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Articles de revues sur le sujet « Distributed attacks »

Auteur : Grafiati

Publié le 10 mars 2023

Mis à jour le 31 juillet 2025

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1

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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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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Kadirov, M. M. "АНАЛИЗ И КЛАССИФИКАЦИЯ КИБЕРАТАК НА ИНФОРМАЦИОННО-КОММУНИКАЦИОННЫЕ СИСТЕМЫ". Journal of Science and Innovative Development 6, № 4 (2023): 27–36. http://dx.doi.org/10.36522/2181-9637-2023-4-3.

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This article analyzes distributed cyberattacks of the “Denial of Service” type and develops their classification. A description of the shortcomings and vulnerabilities of distributed denial-of-service attacks by category is given. An implementation diagram with examples for each category of distributed denial of service attacks is presented. Analyzed the number of attacks carried out by attackers, as well as the purpose and type of attack used. According to the results of the study, the UDP-flood 53.64% attack type is the most commonly used type by attackers in implementing distributed attacks

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Saba Abdulbaqi Salman, Sufyan Al-Janabi, and Ali Makki Sagheer. "Security Attacks on E-Voting System Using Blockchain." Iraqi Journal For Computer Science and Mathematics 4, no. 2 (2023): 179–88. http://dx.doi.org/10.52866/ijcsm.2023.02.02.016.

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Electronic voting has become popular in democratic countries, and thus the cyber security of this system is demanded. In this paper, some attacks were made on a proposed electronic election model based on blockchain technology, where the impact of each attack (Sybil, DDoS, Eclipse, Selfish mining, 51% attack) was calculated, and the time in which it achieved 51% of the attack was calculated. In this study, we investigate of Blockchain technology’s attack surface, focusing on general blockchains. The following factors show how these attacks have an impact on the proposed model: 1) The cryptogra

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Chaudhary, Sachin, and Kanchan Chaudhary. "Distributed Honeypots System." International Journal of Advance Research and Innovation 1, no. 2 (2013): 5–11. http://dx.doi.org/10.51976/ijari.121302.

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Honeypot is a supplemented active defence system for network security. It traps attacks, records intrusion information about tools and activities of the hacking process, and prevents attacks outbound the compromised system. Integrated with other security solutions, Honeypot can solve many traditional dilemmas. It has emerged as a prominent technology that helps learn new hacking techniques from attackers and intruders. Honeypots can initiatively lure hackers to attack the internet, take the record of the ways and means of their invasion, and then analyze and study them.

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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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Karthikeyani, R., and E. Karthikeyan. "A Review on Distributed Denial of Service Attack." Asian Journal of Research in Computer Science 16, no. 4 (2023): 133–44. http://dx.doi.org/10.9734/ajrcos/2023/v16i4378.

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Today’s world, technology has become an inevitable part of human life. In fact, during the Covid-19 pandemic, everything from the corporate world to educational institutions has shifted from offline to online. It leads to exponential increase in intrusions and attacks over the internet-based technologies. Distributed denial of service (DDOS) attack is one of the most dangerous attack that could cause devastating effects on the internet. These attacks are becoming more complex and expected to expand in number day after day, rendering detecting and combating these threats challenging. In network

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Kasture, Pradnya. "DDoS Attack Detection using ML." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 6421–24. http://dx.doi.org/10.22214/ijraset.2023.53133.

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Abstract: DDoS attacks are an attempt to prevent the service from being unavailable by overloading the server with malicious traffic. In the past few years, distributed denial of service attacks is becoming the most difficult and burdensome problem. The number and magnitude of attacks have increased from few megabytes of data to 100s of terabytes of data these days. As there are different attack patterns or new types of attacks, it is difficult to detect such attacks effectively. New techniques for generating and mitigating distributed denial of service attacks have been developed in the prese

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Riyadh, Rahef Nuiaa, Manickam Selvakumar, and Hakem Alsaeedi Ali. "Distributed reflection denial of service attack: A critical review." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (2021): 5327–41. https://doi.org/10.11591/ijece.v11i6.pp5327-5341.

