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image of A Comprehensive Analysis of the Types, Impacts, Prevention, and Mitigation of DDoS Attacks

Abstract

Background

DDoS attacks, where numerous compromised systems overwhelm a target with traffic, are significant threats to online services' stability. These attacks exploit the fundamentals of internet communication, using botnets to flood targets and deplete their resources, severely reducing performance. The strength of DDoS attacks lies in their distributed nature, which complicates the differentiation between legitimate and malicious traffic. As digital reliance grows, so does the significance of these attacks, which impact businesses, governments, and public services crucial for operations.

Objective

The paper aims to provide a comprehensive understanding of DDoS attacks, categorizing them into bandwidth and resource depletion, infrastructure, and zero-day attacks. It seeks to highlight the complexity and impact of these attacks, particularly those utilizing IoT botnets, on internet reliability and security. The study emphasizes the limitations of current defense mechanisms, advocating for improved strategies that consider the distributed nature of these threats. Through this analysis, the paper aims to foster a deeper understanding of DDoS attacks, their consequences, and the need for more effective mitigation and prevention techniques.

Methods

The study employs an in-depth literature review to classify DDoS attacks and explore various mitigation strategies. It provides a detailed examination of attack mechanisms, including bandwidth depletion, resource depletion, infrastructure attacks, and zero-day vulnerabilities. The paper discusses several defense techniques, such as filtering, intrusion detection systems, and advanced AI and machine learning approaches. It emphasizes the role of IoT devices in amplifying DDoS attacks and the challenges of defending against these evolving threats.

Result

The paper identifies four main categories of DDoS attacks and describes their operational mechanisms, impacts, and mitigation challenges. It reveals that due to inadequate security measures, IoT devices significantly contribute to the scale and impact of DDoS attacks. Despite the various defense mechanisms discussed, the paper points out their limitations in effectively countering the evolving nature of DDoS attacks. It emphasizes the need for more robust, adaptive strategies incorporating technological advancements and better security practices in IoT device manufacturing.

Conclusion

DDoS attacks, particularly those leveraging IoT botnets, pose increasingly sophisticated threats to digital infrastructure. The paper underscores the urgent need for more effective defense mechanisms, highlighting the importance of technological advancements, better IoT security, and collaborative efforts among stakeholders. It calls for future research focused on developing AI-driven systems for real-time prediction and mitigation of attacks, as well as the formulation of international cyber-security policies to address the growing menace of DDoS attacks in a globally connected environment.

