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International Journal of Scientific & Technology Research

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IJSTR >> Volume 8 - Issue 12, December 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



The Impact Of DDOS And Ping Of Death On Network Performance

[Full Text]

 

AUTHOR(S)

Waleed Iftikhar, Zunair Mahmood and Daniel Mago Vistro

 

KEYWORDS

Denial of service (DOS), Distributed denial of service (DDOS), Intrusion Detection Systems (IDS) ,Low Orbit Ion Cannon (LOIC), Network Performance, Ping of Death, Riverbed Modeler

 

ABSTRACT

: A network’s performance can be affected by a number of things. Network attacks significantly reduce a networks performance and the most common attacks are the ping of death also known as DOS and the DDOS attacks. Networks of all kind whether on cloud or internet of things are affected by these attacks. Literature related to DDOS and its implications on various networks and their performance has been critically reviewed. Riverbed modeler was used to set up an experiment and Low orbit ion canon (LOIC) was used to perform a DDOS attack on the target website. Based on the outcome of the experiments conducted, DOS, DDOS, and Ping of death attacks significantly slows down the performance of the network.

 

REFERENCES

[1] N. Hoque, M. H. Bhuyan, R. C. Baishya, D. K. Bhattacharyya, and J. K. Kalita, “Network attacks: Taxonomy, tools and systems,” J. Netw. Comput. Appl., vol. 40, no. 1, pp. 307–324, 2014.
[2] K. Prasad, J. Poonam, and K. Gauri, “Data Sharing Security and Privacy Preservation in Cloud Computing,” IEEE Internet Comput., pp. 1070–1075, 2015.
[3] B. Singh, “Defending Against DDOS Flooding Attacks- A Data Streaming Approach,” IJCRT, pp. 38–44, 2015.
[4] K. M. Prasad, A. R. M. Reddy, and K. V. Rao, “DoS and DDoS Attacks: Defense, Detection and TracebackMechanisms -A Survey,” Glob. J. Comput. Sci. Technol. E Network, Web Secur., vol. 14, no. 7, p. 19, 2014.
[5] J. J. Santanna et al., “Booters - An analysis of DDoS-as-a-service attacks,” Proc. 2015 IFIP/IEEE Int. Symp. Integr. Netw. Manag. IM 2015, pp. 243–251, 2015.
[6] S. Behal, K. Kumar, and M. Sachdeva, “Discriminating flash events from DDoS attacks: A comprehensive review,” Int. J. Netw. Secur., vol. 19, no. 5, pp. 734–741, 2017.
[7] C. W. Lee, K. Kim, B. H. Roh, B. Roh, and J. Choi, “SMAT: Simulator monitoring and analysis tool,” Int. Conf. Ubiquitous Futur. Networks, ICUFN, vol. 2015–Augus, pp. 482–485, 2015.
[8] A. Nayyar and R. Singh, “A Comprehensive Review of Simulation Tools for Wireless Sensor Networks ( WSNs ),” J. Wirel. Netw. Commun., vol. 5, no. 1, pp. 19–47, 2015.
[9] G. Somani, M. S. Gaur, D. Sanghi, M. Conti, M. Rajarajan, and R. Buyya, “Combating DDoS attacks in the cloud: Requirements, trends, and future directions,” IEEE Cloud Comput., vol. 4, no. 1, pp. 22–32, 2017.
[10] Z. Xiao and Y. Xiao, “Security and privacy in cloud computing,” IEEE Commun. Surv. Tutorials, vol. 15, no. 2, pp. 843–859, 2013.
[11] Cloud Security Alliance, “The Notorious Nine. Cloud Computing Top Threats in 2013,” Security, no. February, pp. 1–14, 2013.
[12] N. Goodman, “A Survey of Advances in Botnet Technologies,” pp. 1–9, 2017.
[13] Q. Yan, F. R. Yu, Q. Gong, and J. Li, “Software-defined networking (SDN) and distributed denial of service (DDOS) attacks in cloud computing environments: A survey, some research issues, and challenges,” IEEE Commun. Surv. Tutorials, vol. 18, no. 1, pp. 602–622, 2016.
[14] M. A. M. Yusof, F. H. M. Ali, and M. Y. Darus, “Detection and Defense Algorithms of Different Types of DDoS Attacks Using Machine Learning,” Lect. Notes Electr. Eng., vol. 488, no. 5, pp. 370–379, 2018.
[15] A. A. Acharya, K. M. Arpitha, and B. J. Santhosh Kumar, “An intrusion detection system against UDP flood attack and ping of death attack (DDOS) in MANET,” Int. J. Eng. Technol., vol. 8, no. 2, pp. 1112–1115, 2016.
[16] C. K. Chan and A. W. T. Yeoh, “Development of a Platform to Explore Network Intrusion Detection System (NIDS) for Cybersecurity,” J. Comput. Commun., vol. 06, no. 01, pp. 1–11, 2018.
[17] J. Jun, D. Lee, and S. Kim, “DDoS Attack Detection Using Flow Entropy and Packet Sampling on Huge Networks,” Thirteen. Int. Conf. Networks., no. c, pp. 185–190, 2014.
[18] M. Šimon, “DDoS testbed based on peer-to-peer grid,” Int. Conf. Signal Process. Commun. Power Embed. Syst. (SCOPES)-201, pp. 1181–1186, 2016.
[19] K. Hussain, S. J. Hussain, V. Dillshad, M. Nafees, and M. A. Azeem, “An Adaptive SYN Flooding attack Mitigation in DDOS Environment,” IJCSNS Int. J. Comput. Sci. Netw. Secur., vol. 16, no. 7, p. 2016, 2016.
[20] R. Mehta, “Distributed Denial of service Attacks on Cloud Environment,” Int. J. Adv. Res. Comput. Sci., vol. 8, no. 5, pp. 2204–2206, 2017.
[21] T. Halabi and M. Bellaiche, “How to Evaluate The Defense Against DoS and DDoS Attacks in Cloud Computing: A Survey and Taxonomy,” Int. J. Comput. Sci. Inf. Secur., vol. 14, no. 12, pp. 1–10, 2016.
[22] G. Somani, M. S. Gaur, D. Sanghi, M. Conti, and R. Buyya, “DDoS attacks in cloud computing: Issues, taxonomy, and future directions,” Comput. Commun., vol. 107, pp. 30–48, 2017.
[23] S. Agrawal and D. Vieira, “A survey on Internet of Things,” Abak{ó}s, Belo Horiz., vol. 1, no. 2, pp. 78–95, 2013.
[24] C. Kolias, G. Kambourakis, A. Stavrou, and J. Voas, “DDoS in the IoT: Mirai and other botnets,” Computer (Long. Beach. Calif)., vol. 50, no. 7, pp. 80–84, 2017.
[25] G. Ferrari and P. Medagliani, “Performance Analysis of Zigbee Wireless Sensor Networks,” 2018 2nd Int. Conf. Inven. Syst. Control, no. Icisc, pp. 1272–1277, 2018.
[26] D. Freet and R. Agrawal, “A virtual machine platform and methodology for network data analysis with IDS and security visualization,” Conf. Proc. - IEEE SOUTHEASTCON, no. Vm, 2017.
[27] F. Yihunie, E. Abdelfattah, and A. Odeh, “Analysis of Ping of Death DoS and DDoS Attacks,” IJCRT, pp. 3–6, 2017.