• Title/Summary/Keyword: DRDoS

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Multi-level detection method for DRDoS attack (DRDoS 공격에 대한 다단계 탐지 기법)

  • Baik, Nam-Kyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1670-1675
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    • 2020
  • In this study, to provide the basis for establishing effective network based countermeasures against DRDoS(Distributed Reflection Denial of Service) attacks, we propose a new 'DRDoS attack multi-level detection method' that identifies the network based characteristics of DRDoS and applies probability and statistical techniques. The proposed method removes the limit to which normal traffic can be indiscriminately blocked by unlimited competition in network bandwidth by amplification of reflectors, which is characteristic of DRDoS. This means that by comparing 'Server to Server' and 'Outbound Session Incremental' for it, accurate DRDoS identification and detection is possible and only statistical and probabilistic thresholds are applied to traffic. Thus, network-based information security systems can take advantage of this to completely eliminate DRDoS attack frames. Therefore, it is expected that this study will contribute greatly to identifying and responding to DRDoS attacks.

Design and Implementation of Traceback Simulator for Distributed Reflector DoS Attack on Computer Network (네트워크 분산반사 서비스 거부 공격(DRDoS)에 대한 역추적 시뮬레이터 설계 및 구현)

  • Lee, Hyung-Woo
    • The Journal of Korean Association of Computer Education
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    • v.8 no.1
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    • pp.65-72
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    • 2005
  • In this study, we suggest a new mechanism on the design and implementation of IP Traceback system against DDos/DRDoS by Zombie and Reflector attack based on spoofed IP packets. After analysis and comparing on the state-of-arts of several IP traceback mechanisms, we can find their own pros and cons primitives. And then we performed simulations on reflector based DRDoS network packets. In first, we suggest a NS-2 based IP traceback module and implement it for finding its real DRDoS attacker. As a results, we can find advanced new IP traceback scheme for providing enhanced proactive functionality against DRDoS attack.

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Quantitative Approach for Calculating DRDoS Risk

  • Young-Ryul Choi;Nam-Kyun Baik
    • Journal of information and communication convergence engineering
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    • v.21 no.3
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    • pp.192-197
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    • 2023
  • A Distributed reflection denial of service (DRDoS) is a variant of DDoS attacks that threatens the availability of services to legitimate users. In response to this evolving threat landscape, the cybersecurity industry and service providers have intensified their efforts to develop effective countermeasures. Despite these efforts, attackers continue to innovate, developing new strategies and tools while becoming more sophisticated. Consequently, DRDoS attacks continue to be harmful. Therefore, ongoing research and development is essential to improve defense against DRDoS attacks. To advance our understanding and analysis of DRDoS attacks, this study examines the unique characteristics of DRDoS attacks and quantifies the risks involved. Additionally, it adopts a quantitative rather than traditional qualitative methods to derive and apply risk, particularly the probability of loss that can be caused by DRDoS attacks.

A Detect and Defense Mechanism of Stateful DRDoS Attacks (상태기반 DRDoS 공격에 대한 탐지 및 방어기법)

  • Kim, Minjun;Seo, Kyungryong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.5
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    • pp.127-134
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    • 2014
  • In DRDoS(Distributed Reflective Denial of Service) attacks, the victim is bombarded by packets from legitimate reflector unlike DDoS(Distributed Denial of Service) attacks through zombie, which is more dangerous than DDoS attack because it is in stronger disguise. Therefore, the method of filtering packet method on router are useless. Moreover SCTP(Stream Control Transmission Protocol) multi-homing feature, such as with an improved transmission protocol allows detecting attacks is more difficult and the effect of the attack can be maximized. In this paper we propose a DRDoS detection mechanism based on DRDoS utilizing attention to the characteristics of stateful protocols. The proposed scheme is backed by stateful firewall, and detect DRDoS attacks through a rules table and perform a defense treatment against DRDoS attack. Rules table with a simple structure is possible to easily adapt for any kind of stateful protocol can used by DRDoS attack. The experimental result confirm that our proposed scheme well detect DRDoS attacks using SCTP, the next-generation transmission protocol which not known by victim, and reduce the attacking packets rapidly.

Response System for DRDoS Amplification Attacks (DRDoS 증폭 공격 대응 시스템)

  • Kim, Hyo-Jong;Han, Kun-Hee;Shin, Seung-Soo
    • Journal of Convergence for Information Technology
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    • v.10 no.12
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    • pp.22-30
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    • 2020
  • With the development of information and communication technology, DDoS and DRDoS continue to become security issues, and gradually develop into advanced techniques. Recently, IT companies have been threatened with DRDoS technology, which uses protocols from normal servers to exploit as reflective servers. Reflective traffic is traffic from normal servers, making it difficult to distinguish from security equipment and amplified to a maximum of Tbps in real-life cases. In this paper, after comparing and analyzing the DNS amplification and Memcached amplification used in DRDoS attacks, a countermeasure that can reduce the effectiveness of the attack is proposed. Protocols used as reflective traffic include TCP and UDP, and NTP, DNS, and Memcached. Comparing and analyzing DNS protocols and Memcached protocols with higher response sizes of reflective traffic among the protocols used as reflective traffic, Memcached protocols amplify ±21% more than DNS protocols. The countermeasure can reduce the effectiveness of an attack by using the Memcached Protocol's memory initialization command. In future studies, various security-prone servers can be shared over security networks to predict the fundamental blocking effect.

