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Relevant bibliographies by topics / Distributed denial-of-service attack (DDoS attacks)

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Academic literature on the topic 'Distributed denial-of-service attack (DDoS attacks)'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Distributed denial-of-service attack (DDoS attacks)"

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Kotey, Seth, Eric Tchao, and James Gadze. "On Distributed Denial of Service Current Defense Schemes." Technologies 7, no. 1 (2019): 19. http://dx.doi.org/10.3390/technologies7010019.

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Distributed denial of service (DDoS) attacks are a major threat to any network-based service provider. The ability of an attacker to harness the power of a lot of compromised devices to launch an attack makes it even more complex to handle. This complexity can increase even more when several attackers coordinate to launch an attack on one victim. Moreover, attackers these days do not need to be highly skilled to perpetrate an attack. Tools for orchestrating an attack can easily be found online and require little to no knowledge about attack scripts to initiate an attack. Studies have been done

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Sambangi, Swathi, and Lakshmeeswari Gondi. "A Machine Learning Approach for DDoS (Distributed Denial of Service) Attack Detection Using Multiple Linear Regression." Proceedings 63, no. 1 (2020): 51. http://dx.doi.org/10.3390/proceedings2020063051.

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The problem of identifying Distributed Denial of Service (DDos) attacks is fundamentally a classification problem in machine learning. In relevance to Cloud Computing, the task of identification of DDoS attacks is a significantly challenging problem because of computational complexity that has to be addressed. Fundamentally, a Denial of Service (DoS) attack is an intentional attack attempted by attackers from single source which has an implicit intention of making an application unavailable to the target stakeholder. For this to be achieved, attackers usually stagger the network bandwidth, hal

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K.M, Akhil, Rahul C.T, and Athira V.B. "Distributed Denial of Service (DDoS) Attacks and Defence Mechanism." International Journal of Computer Science and Mobile Computing 10, no. 3 (2021): 83–88. http://dx.doi.org/10.47760/ijcsmc.2021.v10i03.010.

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Denial of Service (DoS) attacks is one of the major threats to Internet sites and one of the major security problems Internet faces today. The nature of threats caused by Distributed Denial of Service (DDoS) attacks on networks. With little or no warning, a DDoS attack could easily destroy its victim's communication and network resources in a short period of time. This paper outlines the problem of DDoS attacks and developing a classification of DDoS attacks and DDoS defense mechanisms. Important features of each attack and defense system category are described and advantages and disadvantages

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Zhang, Chunming. "Impact of Defending Strategy Decision on DDoS Attack." Complexity 2021 (March 15, 2021): 1–11. http://dx.doi.org/10.1155/2021/6694383.

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Distributed denial-of-service (DDoS) attack is a serious threat to cybersecurity. Many strategies used to defend against DDoS attacks have been proposed recently. To study the impact of defense strategy selection on DDoS attack behavior, the current study uses logistic function as basis to propose a dynamic model of DDoS attacks with defending strategy decisions. Thereafter, the attacked threshold of this model is calculated. The existence and stability of attack-free and attacked equilibria are proved. Lastly, some effective strategies to mitigate DDoS attacks are suggested through parameter

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Mazur, Katarzyna, Bogdan Ksiezopolski, and Radoslaw Nielek. "Multilevel Modeling of Distributed Denial of Service Attacks in Wireless Sensor Networks." Journal of Sensors 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/5017248.

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The growing popularity of wireless sensor networks increases the risk of security attacks. One of the most common and dangerous types of attack that takes place these days in any electronic society is a distributed denial of service attack. Due to the resource constraint nature of mobile sensors, DDoS attacks have become a major threat to its stability. In this paper, we established a model of a structural health monitoring network, being disturbed by one of the most common types of DDoS attacks, the flooding attack. Through a set of simulations, we explore the scope of flood-based DDoS attack

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Singh, Rajeev, and T. P. Sharma. "Present Status of Distributed Denial of Service (DDoS) Attacks in Internet World." International Journal of Mathematical, Engineering and Management Sciences 4, no. 4 (2019): 1008–17. http://dx.doi.org/10.33889/ijmems.2019.4.4-080.

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Distributed Denial of Service (DDoS) attack harms the digital availability in Internet. The user’s perspective of getting quick and effective services may be badly hit by the DDoS attackers. There are several reports of DDoS attack incidences that have caused devastating effects on the user and web services in the Internet world. In the present digital world dominated by wireless, mobile and IoT devices, the numbers of users are increasing day by day. Most of the users are novice and therefore their devices either fell prey to DDoS attacks or unknowingly add themselves to the DDoS attack Army.

