Skip to main content
SpringerLink
Log in

Approach for Ensuring Fragmentation and Integrity of Data in SEDuLOUS

  • Conference paper
  • First Online:
Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 203))

Abstract

With the rapid adoption of cloud services, more and more data are being uploaded on the cloud platform. These data are under threat from various threat actors constantly researching to steal, corrupt, or get control over the data. The threat actors are not only limited to malicious attackers, but these also include curious service providers, social activists, business entities, and nations. They pose a serious risk to cloud services. There are various approaches to protect data at various levels. Division and replication is one such approach where data are divided into chunks and spread over the cloud to reduce the risk of data leakage and simultaneously increase the accessibility. Under division and replication approach, SEDuLOUS provides a heuristic algorithm for data placement in a distributed cloud environment. In this research work, we have provided a comprehensive analysis on cloud data storage services and associated security issues, analysis of SEDuLOUS algorithm, and methodology to improve the SEDuLOUS by specifying minimum fragments to ensure fragmentation of all files and hashing of each chunk to identify the compromised storage nodes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Mell P, Grance T (2011) The NIST definition of cloud computing. Special Publication, National Institute of Standard and Technology, pp 145–800

    Google Scholar 

  2. Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I (2009) Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Futur Gener Comput Syst 25(6):599–616

    Article  Google Scholar 

  3. Alani MM (2016) Elements of cloud computing security. In: Computer science. DOI https://doi.org/10.1007/978-3-319-41411-9_1. Springer, Berlin

  4. Henze M, Matzutt R, Hiller J, Mühmer E, Ziegeldorf JH, Giet JVD, Wehrle K (2017) Practical data compliance for cloud storage. In: 2017 IEEE international conference on cloud engineering (IC2E), pp 252–258

    Google Scholar 

  5. Buyya R, Broberg J, Goscinski AM (2010) Cloud computing: principles and paradigms, vol 87. Wiley, London

    Google Scholar 

  6. STAMFORD Gartner Identifies the Top Seven Security and Risk Management Trends for 2019 (2019). https://www.gartner.com/en/newsroom/press-releases/2019-03-05-gartner-identifies-the-top-seven-security-and-risk-ma. Last Accessed 22 July 2020

  7. T. T. W. Group (2016) The treacherous 12: cloud computing top threats in 2016. Cloud Security Alliance. Last Accessed 20 June 2020

    Google Scholar 

  8. Varghese B, Buyya R (2018) Next generation cloud computing: new trends and research directions. Futur Gener Comput Syst 79:849–861

    Article  Google Scholar 

  9. Ouffoué G, Ortiz AM, Cavalli AR, Mallouli W, Domingo-Ferrer J, Sánchez D, Zaidi F (2016) Intrusion detection and attack tolerance for cloud environments: the clarus approach. In: 2016 IEEE 36th international conference on distributed computing systems workshops (ICDCSW), pp 61–66

    Google Scholar 

  10. Torkura KA, Sukmana MIH, Meinig M, Kayem AVDM, Cheng F, Graupner H, Meinel C (2018) Securing cloud storage brokerage systems through threat models. In: 2018 IEEE 32nd international conference on advanced information networking and applications (AINA), pp 759–768

    Google Scholar 

  11. Kajal N, Ikram N (2015) Security threats in cloud computing. In: International conference on computing, communication and automation. IEEE, pp 691–694

    Google Scholar 

  12. Tari Z, Yi X, Premarathne US, Bertok P, Khalil I (2015) Security and privacy in cloud computing: vision, trends, and challenges. IEEE Cloud Comput 2(2):30–38

    Article  Google Scholar 

  13. Choo KKR, Sarre R (2015) Balancing privacy with legitimate surveillance and lawful data access. IEEE Cloud Comput 2(4):8–13

    Article  Google Scholar 

  14. Quick D, Choo KKR (2016) Big forensic data reduction: digital forensic images and electronic evidence. Clust Comput 19(2):723–740

    Article  Google Scholar 

  15. Khan N, Al-Yasiri A (2016) Identifying cloud security threats to strengthen cloud computing adoption framework. Procedia Comput Sci 94:485–490

    Article  Google Scholar 

  16. Anwar S, Inayat Z, Zolkipli MF, Zain JM, Gani A, Anuar NB, Khan MK, Chang V (2017) Cross-VM cache-based side channel attacks and proposed prevention mechanisms: a survey. J Netw Comput Appl 93:259–279

    Article  Google Scholar 

  17. Patel D, Gupta RK, Pateriya R (2019) Energy-aware prediction-based load balancing approach with VM migration for the cloud environment. In: Data, engineering and applications. Springer, pp 59–74