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References

  1. York K. Domain Name System (DNS). 2017 Available From: http://dyn.com/blog/dyn-statement-on-10212016-
  2. Constantin L. DDoS Attacks Against US Banks Peaked At 60 Gbps. 2012 Available From: https://www.cio.com/article/2389721/ddos-attacks-against-usbanks-peaked-at-60-gbps.html
  3. Vijayan J.K. Update: Spamhaus hit by biggest-ever DDoS attacks 2013 Available From: https://www.computerworld.com/article/2495967/update--spamhaus-hit-by-biggest-ever-ddos-attacks.html
  4. Russel J.O.N. Hong L. Kong group battles huge DDoS attack. 2014 Available From: https://tinyurl.com/2jfbb9vf
  5. Thompson C. Record-breaking DDoS attack strikes Cloud Flareś network. 2014 Available From: https://www.cnbc.com/2014/02/11/record-breaking-ddos-attackstrikes-cloudflares-network.html
  6. Brian Krebs Krebs on Security hit with record DDoS – Krebs on security. 2016 Available From: https://krebsonsecurity.com/2016/09/krebsonsecurity-hit-withrecord-ddos/
  7. Kennedy J. OVH suffers 1.5Tbps DDoS attack via145,000 webcams. 2016 Available From: https://www.siliconrepublic.com/machines/mega-iot-cyberattackovh-suffers-1-5tbps-ddos-attack-via-145000-webcams
  8. Greenstein S. The aftermath of the dyn DDOS attack. IEEE Micro 2019 39 4 66 68 10.1109/MM.2019.2919886
    [Google Scholar]
  9. Menscher D. Identifying and protecting against the largest DDoS attacks. 2020 Available From: https://cloud.google.com/blog/products/identitysecurity/identifying-and-protecting-against-the
  10. Newman L.H. A 1.3-Tbs DDoS hit GitHub, the largest yet recorded. 2018 Available From: https://www.wired.com/story/github-ddos-memcached/
  11. Amazon AWS Shield Threat Landscape Report – Q1 2020. 2020 Available From: https://aws-shield-tlr.s3.amazonaws.com/2020-Q1_AWS_Shield_TLR.pdf
  12. Kim K. You Y. Park M. Lee K. DDoS mitigation: Decentralized CDN using a private blockchain International Conference on Ubiquitous and Future Networks. 03-06 July 2018 Prague, Czech Republic 2018 10.1109/ICUFN.2018.8436643
    [Google Scholar]
  13. Nazario J. DDoS attack evolution. Netw. Secur. 2008 2008 7 7 10 10.1016/S1353‑4858(08)70086‑2
    [Google Scholar]
  14. Zargar S.T. Joshi J. Tipper D. A survey of defense mechanisms against distributed denial of service (DDoS) flooding attacks. IEEE Commun. Surv. Tutor. 2013 15 4 2046 2069 10.1109/SURV.2013.031413.00127
    [Google Scholar]
  15. Nazario J. Politically motivated denial of service attacks. The virtual battlefield: Perspectives on cyber warfare. Czosseck C. Geers K. Amsterdam IOS Press 2009 163 181
    [Google Scholar]
  16. Wikipedia Internet activism during the 2009 Iranian election protests. 2017 Available From: https://en.wikipedia.org/wiki/Internet_activism_during_the_2009_Iranian_election_protests
  17. Mahjabin T. A survey of distributed denial-of-service attack, prevention, and mitigation techniques. Int. J. Distrib. Sensor Netw. 2017 2017 1463
    [Google Scholar]
  18. Schonfeld E. WikiLeaks reports it is under a denial of service attack. 2017 Available From: https://techcrunch.com/2010/11/28/ WikiLeaks-DDoS-attack/
  19. Specht S.M. Lee R.B. Distributed denial of service: Taxonomies of attacks, tools, and countermeasures. Proceedings of the ISCA 17th international conference on parallel and distributed computing systems (PDCS 2004), international workshop on security in parallel and distributed systems 15-17 September, 2004 San Francisco, CA 2004 543 550
    [Google Scholar]
  20. Patrick N.W. Call flooding attack. 2009 Available From: http://www.networkworld.com/article/2234402/cisco-subnet/callflooding-attack.html
  21. Lee R. Slowloris HTTP DoS. 2009 Available From: https://gist.github.com/steakknife/1865841
  22. RioRey Taxonomy of DDoS attacks. 2015 Available From: https://www.riorey.com/types-of-ddos-attacks#:~:text=DDoS%20attackers%20take%20advantage%20of,%2C%20CPU%2C%20etc