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Dhanapal, A., and P. Nithyanandam. "The Slow HTTP Distributed Denial of Service Attack Detection in Cloud." Scalable Computing: Practice and Experience 20, no. 2 (2019): 285–98. http://dx.doi.org/10.12694/scpe.v20i2.1501.

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Cloud computing became popular due to nature as it provides the flexibility to add or remove the resources on-demand basis. This also reduces the cost of investments for the enterprises significantly. The adoption of cloud computing is very high for enterprises running their online applications. The availability of online services is critical for businesses like financial services, e-commerce applications, etc. Though cloud provides availability, still these applications are having potential threats of going down due to the slow HTTP Distributed Denial of Service (DDoS) attack in the cloud. Th

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Bhavani, Y., V. Janaki, and R. Sridevi. "Survey on Packet Marking Algorithms for IP Traceback." Oriental journal of computer science and technology 10, no. 2 (2017): 507–12. http://dx.doi.org/10.13005/ojcst/10.02.36.

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Distributed Denial of Service (DDoS) attack is an unavoidable attack. Among various attacks on the network, DDoS attacks are difficult to detect because of IP spoofing. The IP traceback is the only technique to identify DDoS attacks. The path affected by DDoS attack is identified by IP traceback approaches like Probabilistic Packet marking algorithm (PPM) and Deterministic Packet Marking algorithm (DPM). The PPM approach finds the complete attack path from victim to the source where as DPM finds only the source of the attacker. Using DPM algorithm finding the source of the attacker is difficul

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Shurman, Mohammad, Rami Khrais, and Abdulrahman Yateem. "DoS and DDoS Attack Detection Using Deep Learning and IDS." International Arab Journal of Information Technology 17, no. 4A (2020): 655–61. http://dx.doi.org/10.34028/iajit/17/4a/10.

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In the recent years, Denial-of-Service (DoS) or Distributed Denial-of-Service (DDoS) attack has spread greatly and attackers make online systems unavailable to legitimate users by sending huge number of packets to the target system. In this paper, we proposed two methodologies to detect Distributed Reflection Denial of Service (DrDoS) attacks in IoT. The first methodology uses hybrid Intrusion Detection System (IDS) to detect IoT-DoS attack. The second methodology uses deep learning models, based on Long Short-Term Memory (LSTM) trained with latest dataset for such kinds of DrDoS. Our experime

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Sharma, Kavita, and B. B. Gupta. "Taxonomy of Distributed Denial of Service (DDoS) Attacks and Defense Mechanisms in Present Era of Smartphone Devices." International Journal of E-Services and Mobile Applications 10, no. 2 (2018): 58–74. http://dx.doi.org/10.4018/ijesma.2018040104.

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This article describes how in the summer of 1999, the Computer Incident Advisory Capability first reported about Distributed Denial of Service (DDoS) attack incidents and the nature of Denial of Service (DoS) attacks in a distributed environment that eliminates the availability of resources or data on a computer network. DDoS attack exhausts the network resources and disturbs the legitimate user. This article provides an explanation on DDoS attacks and nature of these attacks against Smartphones and Wi-Fi Technology and presents a taxonomy of various defense mechanisms. The smartphone is chose

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Dissertations / Theses on the topic "Distributed denial-of-service attack (DDoS 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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Saied, Alan. "Distributed Denial of Service (DDoS) attack detection and mitigation." Thesis, King's College London (University of London), 2015. http://kclpure.kcl.ac.uk/portal/en/theses/distributed-denial-of-service-ddos-attack-detection-and-mitigation(eaa45e51-f602-46da-a37a-75c3ae71d2db).html.

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A Distributed Denial of Service (DDoS) attack is an organised distributed packet-storming technique that aims to overload network devices and the communication channels between them. Its major objective is to prevent legitimate users from accessing networks, servers, services, or other computer resources. In this thesis, we propose, implement and evaluate a DDoS Detector approach consisting of detection, defence and knowledge sharing components. The detection component is designed to detect known and unknown DDoS attacks using an Artificial Neural Network (ANN) while the defence component prev

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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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Khanal, Sandarva, and Ciara Lynton. "Packet Simulation of Distributed Denial of Service (DDoS) Attack and Recovery." International Foundation for Telemetering, 2013. http://hdl.handle.net/10150/579511.

