Open Access   Article Go Back

A Taxonomy and Survey of Security challenges in intrusion detection and prevention for Cloud Computing

R. Hamsaveni1 , Vasumathy M.2

Section:Survey Paper, Product Type: Journal Paper
Volume-8 , Issue-11 , Page no. 79-84, Nov-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i11.7984

Online published on Nov 30, 2020

Copyright © R. Hamsaveni, Vasumathy M. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: R. Hamsaveni, Vasumathy M., “A Taxonomy and Survey of Security challenges in intrusion detection and prevention for Cloud Computing,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.11, pp.79-84, 2020.

MLA Style Citation: R. Hamsaveni, Vasumathy M. "A Taxonomy and Survey of Security challenges in intrusion detection and prevention for Cloud Computing." International Journal of Computer Sciences and Engineering 8.11 (2020): 79-84.

APA Style Citation: R. Hamsaveni, Vasumathy M., (2020). A Taxonomy and Survey of Security challenges in intrusion detection and prevention for Cloud Computing. International Journal of Computer Sciences and Engineering, 8(11), 79-84.

BibTex Style Citation:
@article{Hamsaveni_2020,
author = {R. Hamsaveni, Vasumathy M.},
title = {A Taxonomy and Survey of Security challenges in intrusion detection and prevention for Cloud Computing},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2020},
volume = {8},
Issue = {11},
month = {11},
year = {2020},
issn = {2347-2693},
pages = {79-84},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5267},
doi = {https://doi.org/10.26438/ijcse/v8i11.7984}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i11.7984}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5267
TI - A Taxonomy and Survey of Security challenges in intrusion detection and prevention for Cloud Computing
T2 - International Journal of Computer Sciences and Engineering
AU - R. Hamsaveni, Vasumathy M.
PY - 2020
DA - 2020/11/30
PB - IJCSE, Indore, INDIA
SP - 79-84
IS - 11
VL - 8
SN - 2347-2693
ER -

VIEWS PDF XML
183 226 downloads 160 downloads
  
  
           

Abstract

Most of the Organizations and governments consider security as an undeniable prerequisite have in view of the extending movement of attacks which is hostile both security and assurance. In this paper, we present an investigation of IDPS which drove us to play out a gathering of systems depending upon the strategies used in interferences acknowledgment and neutralization structures. We talk about the focal points and disadvantages of these strategies. A brief timeframe later, we analyze the various issues tangling the most ideal value and efficiency of the current IDPS and moreover research its troubles in appropriated registering, PDAs and sharp metropolitan networks.

Key-Words / Index Term

Networking, Security challenges, Cloud computing, intrusion prevention, Intrusion detection,ids, ips, idps

