A Survey on Botnet Attacks
Keywords:
botnets, DDOS, Data Theft, Security, Click fraud IntroductionAbstract
Devices connected to the Internet are the target of numerous attacks to steal or exploit their resources. As these attacks become widespread (and sophisticated), the first step in protecting your organization is knowing exactly what you are facing. We currently have botnets that are the main source of network attacks such as spam, denial of service (DDoS), click fraud, data theft, Pass the Hash, and RDC attack. With the evolution of technology, we have several solutions to protect against attacks that undermine businesses, governments, individuals, but security attack methods are increasing daily. This study seeks further investigate botnet attacks and also provide a comparison of these attacks, lastly, the survey will create awareness for forthcoming botnet research endeavors.
References
. J. R. Binkley and S. Singh, “An algorithm for anomaly-based botnet detection,” in Proceedings of the 2nd conference on Steps to Reducing Unwanted Traffic on the Internet, pp. 7–7, Berkeley, CA, USA, 2006
. Top Ten Cyber Security Menaces for 2008, SANS Institute, 2009.
. Ramneek Pur, Bots &; Botnet: An Overview, SANS Institute Information Security Reading Room, GSEC Practical Assignment Version 1.4b, August 08, 2003
. Muhammad Mahmoud, Manjinder Nir, and Ashraf Matrawy, International Journal of Network Security, Vol.17, No.3, PP.272-289, May 2015
. Schneier, B. (2004). Secrets and Lies. Indianapolis, Indiana: Wiley Publishing, Inc.
. Narendra Kumar Tyagi(Asst, Professor) DCE.Khentawas, Gurgaon, AbhilashaVyas(Asst. Professor)DCE.Khentawas, Gurgaon, Data security from malicious attack: Computer Virus.
. Sharp, Robin, An Introduction to Malware, pp. 18, 2017
. Matija Stevanovic and Jens Myrup Pedersen Networking and Security Section, Department of Electronic Systems Aalborg University, DK-9220 Aalborg East, Denmark Machine learning for identifying botnet network traffic, pp.5-6, 2013
. Brett Stone-Gross, Marco Cova, Lorenzo Cavallaro, Bob Gilbert, Martin Szydlowski, Richard Kemmerer, Christopher Kruegel, and Giovanni Vigna University of California, Santa Barbara, CCS’09, November 9–13, 2009, Chicago, Illinois, USA.
. Paul Barford Vinod Yegneswaran, an inside Look at Botnets, computer sciences department university of Wisconsin, Madison, pp.15-16, 2017.
. Trend Micro, Taxonomy of Botnet Threats, A Trend Micro White Paper / November 2006.
. USENIX Association Understanding the Mirai Botnet, 26th USENIX Security Symposium 1093.
. Massimiliano Romano, Simone Rosignoli, Ennio Giannini, Robot Wars – How Botnets Work, Window Security, 2009.
. S. K. Pandey, Security Vigilance system through Level Driven Security Maturity Model, International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.2, April 2012.
. Defeating the Botnets of the Future, WatchGuard Technologies, 2008.
. K. Veeramachaneni, I. Arnaldo, V. Korrapati, C. Bassias, and K. Li, “Aiˆ 2: training a big data machine to defend,” in Big Data Security on Cloud, IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS), 2016 IEEE 2nd International Conference on. IEEE, 2016, pp. 49–54.
. N. Blenn, V. Ghiette, and C. Doerr, “Quantifying the Spectrum ¨ of Denial-of-Service Attacks through Internet Backscatter,” in Proceedings of the 12th International Conference on Availability, Reliability, and Security - ARES ’17. ACM Press, 2017, pp. 1–10.
. Y. M. P. Pa, S. Suzuki, K. Yoshioka, T. Matsumoto, T. Kasama, and C. Rossow, “IoTPOT: A Novel Honeypot for Revealing Current IoT Threats,” Journal of Information Processing, vol. 24, no. 3, pp. 522–533, 2016.
. A. Tuor, S. Kaplan, B. Hutchinson, N. Nichols, and S. Robinson, “Deep learning for unsupervised insider threat detection in structured cybersecurity data streams,” in Artificial Intelligence for Cybersecurity Workshop at AAAI, 2017.
. Symantec, 2018. APT28: New Espionage Operations Target Military and Government Organizations, 18 Feb 2019.
. Mirea, M., V. Wang, and J. Jung. 2019. The not so dark side of the darknet: A qualitative study. Security Journal 32: 102–118.
. Chen, W., et al. 2017. CloudBot: Advanced mobile Botnets using ubiquitous cloud technologies. Pervasive and Mobile Computing 41: 270–285.
. Manoj Rameshchandra Thakur, Divye Raj Khilnani, Kushagra Gupta, Sandeep Jain, and Vineet Agarwal, Detection and Prevention of Botnets and malware in an enterprise network, International Journal of Wireless and Mobile Computing · May 2012.
. An Approach to Secure Software Defined Network against Botnet Attack November 2019 Journal of Physics Conference Series 1362:01212.