A Study on Countermeasures of Convergence for Big Data and Security Threats to Attack DRDoS in U-Healthcare Device (U-Healthcare 기기에서 DRDoS공격 보안위협과 Big Data를 융합한 대응방안 연구)

  • Hur, Yun-A;Lee, Keun-Ho
    • Journal of the Korea Convergence Society
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    • v.6 no.4
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    • pp.243-248
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    • 2015
  • U-Healthcare is a convergence service with medical care and IT which enables to examine, manage and maintain the patient's health any time and any place. For communication conducted in U-Healthcare service, the transmission methods are used that patient's medical checkup analysis results or emergency data are transmitted to hospital server using wireless communication method. At this moment when the attacker who executes the malicious access makes DRDoS(Distributed Reflection DoS) attack to U-Healthcare devices or BS(Base Station), various damages occur that contextual information of urgent patients are not transmitted to hospital server. In order to deal with this problem, this study suggests DRDoS attack scenario and countermeasures against DRDoS and converges with Big Data which could process large amount of packets. When the attacker attacks U-Healthcare devices or BS(Base Station), DB is interconnected and the attack is prevented if it is coincident. This study analyzes the attack method that could occur in U-Healthcare devices or BS which are remote medical service and suggests countermeasures against the security threat using Big Data.

Estimation of Excited State Dipole Moment of Exalite Dyes by Solvatochromic Shift Studies

  • Inamdar, S. R.;Nadaf, Y.F.;Deshpande, D.K.;Karguppikar, A.M.
    • Journal of Photoscience
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    • v.9 no.1
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    • pp.29-32
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    • 2002
  • The solvent effect in a series of polar and non-polar solvents of varying dielectric constants and refractive indices has been investigated by studying electronic spectra (S$_1$band) of a series of exalite laser dyes at room temperature (25$\pm$1$\^{C}$). These data are used to determine the magnitude ($\mu$$\_$e/) and direction ($\theta$) of the electric dipole moments in the first electronically excited state. The results indicate that the observed band systems in these compounds may be attributed to ←$\pi$ transition.

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DRDoS Attacking Scenario and Countermeasure for Using Weakness of SSDP Protocol in IoT Device (IoT기기에서 SSDP프로토콜 취약점을 이용한 DRDoS공격시나리오 및 대응방안)

  • Hong, Geun-Mok;Won, Jun Hee;Lee, Keun-Ho;Jeon, You-Boo;Lee, Chang-Jun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2016.04a
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    • pp.280-282
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    • 2016
  • 오늘날 IoT 사물기기들의 사용 범위가 늘어나면서 해커들은 IoT 기기에서 네트워크상의 서비스 및 정보검색의 기능을 하는 프로토콜인 SSDP의 취약점을 악용하여 SSDP DRDoS(분산 반사 서비스 거부) 공격이라는 새로운 형태의 공격을 만들어 공격을 시도하고 있다. 이는 단순히 우리 생활에서 쓰이는 IoT 기기의 위협뿐만 아니라 사람의 생명이나 주요 기반시설 등에서 사용되어지는 IoT기기들의 공격으로 이어지면 큰 위험을 나타낼 수 있다. 앞으로 IoT기기들이 점차 증가되어 생활에 편리함과 실용성을 가지고 오는 반면에 해커들은 더욱더 교묘하고 복잡하게 공격을 시도를 할 것이다. 특히 본 논문에서는 DRDoS의 몇 가지 공격방법을 알아보고 그중에 IoT 기기에서 사용되어지는 SSDP프로토콜의 관련연구 및 공격방법들을 알아보고 공격시나리오 및 대응방안을 제안한다.

Advanced DDoS Attack & Corresponding Technical Trends (은닉형 DDoS 공격 및 대응 기술동향)

  • Kim, J.T.;Kim, I.K.;Kang, K.H.
    • Electronics and Telecommunications Trends
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    • v.31 no.6
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    • pp.77-87
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    • 2016
  • 최근 지능화된 DDoS 공격 추세를 반영하여 DRDoS 및 HTTP GET flooding 공격을 네트워크 내 탐지 포인터에서 검출할 수 있는 방법을 살펴본다. DRDoS 공격은 해커들이 스푸핑 된 IP 주소를 사용하기 때문에 기본적으로 은닉형 공격자로 판단할 수 있다. HTTP GET flooding 공격은 해커의 제어 하에 실제적으로 IP 주소를 위장하여 공격을 시도하는 좀비 PC를 검출하는 것도 중요하지만 좀비 PC를 제어하는 C&C 서버로의 통신 채널을 탐지 및 차단하는 것과 C&C 서버에 접근하는 해커를 추적하는 것이 더 원론적인 방어전략이 될 수 있으며 관련 은닉형 DDoS 공격에 대한 국내외 기술개발 동향 및 대응 기술 추세에 대해서 살펴본다.

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Machine Learning-based Detection of DoS and DRDoS Attacks in IoT Networks

  • Yeo, Seung-Yeon;Jo, So-Young;Kim, Jiyeon
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.7
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    • pp.101-108
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    • 2022
  • We propose an intrusion detection model that detects denial-of-service(DoS) and distributed reflection denial-of-service(DRDoS) attacks, based on the empirical data of each internet of things(IoT) device by training system and network metrics that can be commonly collected from various IoT devices. First, we collect 37 system and network metrics from each IoT device considering IoT attack scenarios; further, we train them using six types of machine learning models to identify the most effective machine learning models as well as important metrics in detecting and distinguishing IoT attacks. Our experimental results show that the Random Forest model has the best performance with accuracy of over 96%, followed by the K-Nearest Neighbor model and Decision Tree model. Of the 37 metrics, we identified five types of CPU, memory, and network metrics that best imply the characteristics of the attacks in all the experimental scenarios. Furthermore, we found out that packets with higher transmission speeds than larger size packets represent the characteristics of DoS and DRDoS attacks more clearly in IoT networks.