  23. Park J. Iwai K. Tanaka H. Analysis of slow read DoS attack. Proceedings of the 2014 International Symposium on Information Theory and its Applications (ISITA) 26-29 October 2014 Melbourne, VIC, Australia 2014 60 64
    [Google Scholar]
  24. Srivastava A. Gupta B. Tyagi A. A recent survey on DDoS attacks and defense mechanisms. Advances in parallel distributed computing. Nagamalai D. Renault E. Dhanuskodi M. Berlin, Heidelberg Springer 2011 570 580 10.1007/978‑3‑642‑24037‑9_57
    [Google Scholar]
  25. EUROCON DoS attacks and countermeasures. 2017 Available From: https://sites.google.com/a/pccare.vn/it/security-pages/dosattacks-and-countermeasures
  26. Deng J. Meng K. Xiao Y. Implementation of dos attack and mitigation strategies in IE 802.11b/g WLAN. Proceedings of SPIE defense security and sensing 5–9 April 2010 Orlando, FL 2010
    [Google Scholar]
  27. Du X. Guizani M. Xiao Y. Defending DoS attacks on broadcast authentication in wireless sensor networks. Proceedings of the IEEE International Conference on Communications 19-23 May 2008 Beijing, China 2008 1653 1657 10.1109/ICC.2008.319
    [Google Scholar]
  28. Peng T. Leckie C. Ramamohanarao K. Survey of network-based defense mechanisms countering the DoS and DDoS problems. ACM Comput. Surv. 2007 39 1 3 10.1145/1216370.1216373
    [Google Scholar]
  29. Mansfield-Devine S. DDoS: Threats and mitigation. Netw. Secur. 2011 2011 12 5 12 10.1016/S1353‑4858(11)70128‑3
    [Google Scholar]
  30. Srivastava A. Gupta B. Tyagi A. A recent survey on DDoS attacks and defense mechanisms. Advances in parallel distributed computing. Nagamalai D. Renault E. Dhanuskodi M. Berlin, Heidelberg Springer 2011 570 580 10.1007/978‑3‑642‑24037‑9_57
    [Google Scholar]
  31. Graham-Cumming J. Understanding and mitigating NTP-based DDoS attacks. San Francisco, CA Cloudflare, Inc. 2014 Vol. 9
    [Google Scholar]
  32. Wikipedia Distributed denial-of-service attacks on root nameservers—Wikipedia, the free encyclopedia. 2017 Available From: https://en.wikipedia.org/w/index.php?title=Distributed_
  33. DNS DNS products trusted by the world’s most admired digital brands. 2017 Available From: http://dyn.com/dns/
  34. Limer E. How hackers wrecked the internet using DVRs and webcams. 2016 Available From: http://www.popularmechanics.com/ technology/infrastructure/a23504/mirai-botnet-internetof-things-ddos-attack/
  35. Statistica Internet of Things (IoT): Number of connected devices worldwide from 2012 to 2020. 2017 Available From: https:// www.statista.com/statistics/471264/iot-number-of-connec ted-devices-worldwide/
  36. Akamei Akamais [state of the internet]/security Q4 2016 executive summary. 2017 Available From: https://www.akamai.com/us/ en/multimedia/documents/state-of-the-internet/q4-2016- state-of-the-internet-security-executive-summary.pdf
  37. Baker F. Requirements for IP version 4 routers. 1995 Available From: https://datatracker.ietf.org/doc/rfc1812/
  38. Zhenhai Duan Xin Yuan Chandrashekar J. Controlling IP spoofing through interdomain packet filters. IEEE Trans. Depend. Secure Comput. 2008 5 1 22 36 10.1109/TDSC.2007.70224
    [Google Scholar]
  39. Li J. Mirkovic J. Wang M. SAVE source address validity enforcement protocol. Proceedings of the 21st annual joint conference of the IEEE computer and communications societies (INFOCOM 2002) 23-27 June 2002 New York 2002
    [Google Scholar]
  40. Jin C. Wang H. Shin K.G. Hop-count filtering: An effective defense against spoofed DDoS traffic. Proceedings of the 10th ACM conference on computer and communications security Washington, DC 2003 30 41 10.1145/948109.948116
    [Google Scholar]
  41. Peng T. Leckie C. Ramamohanarao K. Protection from distributed denial of service attacks using history-based IP filtering. Proceedings of the IEEE International Conference on Communications 11-15 May 2003 Anchorage, AK 2003 10.1109/ICC.2003.1204223