. Botnet detection using software-defined networking, 22nd International Conference on Telecommunications, June 2015.
. Shang-Chiuan Su,1 Yi-Ren Chen,1 Shi-Chun Tsai,1 and Yi-Bing Lin Detecting P2P Botnet in Software Defined Networks, Security and Communication Networks, Volume 2018
. Baldwin, R., Cave, M., & Lodge, M. (2010). Introduction: Regulation–The field and developing agenda. Dans R. Baldwin, M. Cave & M. Lodge (Éds.), The Oxford handbook of the regulation (pp. 3-16). Oxford: Oxford University Press.
. Abdelrahman, O.H., E. Gelenbe, G. Görbil, and B. Oaklander, “Mobile Network Anomaly Detection and Mitigation: The NEMESYS Approach,” Information Sciences and Systems 2013 Lecture Notes in Electrical Engineering, vol. 264, pp.429-438, 2013.
. Abdullah Al Hasib, “Threats of Online Social Networks", IJCSNS, Vol. 9, No 11, November 2009
. THREATS STATISTICS, Malware, Incidents Web and Network Threats, McAfee Labs Threats Report, March 2018.
. IBM Security, releases the IBM X-Force Threat Intelligence Index, 2019.
. IBM Security, releases the IBM X-Force Threat Intelligence Index, 2020
. Mahmoud, M., Nir, M., & Matrawy, A. (2015). A Survey on Botnet Architectures, Detection, and Defences. IJ Network Security, 17(3), 264-281.
. PENG, T., LECKIE, C., AND RAMAMOHANARAO, K. Survey of network-based defense mechanisms countering the dos and DDoS problems. ACM Comput. Surv. 39, 1 (Apr. 2007).
. ROBINSON, M., MIRKOVIC, J., MICHEL, S., SCHNAIDER, M., AND REIHER, P. Defcom: defensive cooperative overlay mesh. In Proceedings DARPA Information Survivability Conference and Exposition (April 2003), vol. 2, pp. 101–102 vol.2.
. SAHAY, R., BLANC, G., ZHANG, Z., AND DEBAR, H. Towards autonomic DDoS mitigation using software-defined networking. In SENT 2015: NDSS Workshop on Security of Emerging Networking Technologies (2015), Internet society.
. SATYANARAYANAN, M. A brief history of cloud offload: A personal journey from the odyssey through cyber foraging to cloudlets. GetMobile: Mobile Comp. and Comm. 18, 4 (Jan. 2015), 19–23.
. SEKAR, V., DUFFIELD, N. G., SPATSCHECK, O., VAN DER MERWE, J. E., AND ZHANG, H. Lads: Large-scale automated DDoS detection system. In USENIX Annual Technical Conference, General Track (2006), pp. 171–184.
. SITARAMAN, R. K., KASBEKAR, M., LICHTENSTEIN, W., AND JAIN, M. Overlay networks: An akamai perspective. Advanced Content Delivery, Streaming, and Cloud Services 51, 4 (2014), 305–328.
. WANG, Y.-P. E., LIN, X., ADHIKARY, A., GROÌ´LVLEN, A., SUI, Y., BLANKENSHIP, Y., BERGMAN, J., AND RAZAGHI, H. S. A Primer on 3GPP Narrowband Internet of Things (NBIoT). In arxiv.org (2016).
. Da-Wen Huang, 1 Lu-Xing Yang, 2 Xiaofan Yang, 1 Xiang Zhong, 1 and Yuan Yan Tang 3 Evaluating the Performance of a Static Patching Strategy against Computer Viruses, Hindawi, Volume 2020 |Article ID 9408942
. ZARGAR, S. T., JOSHI, J., AND TIPPER, D. A survey of defense mechanisms against distributed denial of service (DDoS) flooding attacks. IEEE Communications Surveys Tutorials 15, 4 (Fourth 2013), 2046–2069.
. G. Nikolic, T. Nikolic, M. Stojcev, B. Petrovic, and G. Jovanovic, “Battery capacity estimation of the wireless sensor node,” in Proceedings of the IEEE 30th International Conference on Microelectronics (MIEL), pp. 279–282, IEEE, 2017.
. Farrell, G., Tseloni, A., Mailley, J., & Tilley, N. (2011). The crime drop and the security hypothesis. Journal of Research on Crime and Delinquency, 48(2), 147-175.
. Akamai, “Spike DDoS toolkit,” Tech. Rep. 1078, Akamai, Cambridge, Mass, USA, 2014.
. M. J. Bohio, “Analyzing a backdoor/bot for the MIPS platform,” Tech. Rep., SANS Institute, 2015.
. Symantec Security Response, ShellShock: All you need to know about the Bash Bug vulnerability, Symantec Blog, 2014.
. Akamai, “Case study: FastDNS infrastructure battles Xor botnet,” Tech. Rep., Akamai Technologies, Cambridge, Mass, USA,2015.
. NSFOCUS DDoS Defense Research Lab and Treat Response Center (TRC), “2016 q3 report on DDoS situation and trends,” Tech. Rep., NSFOCUS, Inc., 2016.
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