist.com/kaspersky-ddos-intelligence-report-q3-2015/72560/ Kaspersky, (August 1, 2016), “DDoS Intelligence Report for Q2 2016”, Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-for-q2-2016/75513/
  • Kaspersky, (January 28, 2016), “DDoS Intelligence Report for Q4 2015”, By Kaspersky Lab [Online]. https://securelist.com/kaspersky-ddos-intelligence-report-for-q4-2015/73414/
  • Kene S.G., Theng D.P., (2015), “A review on intrusion detection techniques for cloud computing and security challenges,” IEEE 2nd International Conference on Electronics and Communication Systems (ICECS), 2015, pp.227-323.
  • Khaldi A., Karoui K. and Ghezala H. B., (2014), “Framework to detect and repair distributed intrusions based on mobile agent in hybrid cloud,” Inter. Conf. Par. and Dist. Proc. Tech. and Appl. (PDPTA'14), pp.471-476.
  • Khaldi A., Karoui K. and Ghezala H. Ben, (2014) “Framework to detect and repair distributed intrusions based on mobile agent in hybrid cloud,” Inter. Conf. Par. and Dist. Proc. Tech. and Appl. (PDPTA'14), pp.471-476.
  • Khalimonenko A, Kupreev O, (2017), “DDOS attacks in Q1 2017” [Online]., https://securelist.com/ddos-attacks-in-q12017/78285/
  • Khalimonenko A, Kupreev O, Ilganaev K (2018) “DDoS attacks in Q4 2017” [Online]., Feb 6, https://securelist.com/ddos-attacks-in-q4-2017/83729
  • Khalimonenko A, Kupreev O, Ilganaev K (2017) “DDoS attacks in Q3 2017”, [Online]. November 6,, , https://securelist.com/ddos-attacks-in-q3-2017/83041/
  • Khalimonenko A, Strohschneider J, Kupreev O, (2017), “DDoS attacks in Q4 2016” [Online]. February 2, https://securelist.com/ddos-attacks-in-q4-2016/77412/
  • Khatri J.K., Khilari G., (2015), “Advancement in Virtualization Based Intrusion Detection System in Cloud Environment,” International Journal of Science, Engineering and Technology Research (IJSETR), vol. 4, pp.1510-1514.
  • Kolahi .S, K, Sarrafpour. B. (2015 ), “Analysis of UDP DDoS Flood Cyber Attack and Defense Machanics on Web Service with Linux Ubuntu 13”. New Zealand, 978-1-4799-6532-8/15: Department of computing Unitec Institute of Technology. Auckland, IEEE.
  • Kupreev O, Strohschneider J, Khalimonenko A. Kaspersky, (2016) “DDOS intelligence report for Q3 2016” [Online]. October 31,,https://securelist.com/kaspersky-ddos-intelligence-report-for-q3-2016/76464/
  • Madhavi, M. (2012), "An Approach For Intrusion Detection System In Cloud Computing", International Journal of Computer Science and Information Technologies, 3(5), 5219–5222. 2012
  • Manthira S.M. and Rajeswari M., (2014), “Virtual Host based Intrusion Detection System for Cloud,” International Journal of Engineering and Technology (IJET), vol. 5, pp. 5023- 5029.
  • Messier R., (2014) “Collaboration with cloud computing security, social Media, and Unified communications” Elsevier.
  • Modi C.N, D. Patel, (2013), “A novel Hybrid-Network Intrusion Detection System (H-NIDS) in Cloud Computing,” IEEE Symposium on Computational Intelligence in Cyber Security (CICS), pp. 23-30.
  • Modi C.N. and Patel D., (2013), “A novel Hybrid-Network Intrusion Detection System (H-NIDS) in Cloud. Computing,” IEEE Symposium on Computational Intelligence in Cyber Security(CICS), pp. 23-30.
  • Modi C.N., Patel D.R., Patel A. and Rajarajan M., (2012 ), “Integrating signature A priori based network intrusion detection system (NIDS) in cloud computing,” 2nd International Conference on Communication, Computing and Security, pp.905–912.
  • Muthukumar B. B. and Rajendran P.K., (2015 ), “Intelligent Intrusion Detection System for Private Cloud Environment,” Communications in Computer and Information Science , vol. 536, pp.54-65.
  • NIST, Guidelines on Security and Privacy in Public Cloud Computing, National Institute of Standards and Technology, Draft Special Publication 800-144, USA.
  • Pandeeswari N. and Kumar G., (2015), “Anomaly Detection System in Cloud Environment Using Fuzzy Clustering Based ANN,” Mobile Networks and Applications, pp.1-12.
  • Patel A., Taghavi M., Bakhtiyari K., Junior J.C., (2013 ), “An Intrusion Detection and Prevention System in Cloud Computing: A Systematic Overview,” Journal of Network and Computer Applications, vol. 36, pp.25–41.
  • Peng T, Leckie C, Ramamohanarao K. (2006), “Survey of Network-based Defense Mechanisms Countering the DoS and DDoS Problems.” ACM Transactions on Computational Logic ,1-0.
  • Robinson T., (2015), “Series of DDoS Attacks plague linode data centers, infrastructure”. SC Magazine.
  • Sangeetha S., Devi B.G., Ramya R., Dharani M.K. and Sathya P., (2015), “Signature Based Semantic Intrusion Detection System on Cloud,” Chapter 66 of the book “Information Systems Design and Intelligent Applications”, vol. 339 of the series Advances inIntelligent Systems and Computing, pp. 657 666
  • Singh D., Patel D., Borisaniya B., Modi C., (2016), “Collaborative IDS framework for cloud,” International Journal of Network Security, vol.18, pp.699-709.
  • Stephen M. Specht, Ruby B. Lee. (2004), “Distributed Denial of Service: Taxonomies of Attacks, Tools and Countermeasures”. International Workshop on Security in Parallel and Distributed Systems pp. 543-550, September.
There are 39 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Ahmet Efe

Sameer Abbas This is me

Hakam Sameer This is me

Publication Date December 30, 2020
Published in Issue Year 2020 Volume: 6 Issue: 2

Cite

APA Efe, A., Abbas, S., & Sameer, H. (2020). BULUT BİLİŞİM ORTAMINDAKİ YBS İÇİN SALDIRI TESPİT VE ÖNLEME SİSTEMLERİ ÜZERİNDE BİR DEĞERLENDİRME. Yönetim Bilişim Sistemleri Dergisi, 6(2), 1-28.