    [Google Scholar]
  42. Yaar A. Perrig A. Song D. Pi: A path identification mechanism to defend against DDoS attacks. Proceedings of the 2003 symposium on security and privacy Berkeley, CA 2003 93 107 10.1109/SECPRI.2003.1199330
    [Google Scholar]
  43. Yaar A. Perrig A. Song D. StackPi: New packet marking and filtering mechanisms for DDoS and IP spoofing defense. IEEE J. Sel. Areas Comm. 2006 24 10 1853 1863 10.1109/JSAC.2006.877138
    [Google Scholar]
  44. Beverly R. Berger A. Hyun Y. Understanding the efficacy of deployed internet source address validation filtering. Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference Chicago, IL 2009 356 369 10.1145/1644893.1644936
    [Google Scholar]
  45. Yoohwan Kim Chao H.J. Chuah M.C. PacketScore: A statistics-based packet filtering scheme against distributed denial-of-service attacks. IEEE Trans. Depend. Secure Comput. 2006 3 2 141 155 10.1109/TDSC.2006.25
    [Google Scholar]
  46. Adkins D. Lakshminarayanan K. Perrig A. Towards a more functional and secure network infrastructure. Technical report no. UCB/CSD-03-1242. Berkeley University of California 2003
    [Google Scholar]
  47. Keromytis A.D. Misra V. Rubenstein D. SOS: Secure overlay services. Comput. Commun. Rev. 2002 32 4 61 72 10.1145/964725.633032
    [Google Scholar]
  48. Xianjun Geng Whinston A.B. Defeating distributed denial of service attacks. IT Prof. 2000 2 4 36 42 10.1109/6294.869381
    [Google Scholar]
  49. Sun B. Osborne L. Xiao Y. Guizani S. Intrusion detection techniques in mobile ad hoc and wireless sensor networks. IEEE Wirel. Commun. 2007 14 5 56 63 10.1109/MWC.2007.4396943
    [Google Scholar]
  50. Paxson V. Bro: A system for detecting network intruders in real-time. Comput. Netw. 1999 31 23-24 2435 2463 10.1016/S1389‑1286(99)00112‑7
    [Google Scholar]
  51. Cabrera J.B. Lewis L. Qin X. Proactive detection of distributed denial of service attacks using mib traffic variables - a feasibility study. 2001 IEEE/IFIP International Symposium on Integrated Network Management 14-18 May 2001 Seattle, USA 2001
    [Google Scholar]
  52. Roesch M. Snort: Lightweight intrusion detection for networks. Proceedings of the 13th USENIX conference on system administration Seattle, WA 1999 229 238
    [Google Scholar]
  53. Cheng C.M. Kung H. Tan K.S. Use of spectral analysis in defense against DoS attacks. Proceedings of the IEEE Global Telecommunications Conference 17-21 November 2002 Taipei, Taiwan 2002 10.1109/GLOCOM.2002.1189011
    [Google Scholar]
  54. Hussain A. Heidemann J. Papadopoulos C. A framework for classifying denial of service attacks. Proceedings of the 2003 conference on applications, technologies, architectures, and protocols for computer communications Karlsruhe 2003 99 110 New York ACM 10.1145/863955.863968
    [Google Scholar]
  55. Hussain A. Heidemann J. Papadopoulos C. Identification of repeated denial of service attacks. Proceedings of the 25th IEEE International Conference on computer communications (INFOCOM 2006) Barcelona 2006 1 15 10.1109/INFOCOM.2006.126
    [Google Scholar]
  56. Jow J. Xiao Y. Han W. A survey of intrusion detection systems in smart grid. Int J Sensor Netw 2017 23 3 170 186 10.1504/IJSNET.2017.083410
    [Google Scholar]
  57. Naoumi S. Bazzi A. Bomfin R. Chafii M. Complex Neural Network based Joint AoA and AoD Estimation for Bistatic ISAC. IEEE J. Sel. Top. Signal Process. 2024 1 15 10.1109/JSTSP.2024.3387299
    [Google Scholar]
  58. Delamou M. Deep Learning-based Estimation for Multitarget Radar Detection. 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring) 20-23 June 2023 Florence, Italy 2023 10.1109/VTC2023‑Spring57618.2023.10200157
    [Google Scholar]
  59. Naoumi S. Deep Learning-Enabled Angle Estimation in Bistatic ISAC Systems. 2023 IEEE Globecom Workshops. Kuala Lumpur, Malaysia 2023 854 859 10.1109/GCWkshps58843.2023.10464930
