Relevant bibliographies by topics / Flooding distributed denial of service attacks

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Flooding distributed denial of service attacks'

Author: Grafiati
Published: 7 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Flooding distributed denial of service attacks"

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Wang, Haojun. "Distributed Denial of Service Attack with Large Language Model." Highlights in Science, Engineering and Technology 138 (May 11, 2025): 132–37. https://doi.org/10.54097/586gg060.

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Distributed Denial of Service (DDoS) attacks take full advantage of distributed networks by sending a relentless barrage of requests to a target server to disrupt the regular operation of the server. The main difference between a DDoS attack and a traditional Denial of Service (DoS) attack is its decentralized nature. This characteristic increases the attack's impact and thus creates incredible difficulty in prevention. Traditional DDoS strategies cover flooding attacks (e.g., TCP SYN and UDP floods), protocol usage techniques (e.g., SYN floods and the infamous Ping of Death), and resource exh
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Ali, Raza. "Detection of DDoS attack in cloud computing and its prevention: a systematic review." i-manager’s Journal on Cloud Computing 9, no. 1 (2022): 1. http://dx.doi.org/10.26634/jcc.9.1.18542.

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Cloud computing is one of the latest and greatest environments for delivering Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS) in digital communications infrastructure. Cloud computing helps the user remotely access the required service as needed through the Internet. But this technological advancement, due to its remote availability in the cloud, leads to new attacks. One of the biggest threats to cloud infrastructure is Distributed Denial of Service (DDoS) flooding attacks. DDoS flooding attacks are clearly trying to exploit the availability
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Nashat, Dalia, Fatma A. Hussain, and Xiaohong Jiang. "Detection of Distributed Denial of Service Flooding Attack Using Odds Ratio." Journal of Networking and Network Applications 1, no. 2 (2021): 67–74. http://dx.doi.org/10.33969/j-nana.2021.010204.

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Computer networks are vulnerable to many types of attacks while the Distributed Denial of Service attack (DDoS) serves as one of the top concerns for security professionals. The DDoS flooding attack denies the services by consuming the server resources to prevent the legitimate users from using their desired services. The hardness of detecting this attack lies in sending a stream of packets to the server with spoofed IP addresses, so that the internet routing infrastructure cannot distinguish the spoofed packets. Based on the odds ratio (OR) statistical measurement, in this work we propose a n
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Ghazali. "Flooding Distributed Denial of Service Attacks-A Review." Journal of Computer Science 7, no. 8 (2011): 1218–23. http://dx.doi.org/10.3844/jcssp.2011.1218.1223.

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SINGH, SATWINDER, ABHINAV BHANDARI, KRISHAN KUMAR SALUJA, and A. L. SANGAL. "Study to Validate the Performance of Flooding Based Distributed Denial of Service Attacks." International Journal of Computer Networks and Communications Security 8, no. 1 (2020): 1–9. http://dx.doi.org/10.47277/ijcncs/8(1)1.

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Network technology has experienced explosive growth in the past decades. The generally accepted viewpoint in the security world is that no system or network is totally protected which makes network security an important concern. The work done in this paper focuses on Distributed Denial of Service Attacks (DDoS) where legitimate users are prevented from accessing network services. Distributed Denial of Service (DDoS) Attacks has been increasingly found to be disturbing the normal working of organizations causing billions of rupees of losses. Organizations are trying their best to reduce their l
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Ramli, Hartini, and Maharaja Yasin Alifsyah. "Analisis Keamanan Komputer Terhadap Serangan Distributed Denial of Service (DDOS)." Journal of Renewable Energy and Smart Device 1, no. 1 (2023): 25–30. http://dx.doi.org/10.61220/joresd.v1i1.235.