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As the world becomes increasingly connected and the number of users grows exponentially and “things” go online, the prospect of cyberspace becoming a significant target for cybercriminals is a reality. Any host or device that is exposed on the internet is a prime target for cyberattacks. A denial-of-service (DoS) attack is accountable for the majority of these cyberattacks. Although various solutions have been proposed by researchers to mitigate this issue, cybercriminals always adapt their attack approach to circumvent countermeasures. One of the modified DoS attacks is known as d

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Riskhan, Basheer, Halawati Abd Jalil Safuan, Khalid Hussain, et al. "An Adaptive Distributed Denial of Service Attack Prevention Technique in a Distributed Environment." Sensors 23, no. 14 (2023): 6574. http://dx.doi.org/10.3390/s23146574.

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Cyberattacks in the modern world are sophisticated and can be undetected in a dispersed setting. In a distributed setting, DoS and DDoS attacks cause resource unavailability. This has motivated the scientific community to suggest effective approaches in distributed contexts as a means of mitigating such attacks. Syn Flood is the most common sort of DDoS assault, up from 76% to 81% in Q2, according to Kaspersky’s Q3 report. Direct and indirect approaches are also available for launching DDoS attacks. While in a DDoS attack, controlled traffic is transmitted indirectly through zombies to reflect

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Li, Muhai, and Ming Li. "An Adaptive Approach for Defending against DDoS Attacks." Mathematical Problems in Engineering 2010 (2010): 1–15. http://dx.doi.org/10.1155/2010/570940.

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In various network attacks, the Distributed Denial-of-Service (DDoS) attack is a severe threat. In order to deal with this kind of attack in time, it is necessary to establish a special type of defense system to change strategy dynamically against attacks. In this paper, we introduce an adaptive approach, which is used for defending against DDoS attacks, based on normal traffic analysis. The approach can check DDoS attacks and adaptively adjust its configurations according to the network condition and attack severity. In order to insure the common users to visit the victim server that is being

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Kumar, Aman. "Distributed Denial of Service (DDoS) Attack Mitigation using AI." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 5706–14. https://doi.org/10.22214/ijraset.2025.69632.

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Abstract: Distributed Denial of Service(DDoS) attacks have been the major threats for the Internet and can bring great loss to companies and governments. With the development of emergingtechnologies, suchascloudcomputing, InternetofThings(IoT), artificialintelligence techniques, attackers can launch a huge volume of DDoS attacks with a lower cost, and it is much harder to detect and prevent DDoS attacks, because DDoS traffic is similar to normal traffic. Naive Bayes and Random Forest trees are two examples of artificial intelligence techniques that have been used to detect and categorize DDoS

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Mou, Jinping. "Adaptive Consensus of Distributed Varying Scale Wireless Sensor Networks under Tolerable Jamming Attacks." Mathematical Problems in Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/931934.

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Consensus problem is investigated for a varying scale wireless sensor network (VSWSN) under tolerable jamming attacks, where the scale of the network is increasing or decreasing due to the newly joined nodes or the removed nodes, respectively; the tolerable jamming attack means that the attack strength is limited. It supposes that during the communications, all nodes may encounter with the tolerable jamming attacks; when the attack power is larger than the given value, the attacked nodes fall asleep, or otherwise the nodes are awakened. Under the sleep method, based on the Lyapunov method, it

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Gavrić, Nikola, and Živko Bojović. "Security Concerns in MMO Games—Analysis of a Potent Application Layer DDoS Threat." Sensors 22, no. 20 (2022): 7791. http://dx.doi.org/10.3390/s22207791.