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ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV<br>Distributed Denial of Service (DDoS) attacks have been gaining popularity in recent years. Most research developed to defend against DDoS attacks have focused on analytical studies. However, because of the inherent nature of a DDoS attack and the scale of a network involved in the attack, analytical simulations are not always the best way to study DDoS attacks. Moreover, because DDoS attacks are c

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Skog, Andersen Jonas, and Ammar Alderhally. "Denial-of-service attack : A realistic implementation of a DoS attack." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-120690.

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This report describes some of the most well known denial of service attacks (DoS-attacks). This will be done in the first part of the report, the second part describes an implementation of a DoS-attack. The main purpose of its first part is to closer examine common DoS-attacks, the purpose of such attacks, the protection methods that can be deployed to mitigate these attacks and the ways that are used to measure these attacks. The second part describes a implementation of a practical attack implemented using HTTP POST requests to overwhelm a web server, so called HTTP POST attack. The attack w

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Jawad, Dina, and Felicia Rosell. "Speak-up as a Resource Based Defence against Application Layer Distributed Denial-of-Service Attacks." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166597.

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Under de senaste åren har antalet DDoS-attacker i Internets applikationsskikt ökat. Detta problem behöver adresseras. Den här rapporten presenterar ett antal existerande metoder för att upptäcka och skydda mot DDoS-attacker i applikationsskiktet. En metod för detta ändamål är att hitta avvikelser av olika typer hos de attackerande klienterna, för att urskilja mellan attackerande och vanliga klienter. Detta är ett brett utforskatförsvarsområde med många positiva resultat, men dessa metoder har ett antal brister, som att de kan resultera i både falska positiva och negativa resultat. En metod som

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Mekhitarian, Araxi, and Amir Rabiee. "A simulation study of an application layer DDoS detection mechanism." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191145.

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Over the last couple of years the rise of application layer Distributed Denial of Service (DDoS) attacks has significantly increased. Because of this, many issues have been raised on how organizations and companies can protect themselves from intrusions and damages against their systems and services. The consequences from these attacks are many, ranging from revenue losses for companies to stolen personal data. As the technologies are evolving, application layer DDoS attacks are becoming more effective and there is not a concrete solution that entirely protects against them. This thesis focuse

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Chan, Yik-Kwan Eric, and 陳奕鈞. "Investigation of a router-based approach to defense against Distributed Denial-of-Service (DDoS) attack." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30173309.

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Andersson, Karl, and Marcus Odlander. "Detecting a Distributed Denial-of-Service Attack Using Speed Test Data: A Case Study on an Attack with Nationwide Impact." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-120611.

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This thesis presents a case study that investigates a large Distributed Denial of Service (DDoS) attack and how it affected speed tests observed by the crowd-based speed test application Bredbandskollen. Furthermore, the thesis also investigates the possibility of using crowd-based speed tests as a method to detect a DDoS attack. This method has very low overhead which makes it an interesting complement to other methods. This thesis also shows that there was a significant deviation in the number of measurements during the DDoS attack considered in the case study compared to the year average.

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Books on the topic "Distributed denial-of-service attack (DDoS attacks)"

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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 Attack and Defense. Springer, 2013.

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Book chapters on the topic "Distributed denial-of-service attack (DDoS attacks)"

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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. "What is DDoS?" In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-2.

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Brooks, Richard R., and İlker Özçelik. "DDoS Research: Testing." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-6.

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Brooks, Richard R., and İlker Özçelik. "Deceiving DDoS Detection." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-9.

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Brooks, Richard R., and İlker Özçelik. "DDoS Research: Traffic." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-5.

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Brooks, Richard R., and İlker Özçelik. "DDoS Research: Evaluation." In Distributed Denial of Service Attacks. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315213125-7.

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Yu, Shui. "An Overview of DDoS Attacks." In Distributed Denial of Service Attack and Defense. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9491-1_1.

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Yu, Shui. "Malicious Networks for DDoS Attacks." In Distributed Denial of Service Attack and Defense. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9491-1_2.

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Yu, Shui. "DDoS Attack Detection." In Distributed Denial of Service Attack and Defense. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9491-1_3.