References

[1]. J. A. P. Marpaung, M. Sain, and H.-J. Lee, “ Survey on malware evasion techniques: State of the art and challenges “, in 2012 14th International Conference on Advanced Communication Technology (ICACT), pp. 744 -749 , 2012 .
[2]. Kührer, C. Rossow, and T. Holz, “ Paint It Black: Evaluating the Effectiveness of Malware Blacklists “, in Research in Attacks, Intrusions and Defenses, A. Stavrou, H. Bos, and G. Portokalidis, Éd. Springer International Publishing, pp. 1 -21, 2014.
[3]. K. D. Bowers, C. Hart, A. Juels, and N. Triandopoulos, “PillarBox: Combating Next-Generation Malware with Fast Forward-Secure Logging “, in Research in Attacks, Intrusions and Defenses, A. Stavrou, H. Bos, and G. Portokalidis, Éd. Springer International Publishing, pp. 46-67, 2014. 1992,
[4]. S. Peng, M. Wu, G. Wang, and S. Yu, « Propagation model of smartphone worms based on semi-Markov process and social relationship graph », Computer. Security., vol. 44, pp. 92-103, 2014.
[5]. W. M. Fitzgerald, U. Neville, and S. N. Foley, “ MASON: Mobile autonomic security for network access controls “, J. Inf. Security. Appl., vol. 18, no. 1, pp. 14-29,. 2013.
[6]. K. Su, J. Li, and H. Fu, “ Smart city and the applications », in 2011 International Conference on Electronics, Communications and Control (ICECC), pp. 1028 -1031, 2011.
[7]. A. S. Elmaghraby and M. M. Losavio, “ Cyber security challenges in Smart Cities: Safety, security and privacy “, J. Adv. Res., vol. 5, no. 4,pp. 491-497, Jul. 2014.
[8]. S. Djahel, R. Doolan, G. Muntean, and J. Murphy, “ A Communications-Oriented Perspective on Traffic Management Systems for Smart Cities: Challenges and Innovative Approaches “, IEEE Commun. Surv. Tutor., vol. 17, no. 1, pp. 125 -151, Firstquarter 2015.
[9]. B. Morin, L. Mé, H. Debar, and M. Ducassé, “ A logic-based model to support alert correlation in intrusion detection “, Inf. Fusion, vol. 10, no. 4, p. 285 - 299, 2009.
[10]. M. M. M. Hassan, “Current Studies On Intrusion Detection System, Genetic Algorithm And Fuzzy Logic”, Int. J. Distrib. Parallel Syst., vol. 4, no. 2, 2013.
[11]. S. Elhag, A. Fernández, A. Bawakid, S. Alshomrani, and F. Herrera, “On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems” , Expert Syst. Appl., vol. 42, no. 1, pp. 193-202, 2015.
[12]. M. A. Ayd?n, A. H. Zaim, and K. G. Ceylan, “ A hybrid intrusion detection system design for computer network security ”, Comput. Electr. Eng., vol. 35, no. 3, pp. 517-526, 2009.
[13]. C.-C. Lo, C.-C. Huang, and J. Ku, “ A Cooperative Intrusion Detection System Framework for Cloud ComputingNetworks “, in 2010 39th International Conference on Parallel Processing Workshops (ICPPW) pp. 280- 284, 2010.
[14]. K. Wankhade, S. Patka, and R. Thool, “An Overview of Intrusion Detection Based on Data Mining Techniques “,International Conference on Communication Systems and Network Technologies (CSNT),pp. 626-629, 2013.
[15]. F. Gharibian and A. A. Ghorbani, “Comparative Study of Supervised Machine Learning Techniques for Intrusion Detection “, in Fifth Annual Conference on Communication Networks and Services Research, 2007. CNSR ’07, pp. 350-358, 2007.
[16]. L. M. Ibrahim,” Artificial Neural Network for Misuse Detection “, J. Commun. Comput., vol. 7, pp. 1548 -7709, 2010.
[17]. W.-H. Chen, S.-H. Hsu, and H.-P. Shen,” Application of SVM and ANN for intrusion detection “, Comput. Oper. Res., vol. 32, no. 10, p. 2617- 2634, 2005.
[18]. A. Tajbakhsh, M. Rahmati, and A. Mirzaei, “ Intrusion detection using fuzzy association rules “, Appl. Soft Computer, vol. 9, no. 2, p. 462-469, mar 2009.
[19]. G.-Y. Chan, C.-S. Lee, and S.-H. Heng, “ Discovering fuzzy association rule patterns and increasing sensitivity analysis of XML-related attacks “, J. Netw. Comput. Appl., vol. 36, no. 2, pp. 829-842, 2013.
[20]. H. S. Seo and T. H. Cho, « Application of Fuzzy Logic for Distributed Intrusion Detection », in Computational Intelligence and Security, Y. Hao, J. Liu, Y.-P. Wang, Y. Cheung, H. Yin, L. Jiao, J. Ma, and Y.-C. Jiao, Éd. Springer Berlin Heidelberg, pp. 340- 347, 2005.
[21]. S.K. Sharma, L. Gupta, “A Novel Approach for Cloud Computing Environment”, International Journal of Computer Engineering, Vol.4, Issue.12, pp.1-5, 2014.
[22]. K. Gupta, “A Proposed New Approach for Cloud Environment using Cryptic rules”, ISROSET Publisher, India, pp. 542-545, 2016.