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The application layer in the Internet protocol suite offers a significant degree of freedom regarding the orchestration of distributed denial-of-service attacks due to many different and unstandardized protocols. The primary focus of defending against application-layer distributed denial-of-service attacks has traditionally been Hypertext Transfer Protocols oriented while observing individual users’ actions independently from one another. In this paper, we present and analyze a novel application-layer DDoS attack in massively multiplayer online games that utilize the cooperative efforts of the

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Prenzel, Björn G., William G. Laidlaw, and Hal Wieser. "WITHIN-TREE DYNAMICS OF MASS ATTACK BY DENDROCTONUS PSEUDOTSUGAE (COLEOPTERA: SCOLYTIDAE) ON ITS HOST." Canadian Entomologist 131, no. 5 (1999): 635–43. http://dx.doi.org/10.4039/ent131635-5.

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AbstractThe within-tree scale dynamics of mass attack by the Douglas-fir beetle, Dendroctonus pseudotsugae Hopkins, on its host were investigated and quantified. Seven similarly sized Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco (Pinaceae), infested as part of several pheromone-induced infestations, were monitored over an entire attack season. Ninety percent of the attacks on mass-attacked trees occurred within 3 weeks of colonization; the remaining 10% occurred gradually over the remaining 7 weeks of the attack season. Vertical attack distribution followed a Gaussian form that shifted up

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Manaseer, Saher, and Ahmad K. Al Hwaitat. "Centralized Web Application Firewall Security System." Modern Applied Science 12, no. 10 (2018): 164. http://dx.doi.org/10.5539/mas.v12n10p164.

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In this paper we propose a centralized web firewall system for web application security which will provide a new type of synchronized system, which has the ability to&nbsp; detect&nbsp; and prevent a variety of web application attacks for a wide range of hosts at the same time , using an centralized command and control system, the attacked client then sends the information to a centralized command and control server which will distribute the attack information to all of the integrated clients connected to it. The distributed information contains all of the attack information including

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Li, Wenpei, Han Fu, Shun Wu, Bin Yang, and Zhixiong Liu. "A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids." Energies 16, no. 24 (2023): 7959. http://dx.doi.org/10.3390/en16247959.

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To ensure fast dynamics and the stability of multiple distributed generator units (DGUs) in DC microgrids, communication links among the controllers of DGUs are generally adopted. However, those communication channels are vulnerable to cyber-attacks. To alleviate this hassle, a Kalman Filter (KF)-based distributed cyber-attack mitigation strategy, which is highly involved in both primary and secondary control, is proposed in this paper. The KF, as a robust state estimator, is utilized to accurately estimate the authentic terminal voltages and currents of the DGUs. Based on the discrepancies be

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K., Thamizhmaran. "Enhanced Secure Technique for Detecting Attacks in Network." Journal of Advancement in Electronics Design 3, no. 3 (2020): 1–6. https://doi.org/10.5281/zenodo.4223718.

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<em>Recent research years of development of network mainly affected denial of service attacks are a virulent. Distributed rejection of service attackers infiltrate enormous quantities of computers by misusing software vulnerabilities, to set up distributed attack networks.These accidental computers are then summoned to wage a coordinated, large-scale enormous attack against at least one more victim systems. As specific counter measures are developed, attackers enhance existing denial attack tools, developing new and derivative developed techniques and attack tools. As opposed to respond to new

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Li, Yufeng, Le Tian, Han Qiu, and Chuanhao Zhang. "Research Notes: Distributed Shadow for Router Security Defense." International Journal of Software Engineering and Knowledge Engineering 28, no. 02 (2018): 193–206. http://dx.doi.org/10.1142/s021819401840003x.

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Router security defense technologies emerging in recent years could hardly detect and block the new booming threats with unknown signatures such as hardware Trojan, zero-day attacks, etc. We present a novel router defense technology, distributed router shadow, which builds a closed execution environment to deceive attacks entering into the router, thereby misleading the attackers into regarding it as the real attack target and executing the suspicious code to maximize the chances of detonating the system exploit; thus the original router is prevented from attacking and the suspicious code can

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Shui, Yongtao, Yu Wang, Yu Li, Yongzhi Shan, Naigang Cui, and Baojun Pang. "Consensus-Based Distributed Target Tracking with False Data Injection Attacks over Radar Network." Applied Sciences 11, no. 10 (2021): 4564. http://dx.doi.org/10.3390/app11104564.