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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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Conference papers on the topic "Distributed denial-of-service attack (DDoS attacks)"

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Adeshina, Qozeem Adeniyi, and Baidya Nath Saha. "Using Machine Learning to Predict Distributed Denial-of-Service (DDoS) Attack." In Intelligent Computing and Technologies Conference. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.115.21.

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The IT space is growing in all aspects ranging from bandwidth, storage, processing speed, machine learning and data analysis. This growth has consequently led to more cyber threat and attacks which now requires innovative and predictive security approach that uses cutting-edge technologies in order to fight the menace. The patterns of the cyber threats will be observed so that proper analysis from different sets of data will be used to develop a model that will depend on the available data. Distributed Denial of Service is one of the most common threats and attacks that is ravaging computing d

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Wang, Zhongqing, and Yue Zhang. "DDoS Event Forecasting using Twitter Data." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/580.

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Distributed Denial of Service (DDoS) attacks have been significant threats to the Internet. Traditional research in cyber security focuses on detecting emerging DDoS attacks by tracing network package flow. A characteristic of DDoS defense is that rescue time is limited since the launch of attack. More resilient detection and defence models are typically more costly. We aim at predicting the likelihood of DDoS attacks by monitoring relevant text streams in social media, so that the level of defense can be adjusted dynamically for maximizing cost-effect. To our knowledge, this is a novel and ch

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Trostle, Jonathan. "Protecting Against Distributed Denial of Service (DDoS) Attacks Using Distributed Filtering." In 2006 Securecomm and Workshops. IEEE, 2006. http://dx.doi.org/10.1109/seccomw.2006.359548.

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Tavares, Kairo, and Tiago Coelho Ferreto. "DDoS on Sketch: Spoofed DDoS attack defense with programmable data plans using sketches in SDN." In XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbrc.2019.7404.

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Distributed Denial of Service (DDoS) attacks continues to be a major issue in todays Internet. Over the last few years, we have observed a dramatic escalation in the number, scale, and diversity of these attacks. Among the various types, spoofed TCP SYN Flood is one of the most common forms of volumetric DDoS attacks. Several works explored the flexible management control provided by the new network paradigm called Defined Networking Software (SDN) to produce a flexible and powerful defense system. Among them, data plane based solutions combined with recent flexibility of programmable switches

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Sharafaldin, Iman, Arash Habibi Lashkari, Saqib Hakak, and Ali A. Ghorbani. "Developing Realistic Distributed Denial of Service (DDoS) Attack Dataset and Taxonomy." In 2019 International Carnahan Conference on Security Technology (ICCST). IEEE, 2019. http://dx.doi.org/10.1109/ccst.2019.8888419.

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Kumar, Sanjeev. "Smurf-based Distributed Denial of Service (DDoS) Attack Amplification in Internet." In Second International Conference on Internet Monitoring and Protection (ICIMP 2007). IEEE, 2007. http://dx.doi.org/10.1109/icimp.2007.42.

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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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"Keynote: Detection of and Defense Against Distributed Denial-of-Service (DDoS) Attacks." In 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2012. http://dx.doi.org/10.1109/trustcom.2012.341.

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Bhosale, Karuna S., Maria Nenova, and Georgi Iliev. "The distributed denial of service attacks (DDoS) prevention mechanisms on application layer." In 2017 13th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS). IEEE, 2017. http://dx.doi.org/10.1109/telsks.2017.8246247.

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Leonardo Costa, Wanderson, Ariel Lima de Carvalho Portela, and Rafael Lopes Gomes. "Análise de Características do Tráfego de Rede para Detecção de Ataques DDoS em Ambientes IoT." In Computer on the Beach. Universidade do Vale do Itajaí, 2021. http://dx.doi.org/10.14210/cotb.v12.p217-224.

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The evolution of computing devices has allowed the evolution ofservice provision in society, applying new technologies based onthe Internet of Things (IoT). Most IoT devices have security vulnerabilities,making them susceptible to Distributed Denial of Service(DDoS) Attacks. Thus, it is necessary to apply solutions that candetect this type of attack in IoT networks from the information ofthe network traffic. However, there is still no definition of whichtraffic characteristics should be used for detection, since the useof inappropriate characteristics tend to make detection difficult.Within th

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Reports on the topic "Distributed denial-of-service attack (DDoS attacks)"

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Blackert, W. J., R. L. Hom, A. K. Castner, R. M. Jokerst, and D. M. Gregg. Distributed Denial of Service-Defense Attack Tradeoff Analysis (DDOS-DATA). Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada429339.

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