    [Google Scholar]
  60. Jiang D. Xu Z. Zhang P. Zhu T. A transform domain-based anomaly detection approach to network-wide traffic. J. Netw. Comput. Appl. 2014 40 292 306 10.1016/j.jnca.2013.09.014
    [Google Scholar]
  61. Ma X. Chen Y. DDoS detection method based on chaos analysis of network traffic entropy. IEEE Commun. Lett. 2014 18 1 114 117 10.1109/LCOMM.2013.112613.132275
    [Google Scholar]
  62. Savage S. Wetherall D. Karlin A. Anderson T. Practical network support for IP traceback. Comput. Commun. Rev. 2000 30 4 295 306 10.1145/347057.347560
    [Google Scholar]
  63. Chen R Park JM Marchany R Track: A novel approach for defending against distributed denial-of-service attacks. 2005 Available From: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=63770920aa42eedc2ae23e5e728ba61610332959
  64. Dean D. Franklin M. Stubblefield A. An algebraic approach to IP traceback. ACM Trans. Inf. Syst. Secur. 2002 5 2 119 137 10.1145/505586.505588
    [Google Scholar]
  65. Song D.X. Perrig A. Advanced and authenticated marking schemes for IP traceback. Proceedings of the 20th annual joint conference of the IEEE Computer and Communications Societies (INFOCOM 2001) Anchorage, AK 2001 878 886 10.1109/INFCOM.2001.916279
    [Google Scholar]
  66. Law T.K.T. Lui J.C.S. Yau D.K.Y. You can run, but you can’t hide: An effective statistical methodology to trace back DDoS attackers. IEEE Trans. Parallel Distrib. Syst. 2005 16 9 799 813 10.1109/TPDS.2005.114
    [Google Scholar]
  67. Goodrich MT Probabilistic packet marking for large-scale IP traceback. IEEE/ACM Transac. Netw. 2008 16 1 15 24 10.1109/TNET.2007.910594
    [Google Scholar]
  68. Tian H. Bi J. Jiang X. A probabilistic marking scheme for fast traceback. Proceedings of the 2010 2nd International Conference on Evolving Internet (INTERNET) Valencia 2010 137 141 10.1109/INTERNET.2010.32
    [Google Scholar]
  69. Fadlallah A. Adaptive probabilistic packet marking scheme for IP traceback. Proceedings of the 2014 World Congress on Computer Applications and Information Systems (WCCAIS) Hammamet, Tunisia 2014 1 5 10.1109/WCCAIS.2014.6916548
    [Google Scholar]
  70. Yu S. Distributed denial of service attack and defense. New York Springer 2014 10.1007/978‑1‑4614‑9491‑1
    [Google Scholar]
  71. Belenky A. Ansari N. IP traceback with deterministic packet marking. IEEE Commun. Lett. 2003 7 4 162 164 10.1109/LCOMM.2003.811200
    [Google Scholar]
  72. Belenky A. Ansari N. Tracing multiple attackers with deterministic packet marking (DPM). Proceedings of the 2003 IEEE Pacific Rim Conference on Communications, computers, and Signal Processing 28-30 August 2003 Victoria, BC, Canada 2003 49 52 10.1109/PACRIM.2003.1235716
    [Google Scholar]
  73. Yang Xiang Wanlei Zhou Minyi Guo Flexible deterministic packet marking: An IP traceback. system to find the real source of attacks. IEEE Trans. Parallel Distrib. Syst. 2009 20 4 567 580 10.1109/TPDS.2008.132
    [Google Scholar]
  74. Yu S. Zhou W. Guo S. A dynamical deterministic packet marking scheme for DDoS traceback. Proceedings of the 2013 IEEE Global Communications Conference (GLOBECOM) Atlanta, GA 2013 729 734
    [Google Scholar]
  75. Yu S. Zhou W. Guo S. Guo M. A feasible IP traceback framework through dynamic deterministic packet marking. IEEE Trans. Comput. 2016 65 5 1418 1427 10.1109/TC.2015.2439287
    [Google Scholar]
  76. Bellovin S.M. Leech M. Taylor T. ICMP traceback messages. 2003 Available From: https://academiccommons.columbia. edu/catalog/ac:127253
  77. Saurabh S. Sairam A.S. ICMP based IP traceback with negligible overhead for highly distributed reflector attack using bloom filters. Comput. Commun. 2014 42 60 69 10.1016/j.comcom.2014.01.003
    [Google Scholar]
  78. Yao G. Bi J. Vasilakos A.V. Passive IP traceback: Disclosing the locations of IP spoofers from path backscatter. IEEE Trans. Inf. Forensics Security 2015 10 3 471 484 10.1109/TIFS.2014.2381873