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For target tracking in radar network, any anomaly in a part of the system can quickly spread over the network and lead to tracking failures. False data injection (FDI) attacks can damage the state estimation mechanism by modifying the radar measurements with unknown and time-varying attack variables, therefore making traditional filters inapplicable. To tackle this problem, we propose a novel consensus-based distributed state estimation (DSE) method for target tracking with FDI attacks, which is effective even when all radars are under FDI attacks. First, a real-time residual-based detector is

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Fatkieva, R. R., A. S. Sudakov, and A. S. Nersisyan. "Key Characteristics of Network Traffic to Identify DDoS Attacks." LETI Transactions on Electrical Engineering & Computer Science 17, no. 8 (2024): 65–80. http://dx.doi.org/10.32603/2071-8985-2024-17-8-65-80.

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Modern methods of analyzing and protecting network infrastructure against DDoS (Distributed Denial of Service) attacks are discussed. A DDoS detection model has been developed using statistical techniques, which highlights the main stages of the attacks and key characteristics of network traffic that are crucial for detecting an attack. Potential and attack power are introduced as main concepts in assessing DDoS activity. To identify the type of attack, it is suggested to increase the sensitivity of the model by identifying key characteristics that distinguish between different attack stages.

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Nuiaa, Riyadh Rahef, Selvakumar Manickam, and Ali Hakem Alsaeedi. "Distributed reflection denial of service attack: A critical review." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (2021): 5327. http://dx.doi.org/10.11591/ijece.v11i6.pp5327-5341.

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As the world becomes increasingly connected and the number of users grows exponentially and “things” go online, the prospect of cyberspace becoming a significant target for cybercriminals is a reality. Any host or device that is exposed on the internet is a prime target for cyberattacks. A denial-of-service (DoS) attack is accountable for the majority of these cyberattacks. Although various solutions have been proposed by researchers to mitigate this issue, cybercriminals always adapt their attack approach to circumvent countermeasures. One of the modified DoS attacks is known as distributed r

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Kareem, Morenikeji Kabirat, Olaniyi Dada Aborisade, Saidat Adebukola Onashoga, Tole Sutikno, and Olaniyi Mathew Olayiwola. "Efficient model for detecting application layer distributed denial of service attacks." Bulletin of Electrical Engineering and Informatics 12, no. 1 (2023): 441–50. http://dx.doi.org/10.11591/eei.v12i1.3871.

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The increasing advancement of technologies and communication infrastructures has been posing threats to the internet services. One of the most powerful attack weapons for disrupting web-based services is the distributed denial of service (DDoS) attack. The sophisticated nature of attack tools being created and used for launching attacks on target systems makes it difficult to distinguish between normal and attack traffic. Consequently, there is a need to detect application layer DDoS attacks from network traffic efficiently. This paper proposes a detection system coined eXtreme gradient boosti

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Kumavat, Kavita S., and Joanne Gomes. "Common Mechanism for Detecting Multiple DDoS Attacks." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 4 (2023): 81–90. http://dx.doi.org/10.17762/ijritcc.v11i4.6390.

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An important principle of an internet-based system is information security. Information security is a very important aspect of distributed systems and IoT (Internet of Things) based wireless systems. The attack which is more harmful to the distributed system and IoT-based wireless system is a DDoS (Distributed Denial of Service) attack since in this attack, an attacker can stop the work of all other connected devices or users to the network. For securing distributed applications, various intrusion detection mechanisms are used. But most existing mechanisms are only concentrated on one kind of

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Adam Zukhruf, Bagus Fatkhurrozi, and Andriyatna Agung Kurniawan. "COMPARATIVE STUDY OF DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACK DETECTION IN COMPUTER NETWORKS." Jurnal Teknik Informatika (Jutif) 4, no. 5 (2023): 1033–39. http://dx.doi.org/10.52436/1.jutif.2023.4.5.756.