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Distributed Denial of Service (DDoS) is a type of active attack, an attack that can overwhelm a system by flooding a computer or server with network traffic, disrupting user services. The goal of this attack is usually to disable services and disconnect from the compromised­­­­­­­­ computer or network. The impact is very large for companies or agencies that offer services. Victims of these attacks are unable to provide the services they are supposed to. Due to a bug or constraint on the server you are trying to use and one of the ways to deal with these attacks is to use a computer network fir
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R., Ramkumar, Rahul R., and Gowtham Sri. "Anomaly Based Approach for Defending Denial of Service Attack in Web Traffic." COMPUSOFT: An International Journal of Advanced Computer Technology 04, no. 04 (2015): 1657–64. https://doi.org/10.5281/zenodo.14776346.

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Distributed Denial of Service (DDOS) attacks has become a great threat for internet security. This attackis an advanced form of DOS (Denial of Service) attack. This attack changes its whole origin ID and it gives trouble to find it out and it has become a serious threat for internet security. Almost all traditional services such as bank websites, power resources, medical, educational institutions and military are extended to World Wide Web and thus many people widely use internet services. As many users of Internet is mandatory, network security for attacks are also increasing. Current DDoS at
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Khalaf, Bashar Ahmad, Salama A. Mostafa, Aida Mustapha, et al. "An Adaptive Protection of Flooding Attacks Model for Complex Network Environments." Security and Communication Networks 2021 (April 22, 2021): 1–17. http://dx.doi.org/10.1155/2021/5542919.

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Currently, online organizational resources and assets are potential targets of several types of attack, the most common being flooding attacks. We consider the Distributed Denial of Service (DDoS) as the most dangerous type of flooding attack that could target those resources. The DDoS attack consumes network available resources such as bandwidth, processing power, and memory, thereby limiting or withholding accessibility to users. The Flash Crowd (FC) is quite similar to the DDoS attack whereby many legitimate users concurrently access a particular service, the number of which results in the
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Saurabh Kansal. "DISTRIBUTED DENIAL OF SERVICE ATTACK MITIGATION USING REINFORCEMENT LEARNING." Journal of Sustainable Solutions 2, no. 1 (2025): 11–18. https://doi.org/10.36676/j.sust.sol.v2.i1.54.

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Cybersecurity is threatened by Distributed Denial of Service (DDoS) attacks that destabilize network services by flooding systems with wrongful traffic. Unlike more conventional threat countermeasures, they fail to manage dynamic attack trajectories. In contrast, reinforcement learning provides a dynamic approach since systems improve their learning and response to the emerging threats in a real-time exercise. In this paper, reinforcement learning is used to study DDoS attack prevention and the study including the method, data set and measure used is discussed. Primary conclusions confirm stra
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Narote, Prof Amit, Vamika Zutshi, Aditi Potdar, and Radhika Vichare. "D-Dos Attack Prediction Using Machine Learning Algorithms." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (2022): 2303–12. http://dx.doi.org/10.22214/ijraset.2022.41131.

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Abstract: The risk of cyber-attack keeps on growing irrespective of development of new technologies for protection. One of the most frequent cyber-attacks is the DOS attack. A Denial-of-Service (DoS) attack is an attack which tries to shut down a machine or network, by flooding the target with unwanted traffic or triggers a crash by sending it some information, which makes it challenging for the users to access their network. A higher version of DoS attacks is the DDoS attacks that have recently become quite severe in security companies. Many organizations have begun facing these issues. Such
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Dissertations / Theses on the topic "Flooding distributed denial of service attacks"

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Namuduri, Sarita. "Distributed Denial of Service Attacks (DDoS)- Consequences and Future." Thesis, Linköping University, Department of Electrical Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8055.

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<p>Denial of Service and the Distributed Denial of Service Attacks have recently emerged as one of the most newsworthy, if not the greatest, weaknesses of the Internet. This paper attempt to explain how they work, why they are hard to combat today, and what will need to happen if they are to be brought under control. It is divided into eight sections. The first is an overview of the current situation and also brief explanatory of the rest of the chapters being covered. The second is a detailed description of exactly how this attack works, and why it is hard to cope with today; of necessity it
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Ramanauskaitė, Simona. "Modelling and Research of Distributed Denial of Service Attacks." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2012. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120723_105031-70003.