    [Google Scholar]
  79. Poonia L. Tinker S. DDoS Mitigation by Software-Defined Network (SDN) in the Context of ICMP And SYP Approach. Int J Intell Syst Appl Eng 2023 12 1 173 182
    [Google Scholar]
  80. Yang X. Wetherall D. Anderson T. A DoS-limiting network architecture. Comput. Commun. Rev. 2005 35 4 241 252 10.1145/1090191.1080120
    [Google Scholar]
  81. Liu X. Yang X. Xia Y. NetFence. Comput. Commun. Rev. 2010 40 4 255 266 10.1145/1851275.1851214
    [Google Scholar]
  82. Menth M. Martin R. Charzinski J. Capacity overprovisioning for networks with resilience requirements. Comput. Commun. Rev. 2006 36 4 87 98 10.1145/1151659.1159925
    [Google Scholar]
  83. Naili M. Achroufene A. Naili M. Election-based method for fault tolerance in a hierarchical sensor network (EFTOHSN): A case study of an indoor localisation system. Int J Sensor Netw 2016 22 3 158 165 10.1504/IJSNET.2016.080202
    [Google Scholar]
  84. Sivasubramanian S. Szymaniak M. Pierre G. Steen M. Replication for web hosting systems. ACM Comput. Surv. 2004 36 3 291 334 10.1145/1035570.1035573
    [Google Scholar]
  85. Yan J. Early S. Anderson R. The Xenoservice—a distributed defeat for distributed denial of service. Seman. Sch. 2000
    [Google Scholar]
  86. Al-Haidari F. Sqalli M.H. Salah K. Enhanced EDoS-shield for mitigating DDoS attacks originating from spoofed IP addresses. Proceedings of the 2012 IEEE 11th International Conference on Trust, security and Privacy in Computing and Communications (TrustCom) 25-27 June 2012 Liverpool, UK 2012 10.1109/TrustCom.2012.146
    [Google Scholar]
  87. Karnwal T. Sivakumar T. Aghila G. A comber approach to protect cloud computing against XML DDoS and HTTP DDoS attack. 2012 IEEE Students' Conference on Electrical, Electronics and Computer Science. 01-02 March 2012 Bhopal, India 2012 10.1109/SCEECS.2012.6184829
    [Google Scholar]
  88. Sqalli M.H. Al-Haidari F. Salah K. EDoS-shield—a two-step mitigation technique against EDoS attacks in cloud computing. Proceedings of the 2011 4th IEEE International Conference on Utility and Cloud Computing (UCC) Victoria, NSW, Australia 2011 49 56 10.1109/UCC.2011.17
    [Google Scholar]
  89. Jia Q. Wang H. Fleck D. Catch me if you can: A cloud-enabled DDoS defense. 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks. 23-26 June 2014 Atlanta, GA, USA 2014 10.1109/DSN.2014.35
    [Google Scholar]
  90. Wang H. Jia Q. Fleck D. Powell W. Li F. Stavrou A. A moving target DDoS defense mechanism. Comput. Commun. 2014 46 10 21 10.1016/j.comcom.2014.03.009
    [Google Scholar]
  91. Baig Z.A. Binbeshr F. Controlled Virtual Resource Access to Mitigate Economic Denial of Sustainability (EDoS) Attacks against Cloud Infrastructures. 2013 International Conference on Cloud Computing and Big Data 16-19 December 2013 Fuzhou, China 2013
    [Google Scholar]
  92. Saini B. Somani G. Index page-based EDoS attacks in infrastructure cloud. Recent Trends in Computer Networks and Distributed Systems Security Berlin, Heidelberg SpringerLink 2014 10.1007/978‑3‑642‑54525‑2_34
    [Google Scholar]
  93. Idziorek J. Tannian M. Jacobson D. Detecting fraudulent use of cloud resources. Proceedings of the 3rd ACM workshop on cloud computing security workshop Chicago, IL 2011 61 72 10.1145/2046660.2046676
    [Google Scholar]
  94. Ismail M.N. Aborujilah A. Musa S. Detecting flooding based DoS attack in cloud computing environment using covariance matrix approach. Proceedings of the 7th international conference on ubiquitous information management and communication Kota Kinabalu, Malaysia 2013 36 10.1145/2448556.2448592
    [Google Scholar]
  95. Latanicki J. Massonet P. Naqvi S. Scalable cloud defenses for detection, analysis and mitigation of DDoS attacks. 2010 Available From: http://www. future-internet.eu/
  96. Yu S. Tian Y. Guo S. Wu D.O. Can we beat DDoS attacks in clouds? IEEE Trans. Parallel Distrib. Syst. 2014 25 9 2245 2254 10.1109/TPDS.2013.181
    [Google Scholar]
  97. Wang B. Zheng Y. Lou W. Hou Y.T. DDoS attack protection in the era of cloud computing and Software-Defined Networking. Comput. Netw. 2015 81 308 319 10.1016/j.comnet.2015.02.026
    [Google Scholar]
  98. Wang X. Chen M. Xing C. SDSNM: A softwaredefined security networking mechanism to defend against DDoS attacks. Proceedings of the 2015 9th international conference on frontier of computer science and technology (FCST) Dalian, China 2015 115 121 10.1109/FCST.2015.27
    [Google Scholar]
  99. Aloul F. Al-Ali A.R. Al-Dalky R. Al-Mardini M. El-Hajj W. Smart grid security: Threats, vulnerabilities, and solutions. Int J Smart Grid Clean Energy 2012 1 1 1 6 10.12720/sgce.1.1.1‑6
    [Google Scholar]
  100. Lu Z. Lu X. Wang W. Review and evaluation of security threats on the communication networks in the smart grid. Proceedings of the military communications conference 31 October 2010 - 03 November 2010 San Jose, CA, USA 2010 1830 1835 10.1109/MILCOM.2010.5679551
    [Google Scholar]
  101. Wang W. Lu Z. Cyber security in the Smart Grid: Survey and challenges. Comput. Netw. 2013 57 5 1344 1371 10.1016/j.comnet.2012.12.017
    [Google Scholar]
  102. Laxmi Poonia E. DDoS Mitigation by Blockchain With Approach of Cost Model. Int. J. Recent Innov. Trends Comput. Commun. 2023 11 9 3873 3880 10.17762/ijritcc.v11i9.9644
    [Google Scholar]
  103. Liu J. Xiao Y. Li S. Liang W. Chen C.L.P. Cyber security and privacy issues in smart grids. IEEE Commun. Surv. Tutor. 2012 14 4 981 997 10.1109/SURV.2011.122111.00145
    [Google Scholar]
  104. Sheng Y. Tan K. Chen G. Detecting 802.11 MAC layer spoofing using received signal strength. Proceedings of the 27th conference on computer communications (INFOCOM 2008) Phoenix, AZ 2008 1768 1776 10.1109/INFOCOM.2008.239
    [Google Scholar]
  105. Xu W. Trappe W. Zhang Y. The feasibility of launching and detecting jamming attacks in wireless networks. Proceedings of the 6th ACM international symposium on mobile ad hoc networking and computing Urbana-Champaign, IL 2005 46 57 10.1145/1062689.1062697
    [Google Scholar]
  106. Li M. Koutsopoulos I. Poovendran R. Optimal jamming attacks and network defense policies in wireless sensor networks. Proceedings of the 26th IEEE International Conference on computer communications (INFOCOM 2007) Barcelona 2007 1307 1315 10.1109/INFCOM.2007.155
    [Google Scholar]
  107. Bazzi A. Chafii M. Secure Full Duplex Integrated Sensing and Communications. IEEE Trans. Inf. Forensics Security 2024 19 2082 2097 10.1109/TIFS.2023.3346696
    [Google Scholar]
  108. Nunes G. Sony Bravia—remote denial of service. 2012 Available From: https://www.exploit-db.com/exploits/18705/
  109. Yoon S. Park H. Yoo H.S. Security issues on smart home in IoT environment. Computer science and its applications. Park J. Stojmenovic I. Jeong H. Berlin, Heidelberg Springer 2015 691 696 10.1007/978‑3‑662‑45402‑2_97
    [Google Scholar]
  110. Heer T. Garcia-Morchon O. Hummen R. Keoh S.L. Kumar S.S. Wehrle K. Security challenges in the IP-based Internet of things. Wirel. Pers. Commun. 2011 61 3 527 542 10.1007/s11277‑011‑0385‑5
    [Google Scholar]
/content/journals/eng/10.2174/0118722121322166240828112546
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A Comprehensive Analysis of the Types, Impacts, Prevention, and Mitigation of DDoS Attacks
Bentham Science Publishers ; https://doi.org/10.2174/0118722121322166240828112546
/content/journals/eng/10.2174/0118722121322166240828112546
/content/journals/eng/10.2174/0118722121322166240828112546
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  • Article Type:     Research Article
Keywords: Distributed denial of services ; mitigation ; Internet of things ; network ; Botnet

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