• Title/Summary/Keyword: DoS Attack Detection

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A RTSD Mechanism for Detection of DoS Attack on TCP Network (TCP 네트워크에서 서비스거부공격의 탐지를 위한 RTSD 메커니즘)

  • 이세열;김용수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.252-255
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    • 2002
  • As more critical services are provided in the internet, the risk to these services from malicious users increases. Several networks have experienced problems like Denial of Service(DoS) attacks recently. We analyse a network-based denial of service attack, which is called SYM flooding, to TCP-based networks. It occurs by an attacker who sends TCP connection requests with spoofed source address to a target system. Each request causes the targeted system to send instantly data packets out of a limited pool of resources. Then the target system's resources are exhausted and incoming TCP port connections can not be established. The paper is concerned with a detailed analysis of TCP SYN flooding denial of service attack. In this paper, we propose a Real Time Scan Detector(RTSD) mechanism and evaluate it\`s Performance.

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Development of Intrusion Detection System for GOOSE Protocol Based on the Snort (GOOSE 프로토콜 환경에서 Snort 기반의 침입 탐지 시스템 개발)

  • Kim, Hyeong-Dong;Kim, Ki-Hyun;Ha, Jae-Cheol
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.23 no.6
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    • pp.1181-1190
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    • 2013
  • The GOOSE(Generic Object Oriented Substation Event) is used as a network protocol to communicate between IEDs(Intelligent Electronic Devices) in international standard IEC 61850 of substation automation system. Nevertheless, the GOOSE protocol is facing many similar threats used in TCP/IP protocol due to ethernet-based operation. In this paper, we develop a IDS(Intrusion Detection System) for secure GOOSE Protocol using open software-based IDS Snort. In this IDS, two security functions for keyword search and DoS attack detection are implemented through improvement of decoding and preprocessing component modules. And we also implement the GOOSE IDS and verify its accuracy using GOOSE packet generation and communication experiment.

A Security method and Performance evaluation of preventing DoS attack against DAD in MANET (MANET 환경에서 중복 주소 탐지에 대한 DoS 공격을 방지하는 보안 기법과 성능 평가)

  • Lim, Jeong-Mi;Park, Chang-Seop
    • Journal of Korea Multimedia Society
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    • v.12 no.8
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    • pp.1099-1108
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    • 2009
  • The study of IP address allocation in MANET can be categories into Stateful and Stateless. The one, special node monitors other nodes' IP address and allocates IF address. And the other, node generates IP address by itself. Nodes in MANET have mobility and restricted resource, so Stateless is more suitable than Stateful. But, in Stateless, node requires DAD process because of unique IP address allocation. And Dos attack can be happened in DAD precess. In this paper, we propose a security method on preventing DoS attack against DAD in MANET using one-way hash function. Since, Computation of one-way hash function is suitable for nodes' restricted resource character in MANET. And we evaluate performance using NS2 and compare with other security method which is CGA using signature.

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Blocking Intelligent Dos Attack with SDN (SDN과 허니팟 기반 동적 파라미터 조절을 통한 지능적 서비스 거부 공격 차단)

  • Yun, Junhyeok;Mun, Sungsik;Kim, Mihui
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.1
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    • pp.23-34
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    • 2022
  • With the development of network technology, the application area has also been diversified, and protocols for various purposes have been developed and the amount of traffic has exploded. Therefore, it is difficult for the network administrator to meet the stability and security standards of the network with the existing traditional switching and routing methods. Software Defined Networking (SDN) is a new networking paradigm proposed to solve this problem. SDN enables efficient network management by programming network operations. This has the advantage that network administrators can flexibly respond to various types of attacks. In this paper, we design a threat level management module, an attack detection module, a packet statistics module, and a flow rule generator that collects attack information through the controller and switch, which are components of SDN, and detects attacks based on these attributes of SDN. It proposes a method to block denial of service attacks (DoS) of advanced attackers by programming and applying honeypot. In the proposed system, the attack packet can be quickly delivered to the honeypot according to the modifiable flow rule, and the honeypot that received the attack packets analyzed the intelligent attack pattern based on this. According to the analysis results, the attack detection module and the threat level management module are adjusted to respond to intelligent attacks. The performance and feasibility of the proposed system was shown by actually implementing the proposed system, performing intelligent attacks with various attack patterns and attack levels, and checking the attack detection rate compared to the existing system.

Intrusion Detection: Supervised Machine Learning

  • Fares, Ahmed H.;Sharawy, Mohamed I.;Zayed, Hala H.
    • Journal of Computing Science and Engineering
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    • v.5 no.4
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    • pp.305-313
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    • 2011
  • Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate.