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In the dissertation the Denial of Service (DoS) attacks and their models are investigated. DoS attack is a type of cyber attacks when an attacker tries to deny a service in the network machine. There are many types of DoS attacks, and therefore the main object of the dissertation is specified as distributed denial of service (DDoS) attacks. DDoS uses multiple agents at the same time to exhaust certain resources of network machine and make it unavailable. The importance of DDoS attacks can be explained on the basis of the following facts: nowadays there are no countermeasures which can ensure f
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Thing, Vrizlynn Ling Ling. "Adaptive Response System for Distributed Denial-of-Service Attacks." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/4264.

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The continued prevalence and severe damaging effects of the Distributed Denial of Service (DDoS) attacks in today’s Internet raise growing security concerns and call for an immediate response to come up with better solutions to tackle DDoS attacks. The current DDoS prevention mechanisms are usually inflexible and determined attackers with knowledge of these mechanisms, could work around them. Most existing detection and response mechanisms are standalone systems which do not rely on adaptive updates to mitigate attacks. As different responses vary in their “leniency” in treating detected at
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Karandikar, Sampada. "Analysis of distributed denial of service attacks and countermeasures." Connect to this title online, 2009. http://etd.lib.clemson.edu/documents/1263409912/.

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Bhatia, Sajal. "Detecting distributed Denial-of-Service attacks and Flash Events." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/62031/1/Sajal_Bhatia_Thesis.pdf.

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This thesis investigates and develops techniques for accurately detecting Internet-based Distributed Denial-of-Service (DDoS) Attacks where an adversary harnesses the power of thousands of compromised machines to disrupt the normal operations of a Web-service provider, resulting in significant down-time and financial losses. This thesis also develops methods to differentiate these attacks from similar-looking benign surges in web-traffic known as Flash Events (FEs). This thesis also addresses an intrinsic challenge in research associated with DDoS attacks, namely, the extreme scarcity of publi
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Eklund, Martin, and Patrik Ståhlberg. "Distributed denial of service attacks : Protection, Mitigation, and Economic Consequences." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-170924.

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Distributed Denial of Service attacks is a problem that constantly threatens companies that rely on the internet for major parts of their business. A successful DDoS attack that manages to penetrate a company’s network can lead to devastating damages in the form of lost income, reduced productivity, increase in costs, and damage to the company’s image and reputation. The different DDoS attacks are many and of different character and often Offer different parts of the network, which makes it very difficult to defend against. It is also very clear that DDoS attacks are increasing in both numbers
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Li, Chi-Pan. "A distributed scheme to detect and defend against distributed denial of service attacks /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?COMP%202003%20LI.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.<br>Includes bibliographical references (leaves 102-107). Also available in electronic version. Access restricted to campus users.
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Negi, Chandan Singh. "Using network management systems to detect Distributed Denial of Service Attacks." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA397257.

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Thesis (M.S. in Information Systems Technology and M.S. in Computer Science)--Naval Postgraduate School, Sept. 2001.<br>Thesis advisors, Bordetsky, Alex ; Clark, Paul. "September 2001." Includes bibliographical references (p. 115-117). Also available in print.
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McNevin, Timothy John. "Mitigating Network-Based Denial-of-Service Attacks with Client Puzzles." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/31941.

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Over the past few years, denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks have become more of a threat than ever. These attacks are aimed at denying or degrading service for a legitimate user by any means necessary. The need to propose and research novel methods to mitigate them has become a critical research issue in network security. Recently, client puzzle protocols have received attention as a method for combating DoS and DDoS attacks. In a client puzzle protocol, the client is forced to solve a cryptographic puzzle before it can request any operation from a rem
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Vordos, Ioannis. "Mitigating distributed denial of service attacks with Multiprotocol Label Switching--Traffic Engineering (MPLS-TE)." Thesis, Monterey, Calif. : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/March/09Mar%5FVordos.pdf.