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Distributed Denial of Service (DDoS) attack is an internet crime that aims to consume server resources so that the server becomes unusable. Suricata, Snort and Wireshark are useful software applications for detecting DDoS attacks. This study aims to compare the performance of the snort, suricata and wireshark applications in detecting Distributed Denial of Service attacks. The comparison parameters used are the total attacks that can be detected and memory usage. The type of attack used in testing is syn flood and ping of death. The research results obtained by Suricata became the most effecti

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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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Adhikary, Kaushik, Shashi Bhushan, Sunil Kumar, and Kamlesh Dutta. "Evaluating the Impact of DDoS Attacks in Vehicular Ad-Hoc Networks." International Journal of Security and Privacy in Pervasive Computing 12, no. 4 (2020): 1–18. http://dx.doi.org/10.4018/ijsppc.2020100101.

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The presence of either malicious vehicles or inaccessibility of network services makes vehicular ad-hoc networks (VANETs) easy targets for denial of service (DoS) attacks. The sole purpose of DoS attacks is to prevent the intended users from accessing the available resources and services. When the DoS attack is carried out by multiple vehicles distributed throughout the network, it is referred as distributed DoS (DDoS) attack. A lot of works have been done by researchers in securing the vehicular communication against the DDoS attacks. In this paper, efforts have been made to simulate the DDoS

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Baird, Iain, Isam Wadhaj, Baraq Ghaleb, and Craig Thomson. "Impact Analysis of Security Attacks on Mobile Ad Hoc Networks (MANETs)." Electronics 13, no. 16 (2024): 3314. http://dx.doi.org/10.3390/electronics13163314.

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Mobile ad hoc networks (MANETs) offer a decentralized communication solution ideal for infrastructure-less environments like disaster relief zones. However, their inherent lack of central control and dynamic topology make them vulnerable to attacks. This paper examines the impact of various attacks on mobile nodes within two network types: randomly and uniformly distributed stationary networks. Four types of attacks are investigated: delay, dropping, sinkhole (alone), and a combined black hole attack (dropping + sinkhole). The effects of these attacks are compared using the packet delivery rat

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Al-Mashadani, Abdulrahman Khalid Abdullah, and Muhammad Ilyas. "Distributed Denial of Service Attack Alleviated and Detected by Using Mininet and Software Defined Network." Webology 19, no. 1 (2022): 4129–44. http://dx.doi.org/10.14704/web/v19i1/web19272.

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The network security and how to keep it safe from malicious attacks now days is attract huge interest of the developers and cyber security experts (SDN) Software- Defined Network is simple framework for network that allow programmability and monitoring that enable the operators to manage the entire network in a consistent and comprehensive manner also used to detect and alleviate the DDoS attacks the SDN now is the trending of network security evolution there many threats that faces the networks one of them is the distributed Denial of Service (DDoS) because of the architecture weakness in tra

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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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Volokyta, Artem, and Mykyta Melenchukov. "NEURAL NETWORKS IN DETECTING ATTACKS ON DISTRIBUTED SYSTEMS." TECHNICAL SCIENCES AND TECHNOLOGIES, no. 1(35) (2024): 135–45. http://dx.doi.org/10.25140/2411-5363-2024-1(35)-135-145.

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Modern challenges in processing vast amounts of data are solved with the help of complex distributed systems, which in turn require cyber protection, that has the instruments for managing security riskssuch as information acquisition, espionage, reduction of system productivity, etc. This article provides an overview of some approaches to detecting cyberattacks, which in particular use machine learning. Their advantages, disadvantages, work methods, vulnerabilities, and approaches to their protection are given. Approaches to using various machine learning modelsfor pre-processing input data, w

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Li, Ming, and Wei Zhao. "Detection of Variations of Local Irregularity of Traffic under DDOS Flood Attack." Mathematical Problems in Engineering 2008 (2008): 1–11. http://dx.doi.org/10.1155/2008/475878.

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The aim of distributed denial-of-service (DDOS) flood attacks is to overwhelm the attacked site or to make its service performance deterioration considerably by sending flood packets to the target from the machines distributed all over the world. This is a kind of local behavior of traffic at the protected site because the attacked site can be recovered to its normal service state sooner or later even though it is in reality overwhelmed during attack. From a view of mathematics, it can be taken as a kind of short-range phenomenon in computer networks. In this paper, we use the Hurst parameter

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Yaseen, Hiba Salah, and Ahmed Al-Saadi. "Q-learning based distributed denial of service detection." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (2023): 972. http://dx.doi.org/10.11591/ijece.v13i1.pp972-986.

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<span lang="EN-US">Distributed denial of service (DDoS) attacks the target service providers by sending a huge amount of traffic to prevent legitimate users from getting the service. These attacks become more challenging in the software-defined network paradigm, due to the separation of the control plane from the data plane. Centralized software defined networks are more vulnerable to DDoS attacks that may cause the failure of all networks. In this work, a new approach is proposed based on q-learning to enhance the detection of DDoS attacks and reduce false positives and false negatives.

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Hiba, Salah Yaseen, and Al-Saadi Ahmed. "Q-learning based distributed denial of service detection." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (2023): 972–86. https://doi.org/10.11591/ijece.v13i1.pp972-986.

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Distributed denial of service (DDoS) attacks the target service providers by sending a huge amount of traffic to prevent legitimate users from getting the service. These attacks become more challenging in the software-defined network paradigm, due to the separation of the control plane from the data plane. Centralized software defined networks are more vulnerable to DDoS attacks that may cause the failure of all networks. In this work, a new approach is proposed based on q-learning to enhance the detection of DDoS attacks and reduce false positives and false negatives. The results of this work

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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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Shazly, Khadija, Dina A. Salem, Nacereddine Hammami, and Ahmed I. B. ElSeddawy. "A Review on Distributed Denial of Service Detection in Software Defined Network." International Journal of Wireless and Ad Hoc Communication 5, no. 2 (2022): 08–18. http://dx.doi.org/10.54216/ijwac.050201.

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Network security has become considerably essential because of the expansion of the internet of things (IoT) devices. One of the greatest hazards of today's networks is distributed denial of service (DDoS) attacks, which could destroy critical network services. Recently numerous IoT devices are unsuspectingly attacked by DDoS. To securely manage IoT equipment, researchers have introduced software-defined networks (SDN). This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attacks. The results have indicated that the algorithms for machine lea

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R K, Monika, and Ravikumar K. "PROTECTING VIRTUALIZED INFRASTRUCTURES IN CLOUD COMPUTING BASED ON BIG DATA SECURITY ANALYTICS." ICTACT Journal on Soft Computing 11, no. 2 (2021): 2306–15. https://doi.org/10.21917/ijsc.2021.0330.

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Virtualized infrastructure in cloud computing has become an attractive target for cyber attackers to launch advanced attacks. This paper proposes a novel big data based security analytics approach to detecting advanced attacks in virtualized infrastructures. Network logs as well as user application logs collected periodically from the guest virtual machines (VMs) are stored in the Hadoop Distributed File System (HDFS). Then, extraction of attack features is performed through graph-based event correlation and Map Reduce parser based identification of potential attack paths. Next, determination

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Li, Xi, Songhe Wang, Ruiquan Huang, Mahanth Gowda, and George Kesidis. "Temporal-Distributed Backdoor Attack against Video Based Action Recognition." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 4 (2024): 3199–207. http://dx.doi.org/10.1609/aaai.v38i4.28104.

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Deep neural networks (DNNs) have achieved tremendous success in various applications including video action recognition, yet remain vulnerable to backdoor attacks (Trojans). The backdoor-compromised model will mis-classify to the target class chosen by the attacker when a test instance (from a non-target class) is embedded with a specific trigger, while maintaining high accuracy on attack-free instances. Although there are extensive studies on backdoor attacks against image data, the susceptibility of video-based systems under backdoor attacks remains largely unexplored. Current studies are di

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Zhang, Yan, Yong Wang, Yihua Hu, et al. "Security Performance Analysis of LEO Satellite Constellation Networks under DDoS Attack." Sensors 22, no. 19 (2022): 7286. http://dx.doi.org/10.3390/s22197286.

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Low Earth orbit satellite constellation networks (LSCNs) have attracted significant attention around the world due to their great advantages of low latency and wide coverage, but they also bring new challenges to network security. Distributed denial of service (DDoS) attacks are considered one of the most threatening attack methods in the field of Internet security. In this paper, a space-time graph model is built to identify the key nodes in LSCNs, and a DDoS attack is adopted as the main means to attack the key nodes. The scenarios of two-satellite-key-node and multi-satellite-key-node attac

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Singh, Karanbir, Kanwalvir Singh Dhindsa, and Bharat Bhushan. "Distributed Defense: An Edge over Centralized Defense against DDos Attacks." International Journal of Computer Network and Information Security 9, no. 3 (2017): 36–44. http://dx.doi.org/10.5815/ijcnis.2017.03.05.

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Distributed Denial of Service (DDoS) attack is a large-scale, coordinated attack on the availability of services of a target/victim system or network resource/service. It can be launched indirectly through many compromised machines on the Internet. The Purpose behind these attacks is exhausting the existing bandwidth and makes servers deny from providing services to legitimate users. Most detection systems depend on some type of centralized processing to analyze the data necessary to detect an attack. In centralized defense, all modules are placed on single point. A centralized approach can be

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Zhang, Jian, Qidi Liang, Rui Jiang, and Xi Li. "A Feature Analysis Based Identifying Scheme Using GBDT for DDoS with Multiple Attack Vectors." Applied Sciences 9, no. 21 (2019): 4633. http://dx.doi.org/10.3390/app9214633.

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In recent years, distributed denial of service (DDoS) attacks have increasingly shown the trend of multiattack vector composites, which has significantly improved the concealment and success rate of DDoS attacks. Therefore, improving the ubiquitous detection capability of DDoS attacks and accurately and quickly identifying DDoS attack traffic play an important role in later attack mitigation. This paper proposes a method to efficiently detect and identify multivector DDoS attacks. The detection algorithm is applicable to known and unknown DDoS attacks.

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Zeebaree, Subhi R. M., Karzan H. Sharif, and Roshna M. Mohammed Amin. "Application Layer Distributed Denial of Service Attacks Defense Techniques : A review." Academic Journal of Nawroz University 7, no. 4 (2018): 113. http://dx.doi.org/10.25007/ajnu.v7n4a279.

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Currently distributed denial of service (DDoS) is the most sever attack that effect on the internet convenience. The main goal of these attacks is to prevent normal users from accessing the internet services such as web servers. However the more challenge and difficult types to detect is application layer DDoS attacks because of using legitimate client to create connection with victims. In this paper we give a review on application layer DDoS attacks defense or detection mechanisms. Furthermore, we summarize several experimental approaches on detection techniques of application layer DDoS atta

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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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Song, Zhenghang, Xiang Wang, Baoze Wei, Zhengyu Shan, and Peiyuan Guan. "Distributed Finite-Time Cooperative Economic Dispatch Strategy for Smart Grid under DOS Attack." Mathematics 11, no. 9 (2023): 2103. http://dx.doi.org/10.3390/math11092103.

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This paper proposes an energy management strategy that can resist DOS attacks for solving the Economic Dispatch Problem (EDP) of the smart grid. We use the concept of energy agent, which acts as a hub for the smart grid, and each EA is an integrated energy unit that converts, stores, and utilizes its local energy resources. This approach takes into account the coupling relationship between energy agents (EA) and utilizes the Lyapunov function technique to achieve finite-time solutions for optimization problems. We incorporate strategies to resist DOS attacks when analyzing finite-time converge

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Jaideep, Gera, and Bhanu Prakash Battula. "Detection of DDOS attacks in distributed peer to peer networks." International Journal of Engineering & Technology 7, no. 2.7 (2018): 1051. http://dx.doi.org/10.14419/ijet.v7i2.7.12227.

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Peer to Peer (P2P) network in the real world is a class of systems that are made up of thousands of nodes in distributed environments. The nodes are decentralized in nature. P2P networks are widely used for sharing resources and information with ease. Gnutella is one of the well known examples for such network. Since these networks spread across the globe with large scale deployment of nodes, adversaries use them as a vehicle to launch DDoS attacks. P2P networks are exploited to make attacks over hosts that provide critical services to large number of clients across the globe. As the attacker

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Čerňanský, Michal, Ladislav Huraj, and Marek Šimon. "Controlled DDoS Attack on IPv4/IPv6 Network Using Distributed Computing Infrastructure." Journal of information and organizational sciences 44, no. 2 (2020): 297–316. http://dx.doi.org/10.31341/jios.44.2.6.

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The paper focuses on design, background and experimental results of real environment of DDoS attacks. The experimental testbed is based on employment of a tool for IT automation to perform DDoS attacks under monitoring. DDoS attacks are still serious threat in both IPv4 and IPv6 networks and creation of simple tool to test the network for DDoS attack and to allow evaluation of vulnerabilities and DDoS countermeasures of the networks is necessary. In proposed testbed, Ansible orchestration tool is employed to perform and coordinate DDoS attacks. Ansible is a powerful tool and simplifies the imp

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Cheng, Zhijian, Guanjun Chen, Xiao-Meng Li, and Hongru Ren. "Consensus-Based Power System State Estimation Algorithm Under Collaborative Attack." Sensors 24, no. 21 (2024): 6886. http://dx.doi.org/10.3390/s24216886.

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Due to its vulnerability to a variety of cyber attacks, research on cyber security for power systems has become especially crucial. In order to maintain the safe and stable operation of power systems, it is worthwhile to gain insight into the complex characteristics and behaviors of cyber attacks from the attacker’s perspective. The consensus-based distributed state estimation problem is investigated for power systems subject to collaborative attacks. In order to describe such attack behaviors, the denial of service (DoS) attack model for hybrid remote terminal unit (RTU) and phasor measuremen

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Le, Jian, Jing Wang, Hongke Lang, and Weihao Wang. "Distributed Secure Economic Dispatch Strategy Based on Robust Graph Theory and W-MSR Algorithm." Sensors 25, no. 8 (2025): 2551. https://doi.org/10.3390/s25082551.

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The traditional consensus-based distributed economic dispatch strategy may lose system convergency and cause imbalanced power when facing an information attack on the individual power generation unit; thus, it is unable to achieve the dispatching goal. Taking into consideration several kinds of attack behaviors that may exist in a distributed control system, this paper develops models of node attacks from the two aspects of action mode and deployment scope, and analyzes the influence of attack behaviors on the distributed economic dispatch system. Based on the idea of the W-MSR algorithm that

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Manita, Mohamed Sasi, and Ahmed Ibrahim Suleiman. "Training Machine Learning Algorithms to Detect Distributed Denial of Service Attacks." International Science and Technology Journal 34, no. 2 (2024): 1–23. http://dx.doi.org/10.62341/msai2687.

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Cyber-attacks are becoming more and more sophisticated, posing a serious threat to our technologically dependent society. Such an attack is the Distributed Denial of Service (DDoS) attack, which is becoming a serious threat to businesses that have integrated their technology with public networks since they enable numerous attackers to obtain data or provide services to major corporations or nations. When a company's servers are overloaded with fraudulent requests while legitimate users' requests are denied, Distributed Denial of Service (DDoS) attacks disrupt Web service availability for an ar

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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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