Open Access
Issue
E3S Web Conf.
Volume 202, 2020
The 5th International Conference on Energy, Environmental and Information System (ICENIS 2020)
Article Number 15003
Number of page(s) 10
Section Smart Information System
DOI https://doi.org/10.1051/e3sconf/202020215003
Published online 10 November 2020
  1. S. Sundaresan, W. De Donato, N. Feamster, R. Teixeira, S. Crawford, and A. Pescapè, “Measuring home broadband performance,” Commun. ACM, vol. 55, no. 11, pp. 100–109, (2012). [Google Scholar]
  2. E. Y. M. Muharish, “Packet Filter Approach To Detect,” i, (2016). [Google Scholar]
  3. N. S.Mangrulkar, A. R. Bhagat Patil, and A. S. Pande, “Network Attacks and Their Detection Mechanisms: A Review,” Int. J. Comput. Appl., vol. 90, no. 9, pp. 37–39, (2014). [Google Scholar]
  4. D. Chasaki, Q. Wu, and T. Wolf, “Attacks on network infrastructure,” Proc. - Int. Conf. Comput. Commun. Networks, ICCCN, no. September, (2011). [Google Scholar]
  5. P. P. Laskowski, “Internet security - Technology and social awareness of the dangers,” Stud. Logic, Gramm. Rhetor., vol. 50, no. 1, pp. 239-252, (2017). [CrossRef] [Google Scholar]
  6. Q. Yan and F. R. Yu, “Distributed denial of service attacks in software-defined networking with cloud computing,” IEEE Commun. Mag., vol. 53, no. 4, pp. 52-59, (2015). [Google Scholar]
  7. S. Pareek, A. Gautam, and R. Dey, “Different Type Network Security Threats and Solutions, A Review,” IPASJ Int. J. Comput. Sci., vol. Volume 5, no. issue 4, pp. 1-10, (2017). [Google Scholar]
  8. P. D. Bojović, I. Bašičević, S. Ocovaj, and M. Popović, “A practical approach to detection of distributed denial-of-service attacks using a hybrid detection method,” Comput. Electr. Eng., vol. 73, no. August, pp. 84-96, (2019). [Google Scholar]
  9. P. Dzurenda, Z. Martinasek, and L. Malina, “Network Protection Against DDoS Attacks,” Int. J. Adv. Telecommun. Electrotech. Signals Syst., vol. 4, no. 1, (2015). [Google Scholar]
  10. U. Farooq, “Network Security Challenges,” Researchgate, no. August, pp. 2-7, (2018). [Google Scholar]
  11. P. A. Devi, S. R. Laskhmi, and K. S. Vaishnavi, “A Study on Network Security Aspects and Attacking Methods,” Int. J. P2P Netw. Trends Technol, vol. 3, no. 2, pp. 97-103, (2013). [Google Scholar]
  12. K. Ahmad, S. Vivekananda, and U. Pradesh, “Classification of Internet Security Attacks Classification of Internet Security Attacks,” Researchgate, no. October, pp. 1-4, (2015). [Google Scholar]
  13. R. H. Puspita and D. Rohedi, “The Impact of Internet Use for Students,” IOP Conf. Ser. Mater. Sci. Eng., vol. 306, no. 1, (2018). [Google Scholar]
  14. W. Dou, Q. Chen, and J. Chen, “A confidence-based filtering method for DDoS attack defense in cloud environment,” Futur. Gener. Comput. Syst, vol. 29, no. 7, pp. 1838–1850, (2013). [CrossRef] [Google Scholar]
  15. S. Patil and S. Chaudhari, “DoS Attack Prevention Technique in Wireless Sensor Networks,” Procedia Comput. Sci., vol. 79, pp. 715-721, (2016). [Google Scholar]
  16. A. Madhuri, “Attack Patterns for Detecting and Preventing Ddos and Replay Attacks,” Int. J. Eng. Sci. Technol, vol. 2, no. 9, pp. 4850-4859, (2010). [Google Scholar]
  17. Z. Yi, L. Qiang, and Z. Guofeng, “A real-time DDoS attack detection and prevention system based on per-IP traffic behavioral analysis,” Proc. - 2010 3rd IEEE Int. Conf. Comput. Sci. Inf. Technol. ICCSIT 2010, vol. 2, no. August, pp. 163-167, (2010). [Google Scholar]
  18. K. Zeb, O. Baig, and M. K. Asif, “DDoS attacks and countermeasures in cyberspace,” 2015 2nd World Symp. Web Appl. Networking, WSWAN 2015, no. June, (2015). [Google Scholar]
  19. H. Rahmani, N. Sahli, and F. Kamoun, “Distributed denial-of-service attack detection,” Researchgate, no. September 2011, pp. 2542-2554, (2011). [Google Scholar]
  20. Kamesh and N. Sakthi Priya, “A survey of cyber crimes Yanping,” Secur. Commun. Networks, vol. 5, no. December 2009, pp. 422-437, (2012). [Google Scholar]
  21. Kamesh and N. Sakthi Priya, “A survey of cyber crimes Yanping,” Secur. Commun. Networks, vol. 5, no. July 2014, pp. 422-437, (2012). [Google Scholar]
  22. T. Ait Tchakoucht and M. Ezziyyani, “Building a fast intrusion detection system for high-speed-networks: Probe and dos attacks detection,” Procedia Comput. Sci., vol. 127, pp. 521-530, (2018). [Google Scholar]
  23. M. Ahmed, A. Anwar, A. N. Mahmood, Z. Shah, and M. J. Maher, “An Investigation of Performance Analysis of Anomaly Detection Techniques for Big Data in SCADA Systems,” EAI Endorsed Trans. Ind. Networks Intell. Syst, vol. 2, no. 3, p. e5, (2015). [Google Scholar]
  24. A. Dhaka, A. Nandal, and R. S. Dhaka, “Gray and Black Hole Attack Identification Using Control Packets in MANETs,” Procedia Comput. Sci ., vol 54, pp. 83-91, (2015). [Google Scholar]
  25. X. Sun, J. Dai, P. Liu, A. Singhal, and J. Yen, “Using Bayesian Networks for Probabilistic Identification of Zero-Day Attack Paths,” IEEE Trans. Inf. Forensics Secur., vol. 13, no. 10, pp. 2506–2521, (2018). [CrossRef] [Google Scholar]
  26. A. Singh and D. Juneja, “Agent Based Preventive Measure for UDP Flood Attack in DDoS Attacks,” Int. J. Eng. Sci. Technol., vol. 2, no. 8, pp. 3405–3411, (2010). [Google Scholar]
  27. T. Gairola and K. Singh, “A Review on DOS and DDOS Attacks in Cloud Environment & Security Solutions,” Int. J. Comput. Sci. Mob. Comput., vol. 57, no. 7, pp. 136–141, (2016). [Google Scholar]
  28. T. Gairola and K. Singh, “International Journal of Advanced Research in Cloud Security Issues : Counter DDOS Attack by Integrating IP Monitoring and Routing Protocol,” Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 6, no. 7, pp. 217–222, (2016). [Google Scholar]
  29. A. N. Jaber, “Methods for Preventing DDoS Attacks in Cloud Computing,” Am. Sci. Publ., no. May 2017, 2016. [Google Scholar]
  30. A. Bijalwan, M. Wazid, E. S. Pilli, and R. C. Joshi, “Forensics of Random-UDP Flooding Attacks,” J. Networks, vol. 10, no. 5, (2015). [CrossRef] [Google Scholar]

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