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Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 2009.<br>Thesis Advisor(s): Xie, Geoffry. "March 2009." Description based on title screen as viewed on April 23, 2009. Author(s) subject terms: Traffic Engineering, Distributed Denial of Service Attacks, Sinkhole Routing, Blackhole Routing. Includes bibliographical references (p. 115-119). Also available in print.
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Books on the topic "Flooding distributed denial of service attacks"

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Brooks, Richard R., and İlker Özçelik. Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125.

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Singh, Rajeev, and Mangey Ram, eds. Distributed Denial of Service Attacks. De Gruyter, 2021. http://dx.doi.org/10.1515/9783110619751.

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Distributed Denial of Service Attacks. Taylor & Francis Group, 2020.

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Gupta, Brij B., and Amrita Dahiya. Distributed Denial of Service (DDoS) Attacks. CRC Press, 2021. http://dx.doi.org/10.1201/9781003107354.

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Distributed Denial of Service (ddos) Attacks. Taylor & Francis Group, 2021.

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Gupta, Brij B., and Amrita Dahiya. Distributed Denial of Service Attacks: Classification, Attacks, Challenges and Countermeasures. Taylor & Francis Group, 2021.

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Gupta, Brij B., and Amrita Dahiya. Distributed Denial of Service Attacks: Classification, Attacks, Challenges and Countermeasures. Taylor & Francis Group, 2021.

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Gupta, Brij B., and Amrita Dahiya. Distributed Denial of Service Attacks: Classification, Attacks, Challenges and Countermeasures. Taylor & Francis Group, 2021.

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Gupta, Brij B., and Amrita Dahiya. Distributed Denial of Service Attacks: Classification, Attacks, Challenges and Countermeasures. Taylor & Francis Group, 2021.

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Ram, Mangey, and Rajeev Singh. Distributed Denial of Service Attacks: Concepts, Mathematical and Cryptographic Solutions. de Gruyter GmbH, Walter, 2021.

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Book chapters on the topic "Flooding distributed denial of service attacks"

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Khandare, Hrishikesh, Saurabh Jain, and Rajesh Doriya. "A Survey on HTTP Flooding—A Distributed Denial of Service Attack." In Pervasive Computing and Social Networking. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2840-6_4.

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Yang, Guosong, and João P. Hespanha. "Modeling and Mitigating Link-Flooding Distributed Denial-of-Service Attacks via Learning in Stackelberg Games." In Handbook of Reinforcement Learning and Control. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-60990-0_15.

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Brooks, Richard R., and İlker Özçelik. "Introduction." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-1.

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Brooks, Richard R., and İlker Özçelik. "Attack Mitigation." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-10.

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Demirci, Mehmet. "Security and DDoS in SDN: Opportunities and Challenges." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-11.

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Biron, Zoleikha Abdollahi, and Pierluigi Pisu. "Denial of Service Attack in Control Systems." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-12.

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Arunagirinathan, Paranietharan, Richard R. Brooks, Iroshani Jayawardene, et al. "Denial of Service Attack on Phasor Measurement unit 1." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-13.

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Brooks, Richard R., and İlker Özçelik. "DDoS Lab." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-14.

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Brooks, Richard R., and İlker Özçelik. "Conclusion." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-15.

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Zhong, Xingsi, and Oluwakemi Ade Aina. "Appendix." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-16.

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Conference papers on the topic "Flooding distributed denial of service attacks"

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Sardana, Jyotsana, Sunil Kumar, Dharminder Kumar, and Kamlesh Dutta. "Denial of Service (DoS) Attacks in SDN-Based VANETs: A Study." In 2024 Eighth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2024. https://doi.org/10.1109/pdgc64653.2024.10984030.