    Google Scholar 

  18. Xiao X, Zheng W, Xia Y, Sun X, Peng Q, Guo Y (2019) A work load aware VM consolidation method based on coalitional game for energy saving in cloud. IEEE Access 7:80421–80430

    Google Scholar 

  19. Xiao X, Xia Y, Zeng F, Zheng W, Sun X, Peng Q, Guo Y, Luo X (2019) A novel coalitional game-theoretic approach for energy aware dynamic VM consolidation in heterogeneous cloud datacenters. In: International conference on web services. Springer, pp 95–109

    Google Scholar 

  20. Jordon M (2012) Cleaning up dirty disks in the cloud. Netw Secur 2012(10):12–15

    Article  MathSciNet  Google Scholar 

  21. Xia Y, Liu Y, Chen H, Zang B (2012) Defending against VM rollback attack. In: IEEE/IFIP international conference on dependable systems and networks workshops (DSN 2012). IEEE, pp 1–5

    Google Scholar 

  22. Singh A, Chatterjee K (2017) Cloud security issues and challenges: a survey. J Netw Comput Appl 79:88–115

    Article  Google Scholar 

  23. Castro-Medina F, Rodríguez-Mazahua L, Abud-Figueroa MA, Romero-Torres C, Reyes-Hernández LÁ, Alor-Hernández G (2019) Application of data fragmentation and replication methods in the cloud: a review. In 2019 International conference on electronics, communications and computers (CONIELECOMP). IEEE, pp 47–54

    Google Scholar 

  24. Mansouri N, Javidi MM (2020) A review of data replication based on meta-heuristics approach in cloud computing and data grid. In: Soft computing, pp 1–28

    Google Scholar 

  25. Santos N, Lentini S, Grosso E, Ghita B, Masala G (2019) Performance analysis of data fragmentation techniques on a cloud server. Int J Grid Util Comput 10(4):392–401

    Article  Google Scholar 

  26. Ali M, Bilal K, Khan SU, Veeravalli B, Li K, Zomaya AY (2018) Drops: division and replication of data in cloud for optimal performance and security. IEEE Trans Cloud Comput 6(2):303–315

    Article  Google Scholar 

  27. Pandithurai O, Shenbagalakshmi R, Sindujha AU (2019) A noval approach of drops with NTRU in cloud. In: 2019 5th international conference on science technology engineering and mathematics (ICONSTEM), vol 1, pp 261–265

    Google Scholar 

  28. Khatod V, Ingale S, Gund K, Gorde S, Joshi R, Khengare R (2020) Enigma: a hybrid approach to file security in cloud. In: Proceedings of ICETIT 2019. Springer, Cham, pp 1005–1015

    Google Scholar 

  29. Hudic A, Islam S, Kieseberg P, Rennert S, Weippl ER (2013) Data confidentiality using fragmentation in cloud computing. Int J Pervasive Comput Commun

    Google Scholar 

  30. Kang S, Veeravalli B, Aung KMM (2016) A security-aware data placement mechanism for big data cloud storage systems. In: 2016 IEEE 2nd international conference on big data security on cloud (BigDataSecurity), IEEE international conference on high performance and smart computing (HPSC), and IEEE international conference on intelligent data and security (IDS), pp 327–332

    Google Scholar 

  31. Raghavan S (2014) E-science infrastructure: national knowledge network (NKN) initiative. CSI Trans ICT 2(3):207–215

    Article  Google Scholar 

  32. Peazip. Compression benchmark. https://www.peazip.org/peazip-compression-benchmark.html. Last Accessed 22 July 2020

Download references

Author information

Authors and Affiliations

  1. Sardar Patel University of Police Security and Criminal Justice, Jodhpur, India

    Anand Prakash Singh & Arjun Choudhary

Authors
  1. Anand Prakash Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arjun Choudhary
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anand Prakash Singh .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India

    Pradeep Kumar Singh

  2. Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland

    Sławomir T. Wierzchoń

  3. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Sudeep Tanwar

  4. Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland

    Maria Ganzha

  5. Instituto de Telecomunicações, Federal University of Piauí (UFPI), Teresina, Piauí, Brazil

    Joel J. P. C. Rodrigues

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Singh, A.P., Choudhary, A. (2021). Approach for Ensuring Fragmentation and Integrity of Data in SEDuLOUS. In: Singh, P.K., Wierzchoń, S.T., Tanwar, S., Ganzha, M., Rodrigues, J.J.P.C. (eds) Proceedings of Second International Conference on Computing, Communications, and Cyber-Security. Lecture Notes in Networks and Systems, vol 203. Springer, Singapore. https://doi.org/10.1007/978-981-16-0733-2_61

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-0733-2_61

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0732-5

  • Online ISBN: 978-981-16-0733-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation