Relevant bibliographies by topics / Amplification attack

Contents

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

Academic literature on the topic 'Amplification attack'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Amplification attack"

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Anagnostopoulos, Marios, Georgios Kambourakis, Panagiotis Kopanos, Georgios Louloudakis, and Stefanos Gritzalis. "DNS amplification attack revisited." Computers & Security 39 (November 2013): 475–85. http://dx.doi.org/10.1016/j.cose.2013.10.001.

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Quadir, Md Abdul, J. Christy Jackson, J. Prassanna, K. Sathyarajasekaran, K. Kumar, H. Sabireen, Shivam Ubarhande, and V. Vijaya Kumar. "An efficient algorithm to detect DDoS amplification attacks." Journal of Intelligent & Fuzzy Systems 39, no. 6 (December 4, 2020): 8565–72. http://dx.doi.org/10.3233/jifs-189173.

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Domain name system (DNS) plays a critical part in the functioning of the Internet. But since DNS queries are sent using UDP, it is vulnerable to Distributed Denial of Service (DDoS) attacks. The attacker can take advantage of this and spoof the source IP address and direct the response towards the victim network. And since the network does not keep track of the number of requests going out and responses coming in, the attacker can flood the network with these unwanted DNS responses. Along with DNS, other protocols are also exploited to perform DDoS. Usage of Network Time Protocol (NTP) is to synchronize clocks on systems. Its monlist command replies with 600 entries of previous traffic records. This response is enormous compared to the request. This functionality is used by the attacker in DDoS. Since these attacks can cause colossal congestion, it is crucial to prevent or mitigate these types of attacks. It is obligatory to discover a way to drop the spoofed packets while entering the network to mitigate this type of attack. Intelligent cybersecurity systems are designed for the detection of these attacks. An Intelligent system has AI and ML algorithms to achieve its function. This paper discusses such intelligent method to detect the attack server from legitimate traffic. This method uses an algorithm that gets activated by excess traffic in the network. The excess traffic is determined by the speed or rate of the requests and responses and their ratio. The algorithm extracts the IP addresses of servers and detects which server is sending more packets than requested or which are not requested. This server can be later blocked using a firewall or Access Control List (ACL).
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Sieklik, Boris, Richard Macfarlane, and William J. Buchanan. "Evaluation of TFTP DDoS amplification attack." Computers & Security 57 (March 2016): 67–92. http://dx.doi.org/10.1016/j.cose.2015.09.006.

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Widagdo, Gede Barkah. "Real-Time Early Detection NTP Amplification Attack." ACMIT Proceedings 3, no. 1 (March 18, 2019): 76–84. http://dx.doi.org/10.33555/acmit.v3i1.29.

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This paper is the initials of DDoS mitigation, the goal of this research is to detect NTP Amplification as early as possible so that the victim have a data to do further eskalation process. We knows that the goal of the attacker using NTP Amplification Attack is to exhaust the bandwidth of the victim, in this research also simulate an NTP amplification scenario and detection method; the scenario is the attacker sends requests with spoofed IP MONLIST victim to the compromised NTP server NTP server then responds the large volumes of traffic (amplified traffic) towards Victim to consume the bandwidth so as the legitimate user could not access the services. We put DDoS detection device side of the victim, we combine several monitoring tools to detect NTP amplification i.e bandwidth gauge and netflow analyzer. Netflow analyzer (flow analysis) conduct analysis IP packet header that is sent by the router as a flow-exporter. In our experiment, we could perform early detection of the NTP amplification less than 2 minute.
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Najafabadi, Maryam M., Taghi M. Khoshgoftaar, and Amri Napolitano. "Detecting Network Attacks Based on Behavioral Commonalities." International Journal of Reliability, Quality and Safety Engineering 23, no. 01 (February 2016): 1650005. http://dx.doi.org/10.1142/s0218539316500054.

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Due to the great increase in the amount of attacks that occur in computer networks, there is an increasing dependence on network intrusion detection systems which monitor and analyze the network data to detect attacks. In recent years, machine learning methods have been used to build predictive models for network intrusion detection. These methods are able to automatically extract patterns from the network data to build detection models. Defining proper features, which help models to better discriminate between normal and attack data, is a critical task. While network attacks vary widely, they share some commonalities. Many attacks, by their nature, are repetitive and exhibit behaviors different from normal traffic. Among these commonalities are self-similarity between attack packets, periodicity and repetition characteristics seen in the attack traffic. In this paper, we study the common behaviors between two different attack types, called RUDY and DNS Amplification attacks, in order to propose new features for building predictive models by using machine learning algorithms. We collected Netflow traffic from an operational ISP network. We introduce a concept called “session” derived from Netflow which incorporates both sides of a network communication to define a network instance. Features are extracted for each session. To demonstrate how the newly defined features work for the task of intrusion detection, we use these features to build intrusion detection models for the detection of RUDY attack, DNS Amplification attack and the combination of these two attacks. To build predictive models we apply four machine learning classification algorithms: two versions of a decision tree algorithm, Naïve Bayes and 5-Nearest Neighbor (5-NN) algorithm. Our results show that the proposed features based on the attack commonalities provide very good prediction results for the detection of two studied attacks on real network traffic.
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Khan, Muhammad Salman, Ken Ferens, and Witold Kinsner. "A Chaotic Complexity Measure for Cognitive Machine Classification of Cyber-Attacks on Computer Networks." International Journal of Cognitive Informatics and Natural Intelligence 8, no. 3 (July 2014): 45–69. http://dx.doi.org/10.4018/ijcini.2014070104.

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Today's evolving cyber security threats demand new, modern, and cognitive computing approaches to network security systems. In the early years of the Internet, a simple packet inspection firewall was adequate to stop the then-contemporary attacks, such as Denial of Service (DoS), ports scans, and phishing. Since then, DoS has evolved to include Distributed Denial of Service (DDoS) attacks, especially against the Domain Name Service (DNS). DNS based DDoS amplification attacks cannot be stopped easily by traditional signature based detection mechanisms because the attack packets contain authentic data, and signature based detection systems look for specific attack-byte patterns. This paper proposes a chaos based complexity measure and a cognitive machine classification algorithm to detect DNS DDoS amplification attacks. In particular, this paper computes the Lyapunov exponent to measure the complexity of a flow of packets, and classifies the traffic as either normal or anomalous, based on the magnitude of the computed exponent. Preliminary results show the proposed chaotic measure achieved a detection (classification) accuracy of about 98%, which is greater than that of an Artificial Neural Network. Also, contrary to available supervised machine learning mechanisms, this technique does not require any offline training. This approach is capable of not only detecting offline threats, but has the potential of being applied over live traffic flows using DNS filters.
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Chen, Hsien-Pu, Muneer Mohammad, and Laszlo B. Kish. "Current Injection Attack against the KLJN Secure Key Exchange." Metrology and Measurement Systems 23, no. 2 (June 1, 2016): 173–81. http://dx.doi.org/10.1515/mms-2016-0025.

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AbstractThe Kirchhoff-law-Johnson-noise (KLJN) scheme is a statistical/physical secure key exchange system based on the laws of classical statistical physics to provide unconditional security. We used the LTSPICE industrial cable and circuit simulator to emulate one of the major active (invasive) attacks, the current injection attack, against the ideal and a practical KLJN system, respectively. We show that two security enhancement techniques, namely, the instantaneous voltage/current comparison method, and a simple privacy amplification scheme, independently and effectively eliminate the information leak and successfully preserve the system’s unconditional security.
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Alfraih Abdulaziz Nasser, A., and Wen Bo Chen. "NTP DRDoS Attack Vulnerability and Mitigation." Applied Mechanics and Materials 644-650 (September 2014): 2875–80. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2875.

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The Network Time Protocol (NTP) is used to synchronize clocks of various computer devices such as personal computers, tablets, and phones based their set time zones. The network of devices that use these NTP servers form a huge distributed network that attracted a number of attacks from late 2013 towards early 2014. This paper presents a hands-on test of the Distributed Reflection Denial of Service (DRDoS) attack by the monlist command, provides more vulnerability in the protocol, and offers mitigation to these vulnerabilities. A Kali Linux server was used to test the monlist command on its localhost. The results showed that a request with a size of 234 bytes got a response of 4,680 bytes. A busy NTP server can return up to 600 addresses which were theoretically calculated to return approximately 48 kilobytes in 100 packets. Consequently, this results in an amplification factor of 206×. The knowledge of the way the attack can be propagated was an important step in thwarting the attack and mitigating more such threats in the same protocol.
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Malekzadeh, Mina, Moghis Ashrostaghi, and M. H. Shahrokh Abadi. "Amplification-based Attack Models for Discontinuance of Conventional Network Transmissions." International Journal of Information Engineering and Electronic Business 7, no. 6 (November 8, 2015): 15–22. http://dx.doi.org/10.5815/ijieeb.2015.06.03.

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Veeraraghavan, Prakash, Dalal Hanna, and Eric Pardede. "NAT++: An Efficient Micro-NAT Architecture for Solving IP-Spoofing Attacks in a Corporate Network." Electronics 9, no. 9 (September 14, 2020): 1510. http://dx.doi.org/10.3390/electronics9091510.

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The Internet Protocol (IP) version 4 (IPv4) has several known vulnerabilities. One of the important vulnerabilities is that the protocol does not validate the correctness of the source address carried in an IP packet. Users with malicious intentions may take advantage of this vulnerability and launch various attacks against a target host or a network. These attacks are popularly known as IP Address Spoofing attacks. One of the classical IP-spoofing attacks that cost several million dollars worldwide is the DNS-amplification attack. Currently, the availability of solutions is limited, proprietary, expensive, and requires expertise. The Internet is subjected to several other forms of amplification attacks happening every day. Even though IP-Spoofing is one of the well-researched areas since 2005, there is no holistic solution available to solve this problem from the gross-root. Also, every solution assumes that the attackers are always from outside networks. In this paper, we provide an efficient and scalable solution to solve the IP-Spoofing problem that arises from malicious or compromised inside hosts. We use a modified form of Network Address Translation (NAT) to build our solution framework. We call our framework as NAT++. The proposed infrastructure is robust, crypto-free, and easy to implement. Our simulation results have shown that the proposed NAT++ infrastructure does not consume more than the resources required by a simple NAT.
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Dissertations / Theses on the topic "Amplification attack"

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Göran, Gustafsson, and Lundberg Sebastian. "Överbelastningsattacker genom öppna reläer." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-34909.

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Detta arbete behandlar en specifik typ av överbelastningsattack som blir allt mer populär. Dessa attacker utförs genom öppna reläer med syftet att få ut en avsevärt mycket högre effekt än den som annars är uppnåbar. Granskning av attacker utförda genom tjänsterna DNS och NTP har utförts med syftet att ge en klar bild av hur allvarligt hotet är och även klargöra hur en systemadministratör kan säkra tjänsterna för att skydda både sina egna och andras resurser. Resultaten av undersökningar visar att en attack utförd genom en DNS-tjänst ger under optimala förhållanden en amplifikationsfaktor av "102.4" och en attack genom en NTP-tjänst ger under optimala förhållanden en amplifikationsfaktor av "229.16". Resultaten visar även att problemet kan lösas helt eller delvis genom att begränsa tillåtna nätverk eller stänga av rekursion i DNS och kommandon i NTP.
This work concerns a specific type of Denial of Service attack which is becoming increasingly popular. These attacks are carried out through open relays with the purpose of getting a significantly higher effect than otherwise achievable. Examination of attacks carried out through the services DNS and NTP have been conducted with the purpose of providing a clear picture of how serious the threat is and also clarify how a system administrator can secure the services to protect both their own and others resources. The results of our studies show that an attack performed through a DNS service gives under optimal conditions a amplification factor of "102.4" and an attack through a NTP service gives under optimal conditions a amplification factor of "229.16". The results also show that the problem can be solved in whole or in part by limiting the allowed network or disable recursion in DNS and commands in NTP.
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Avanzato, Simone. "Sicurezza e DNS: test di attacco e difesa." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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Il DNS, Domain Name System, è un’infrastruttura attiva da decenni ed è basilare per il corretto funzionamento di Internet, essendo il punto di collegamento tra lo spazio dei nomi di dominio e lo spazio degli indirizzi IP. Senza di esso molti servizi fra i quali mail e navigazione, non potrebbero essere utilizzati. Molte aziende, inoltre, fanno affidamento a un proprio server DNS per poter gestire al meglio il proprio dominio. Data la sua ubiquità ed essenzialità, si deve porre molta attenzione ai fattori che ne minacciano la sicurezza e in particolar modo ai crescenti attacchi informatici. Nel progetto svolto si vogliono verificare gli effetti degli attacchi più noti e frequenti in grado di compromettere un’infrastruttura DNS, studiando poi delle strategie di difesa e prevenzione che possano garantire la disponibilità del servizio e la consistenza dell’informazione trasmessa. Il primo capitolo del documento fornisce una panoramica generale sul DNS sia dal punto di vista strutturale che funzionale. Nel secondo capitolo vengono esaminate le problematiche tipiche del DNS, interne ed esterne con particolare riguardo per le varie tipologie di attacco. Per il terzo capitolo sono stati effettuati alcuni test pratici su un server DNS. Si è proceduto inizialmente con il setup dello scenario di rete, con un server DNS vittima, una macchina attaccante, la scelta dei tool e l'implementazione degli attacchi. Per ogni test effettuato, vengono riportati gli effetti sulla macchina attaccata. Infine vengono fornite diverse possibilità e metodologie di difesa, mitigazione e prevenzione. Gli attacchi scelti per i test sono DNS flood, DNS amplification e DNS spoofing tramite man-in-the-middle. Nel quarto capitolo si prende in esame un caso di attacco reale di tipo DNS flood avvenuto presso l’azienda dove è stato svolto il progetto. Viene fornita la descrizione dell’attacco, le conseguenze sui server DNS aziendali e la strategia difensiva adottata.
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Dussutour, Audrey. "Organisation spatio-temporelle des déplacements collectifs chez les fourmis." Toulouse 3, 2004. http://www.theses.fr/2004TOU30242.

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This study deals with the organisation of collective movements in ants in presence of environmental heterogeneities, particularly in situations involving crowding. We chose two species of ants, characterised by different degrees of polymorphism, as well as by their mode of food transport. Our aim is to identify the link between the behavioural rules observed at the scale of the individual and the spatio-temporal organisation observed at the scale of the group. Ndependently of the species, we found that the regulation of traffic in crowding situations depends both on interattraction processes, via the communication through the chemical trail, and on dispersion phenomena. These latter vary as a function of the size of the individuals and of the task they achieve, but give rise to comparable organisations in the two species studied. The originality of this work lies in the fact that it shows that the mechanisms of dispersion allowing the regulation of the traffic and the prevention of crowding are a by-product of the interattraction processes.
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CHEN, JYUN-HONG, and 陳俊宏. "Domain Name System Amplification Attack Resolution and Defense." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/46avda.

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碩士
國立雲林科技大學
資訊管理系
105
Domain Name System Amplification Attack (DNS) has been a very common attack type in recent years. As the network grows, it is easy to achieve Denial of Service (DoS) attacks. Paralyze the victim's network, so that the victims can not be normal operation. But also can set the power of the crowd at the same time decentralized distributed denial of service attacks (Distributed Denial of Service, DDoS) is to allow users a headache. Many DNS servers have solutions to this problem, such as the ACL (Access Control List) restriction, the close recursive query function, and so on, can be effectively attacked or exploited to attack the DNS attack attacks. Of the DNS server for adequate protection. But for the end user does not provide good protection measures. In this paper, we study the protection rules of the DNS server and the intrusion detection system based on DNS and the open source intrusion detection system, and combine the characteristics of the attack packets to make the intrusion detection system provide the security of end-user protection DNS amplification attack. Protection. In this paper, an effective DNS amplification attack prevention rule is formulated, so that the internal network server or the end user can have a good security environment not to be amplified attack. This rule can be combined with the intrusion detection system inline mode (Inline Mode) with the firewall can be the actual block (drop, block ... and other actions), or just observe and does not affect the actual flow of the detection mode (Sniffer Mode) , Are can be used with the demand environment. Keywords：DNS, Amplification Attack, DDOS, Snort, intrusion detection systems
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LAN, YI-CHIAO, and 籃奕喬. "Defense DNS Distributed Denial of Service Amplification Attack." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/6m7687.

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碩士
國立中正大學
雲端計算與物聯網數位學習碩士在職專班
106
Nowaday, the enterprise network faces a huge number of network attacks from the Internet. Although many network security equipments and softwares have been deployed in the enterprise network, enterprises still face high security threats. This may due to two main reasons, namely human factor and network system. When administrators receive malicious attack alerts, they must immediately find the device been attacked from many devices and solve the problem with various defneding methods such that the enterprise network can be recovered as soon as possible. A malicious attack may cause the enterprise a huge loss in business. Although most of the network device manufacturers provided RESTful API to the network administrators to reduce the management complexity, the network administrators still face great challenge on dealing with network attachs due to the large number devices and device manufacturers which have their own APIs.. In this thesis, we propose a SDN-based mechanism to tackle with DNS DDoS amplification blocking attack. Through the combination of traditional network and software defined network, the mechanism adopts chat robot as the core of connecting system architecture and machine learning mechanism to implement a centralized control management system and a monitoring system on real-time packet processing. The monitoring rules are based on the history of the query domain name as well as characteristics packet behaviors. An enterprise module is then built to detect anormal packet behaviors in real time. The proposed mechanism can be applied to any enterprise networks such that, in addition to reducing the manpower and network attck handling time, it can improve the quality of the enterprise network..
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Lu, Shih-Yang, and 呂世暘. "DDoS Attack Analysis and Prevention based on DNS Amplification – An Example of University of Taipei." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/rs6v42.

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碩士
臺北市立大學
資訊科學系碩士在職專班
104
DNS is the one of most indispensable infrastructures of Internet service. Any resource connected to the Internet, DNS translate its domain name into IP address. Before the Internet was not yet universal, DNS security was not an important topic at network research. At present people are growing needs for Internet service, DNSs become that hackers attack targets. Recently DNS amplification attacks events of Internet increase rapidly, because DNS protocol has design flaws and the asymmetry in size between DNS queries and replies. Therefore, DNS exists much vulnerability. Hackers can use the distributed Denial of Service attack to destroy DNS services. However, most people were not aware that their DNS servers become accomplices on Internet attacks. In this thesis, we will study an overview of DNS evolution and architecture, and explore the reasons of DNS amplification DDoS attacks. The research sample focuses on University of Taipei. According to these reasons, we propose some related precautions to strengthen the security of our DNS servers and avoid that our DNS servers become accomplices of DNS amplification DDoS attacks. After the implementations by our precautions, our methods are effective.
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Books on the topic "Amplification attack"

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Nolan, T. J., T. B. Nutman, and G. A. Schad. Strongyloidosis. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780198570028.003.0064.

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Strongyloidosis is an intestinal parasitism caused by the threadworm, Strongyloides stercoralis. The parasite, occurring in dogs, primates and man, is found throughout the moist tropics, as well as in temperate areas where poor sanitation or other factors facilitate the occurrence of faecally transmitted organisms. In some parts of the world, notably Africa and New Guinea, human infections caused by S. fülleborni have been reported. In Africa, the latter is primarily a parasite of primates, but in New Guinea, no animal host is known. S. stercoralis is unique among zoonotic nematodes, in that larvae passing in the faeces can give rise to a free-living generation of worms which, in turn, give rise to infective larvae. This life history alternative (i.e. heterogonic development) acts as an amplification mechanism, increasing the population of infective larvae in the external environment. The infective larvae are active skin penetrators; infection per os , while possible, is probably of limited importance. Because the parasitic female’s eggs hatch internally, a potential for autoinfection exists when precociously developing larvae attain infectivity while still in the host. This is another virtually unique feature of S. stercoralis infections in both its human and animal hosts. Autoinfection can occasionally escape control by the host, with massive re-penetration and larval migration. This can cause pulmonary or cerebro-spinal strongyloidosis as well as fulminant intestinal parasitism. Control of canine strongyloidosis has been achieved in kennels by strategic use of anthelmintics. Given the lack of epidemiological information community-based programs to control human strongyloidosis have not been attempted. The growing importance of human strongyloidosis depends upon the unique ability of S. stercoralis to replicate within its host and to behave as a potentially fatal opportunistic pathogen in immunocompromised hosts, particularly in those receiving corticosteroids.
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Book chapters on the topic "Amplification attack"

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Liu, Zheng, Mingwei Xu, Jiahao Cao, and Qi Li. "TSA: A Two-Phase Scheme Against Amplification DDoS Attack in SDN." In Communications in Computer and Information Science, 483–96. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8890-2_37.

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Anagnostopoulos, Marios. "Amplification DoS Attacks." In Encyclopedia of Cryptography, Security and Privacy, 1–3. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-642-27739-9_1486-1.

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Kambourakis, Georgios, Tassos Moschos, Dimitris Geneiatakis, and Stefanos Gritzalis. "Detecting DNS Amplification Attacks." In Critical Information Infrastructures Security, 185–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89173-4_16.

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Krupp, Johannes, Mohammad Karami, Christian Rossow, Damon McCoy, and Michael Backes. "Linking Amplification DDoS Attacks to Booter Services." In Research in Attacks, Intrusions, and Defenses, 427–49. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66332-6_19.

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Krämer, Lukas, Johannes Krupp, Daisuke Makita, Tomomi Nishizoe, Takashi Koide, Katsunari Yoshioka, and Christian Rossow. "AmpPot: Monitoring and Defending Against Amplification DDoS Attacks." In Research in Attacks, Intrusions, and Defenses, 615–36. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26362-5_28.

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MacFarland, Douglas C., Craig A. Shue, and Andrew J. Kalafut. "Characterizing Optimal DNS Amplification Attacks and Effective Mitigation." In Passive and Active Measurement, 15–27. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15509-8_2.

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Colella, Antonio, and Clara Maria Colombini. "Amplification DDoS Attacks: Emerging Threats and Defense Strategies." In Advanced Information Systems Engineering, 298–310. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-319-10975-6_24.

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Kitagawa, Fuyuki, Takahiro Matsuda, Goichiro Hanaoka, and Keisuke Tanaka. "Efficient Key Dependent Message Security Amplification Against Chosen Ciphertext Attacks." In Information Security and Cryptology - ICISC 2014, 84–100. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15943-0_6.

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Fouque, Pierre-Alain, and Pierre Karpman. "Security Amplification against Meet-in-the-Middle Attacks Using Whitening." In Cryptography and Coding, 252–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45239-0_15.

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Kopp, Daniel, Christoph Dietzel, and Oliver Hohlfeld. "DDoS Never Dies? An IXP Perspective on DDoS Amplification Attacks." In Passive and Active Measurement, 284–301. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72582-2_17.

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Conference papers on the topic "Amplification attack"

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Krupp, Johannes, Michael Backes, and Christian Rossow. "Identifying the Scan and Attack Infrastructures Behind Amplification DDoS Attacks." In CCS'16: 2016 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2976749.2978293.

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Han, Myoungbo, Thang Nguyen Canh, Si Chul Noh, Junmin Yi, and Minho Park. "DAAD: DNS Amplification Attack Defender in SDN." In 2019 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2019. http://dx.doi.org/10.1109/ictc46691.2019.8939897.

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Yu, Huiming, Xiangfeng Dai, Tom Baxliey, Xiaohong Yuan, and Terry Bassett. "A visualization analysis tool for DNS amplification attack." In 2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI 2010). IEEE, 2010. http://dx.doi.org/10.1109/bmei.2010.5639324.

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Mehic, M., M. Voznak, J. Safarik, P. Partila, and M. Mikulec. "Using DNS amplification DDoS attack for hiding data." In SPIE Sensing Technology + Applications, edited by Sos S. Agaian, Sabah A. Jassim, and Eliza Y. Du. SPIE, 2014. http://dx.doi.org/10.1117/12.2050700.

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Meitei, Irom Lalit, Khundrakpam Johnson Singh, and Tanmay De. "Detection of DDoS DNS Amplification Attack Using Classification Algorithm." In ICIA-16: International Conference on Informatics and Analytics. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2980258.2980431.

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Zhang, Yuantian, and Yang Cheng. "An Amplification DDoS Attack Defence Mechanism using Reinforcement Learning." In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, 2019. http://dx.doi.org/10.1109/smartworld-uic-atc-scalcom-iop-sci.2019.00145.

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Chang Liu, Gang Xiong, Jie Liu, and Gaopeng Gou. "Detect the reflection amplification attack based on UDP protocol." In 2015 10th International Conference on Communications and Networking in China (ChinaCom). IEEE, 2015. http://dx.doi.org/10.1109/chinacom.2015.7497948.

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Xing, Xiaodong, Tao Luo, Jianfeng Li, and Yang Hu. "A defense mechanism against the DNS amplification attack in SDN." In 2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC). IEEE, 2016. http://dx.doi.org/10.1109/icnidc.2016.7974530.

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Soliman, Ahmed K., Cherif Salama, and Hoda K. Mohamed. "Detecting DNS Reflection Amplification DDoS Attack Originating from the Cloud." In 2018 13th International Conference on Computer Engineering and Systems (ICCES). IEEE, 2018. http://dx.doi.org/10.1109/icces.2018.8639414.

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Ko, Eunhye, Seongmin Park, Sekwon Kim, Kyungho Son, and Hwankuk Kim. "SIP amplification attack analysis and detection in VoLTE service network." In 2016 International Conference on Information Networking (ICOIN). IEEE, 2016. http://dx.doi.org/10.1109/icoin.2016.7427126.

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