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Kharchouf, Ibtissam, Hossam M. Hussein, Mahmoud S. Abdelrahman, S. M. Sajjad Hossain Rafin, and Osama A. Mohammed. "Cyber-Physical Testbed for Distributed Consensus Control Amid Denial of Service Attacks." In 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE, 2024. http://dx.doi.org/10.1109/eeeic/icpseurope61470.2024.10751374.

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Ajeesh, Arunima, and Tessy Mathew. "NeuralGuard5G: Enhancing 5G Network Slice Security Against Distributed Denial of Service Attacks." In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit). IEEE, 2024. https://doi.org/10.1109/globalaisummit62156.2024.10947868.

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Tripathi, Sarvapriya, Himanshu Upadhyay, and Jayesh Soni. "Quantum Long Sort-Term Memory-based Identification of Distributed Denial of Service Attacks." In 2025 IEEE 4th International Conference on AI in Cybersecurity (ICAIC). IEEE, 2025. https://doi.org/10.1109/icaic63015.2025.10849228.

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Javadpour, Amir, Forough Ja'fari, Tarik Taleb, and Chafika Benzaïd. "5G Slice Mutation to Overcome Distributed Denial of Service Attacks Using Reinforcement Learning." In 2024 17th International Conference on Security of Information and Networks (SIN). IEEE, 2024. https://doi.org/10.1109/sin63213.2024.10871675.

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Singh, Jagendra, Jabir Ali, Preeti Sharma, Vinish Kumar, Meenakshi Sharma, and Ramendra Singh. "Mitigating Distributed Denial of Service (DDoS) Attacks in Cloud Networks Using Neural Networks." In 2024 Second International Conference on Advanced Computing & Communication Technologies (ICACCTech). IEEE, 2024. https://doi.org/10.1109/icacctech65084.2024.00036.

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Kunna, Etidal Altom, Mohd Nizam Omar, and Mohamad Fadli bin Zolkipli. "Detecting Distributed Denial of Service Attacks in Software Defined Network Controllers: Proposed Research." In 2024 7th International Conference on Internet Applications, Protocols, and Services (NETAPPS). IEEE, 2024. https://doi.org/10.1109/netapps63333.2024.10823571.

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Jiang, Hong, Shuqiao Chen, Hongchao Hu, and Mingming Zhang. "Superpoint-based detection against distributed denial of service (DDoS) flooding attacks." In 2015 IEEE International Workshop on Local and Metropolitan Area Networks (LANMAN). IEEE, 2015. http://dx.doi.org/10.1109/lanman.2015.7114724.

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Chinnasamy, P., Sai Devika, V. Balaji, S. Dhanasekaran, B. Jency A. Jebamani, and Ajmeera Kiran. "BDDoS: Blocking Distributed Denial of Service Flooding Attacks With Dynamic Path Detectors." In 2023 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2023. http://dx.doi.org/10.1109/iccci56745.2023.10128499.

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Ragu, V., and P. Jesu Jayarin. "Detecting flooding attacks in distributed denial of service attacks using deep neural network compared with naive bayes." In INTERNATIONAL CONFERENCE ON APPLICATION OF ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SOURCES AND ENVIRONMENTAL SUSTAINABILITY. AIP Publishing, 2025. https://doi.org/10.1063/5.0258744.

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Reports on the topic "Flooding distributed denial of service attacks"

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Mankins, David, Rajesh Krishnan, Ceilyn Boyd, John Zao, and Michael Frentz. Mitigating Distributed Denial of Service Attacks with Dynamic Resource Pricing. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada406438.

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Nir, Y., and V. Smyslov. Protecting Internet Key Exchange Protocol Version 2 (IKEv2) Implementations from Distributed Denial-of-Service Attacks. RFC Editor, 2016. http://dx.doi.org/10.17487/rfc8019.

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