A study on the detection of DDoS attack using the IP Spoofing (IP 스푸핑을 통한 DDoS 공격 탐지 방안에 대한 연구)

  • Seo, Jung-Woo;Lee, Sang-Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.1
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    • pp.147-153
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    • 2015
  • Since the DoS(Denial of Service) attack is still an important vulnerable element in many web service sites, sites including public institution should try their best in constructing defensive systems. Recently, DDoS(Distributed Denial of Service) has been raised by prompting mass network traffic that uses NTP's monlist function or DoS attack has been made related to the DNS infrastructure which is impossible for direct defense. For instance, in June 2013, there has been an outbreak of an infringement accident where Computing and Information Agency was the target. There was a DNS application DoS attack which made the public institution's Information System impossible to run its normal services. Like this, since there is a high possibility in having an extensive damage due to the characteristics of DDoS in attacking unspecific information service and not being limited to a particular information system, efforts have to be made in order to minimize cyber threats. This thesis proposes a method for using TTL (Time To Live) value in IP header to detect DDoS attack with IP spoofing, which occurs when data is transmitted under the agreed regulation between the international and domestic information system.

Traffic Flooding Attack Detection using SNMP MIB (SNMP MIB 기반 트래픽 폭주공격 탐지)

  • Park, Jun-Sang;Park, Dai-Hee;Kim, Myung-Sup
    • Annual Conference of KIPS
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    • 2008.05a
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    • pp.935-938
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    • 2008
  • DoS/DDoS 공격과 웜 공격으로 대표되는 트래픽 폭주 공격은 그 특성상 사전 차단이 어렵기 때문에 빠르고 정확한 탐지는 공격 탐지 시스템이 갖추어야 할 필수요건이다. 기존의 SNMP MIB 기반 트래픽 폭주공격 탐지 방법은 1 분 이상의 탐지 시간을 요구하였다. 본 논문은 SNMP MIB 객체의 상관 관계를 이용한 빠른 트래픽 폭주 공격 탐지 알고리즘을 제안한다. 또한 빠른 탐지 시간으로 발생되는 시스템의 부하와 탐지 트래픽을 최소화하는 방안도 함께 제시한다. 공격 탐지 방법은 3 단계로 구성되는데, 1 단계에서는 MIB 정보의 갱신주기를 바탕으로 탐지 시점을 결정하고, 2 단계에서는 MIB 정보간의 상관 관계를 이용하여 공격의 징후를 판단하고, 3 단계에서는 프로토콜 별 상세 분석을 통하여 공격 탐지뿐만 아니라 공격 유형까지 판단한다. 따라서 빠르고 정확하게 공격을 탐지할 수 있고, 공격 유형을 분류해 낼 수 있어 신속한 대처가 가능해 질 수있다.

A Survey on Defense Mechanism against Distributed Denial of Service (DDoS) Attacks in Control System

  • Kwon, YooJin
    • KEPCO Journal on Electric Power and Energy
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    • v.1 no.1
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    • pp.55-59
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    • 2015
  • Denial of Service (DoS) attack is to interfere the normal user from using the information technology services. With a rapid technology improvements in computer and internet environment, small sized DoS attacks targeted to server or network infrastructure have been disabled. Thus, Distributed Denial of Service (DDoS) attacks that utilizes from tens to several thousands of distributed computers as zombie PC appear to have as one of the most challenging threat. In this paper, we categorize the DDoS attacks and classify existing countermeasures based on where and when they prevent, detect, and respond to the DDoS attacks. Then we propose a comprehensive defense mechanism against DDoS attacks in Control System to detect attacks efficiently.

Data Mining based Denial of Service Attack Detection Scheme (데이터 마이닝을 이용한 서비스 거부 공격 탐지 기법)

  • 박호상;조은경;강용혁;엄영익
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10a
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    • pp.715-717
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    • 2003
  • DoS (Denial of Service) 공격은 주로 victim 호스트에 대량의 패킷을 보내거나 비정상적인 패킷을 보냄으로써 정상 사용자가 서비스를 이음하지 못하도록 하는 공격을 의미한다. 이러한 DoS 공격을 탐지하기 위해 다양한 기법들이 개발되어 왔으나, 공격의 종류와 방법은 시간이 흐를수록 매우 다양해지고 있어 이를 탐지하는데 한계가 있다. 본 논문에서는 네트워크 패킷의 헤더정보를 감사 자료로 가지고 있는 NIDS (Network-based Intrusion Detection System)에 데이터 마이닝 기법을 적용기켜 이러한 DoS 공격을 탐지할 수 있는 기법을 제안한다. 이 기법을 이용하면 빠르고 자동화된 방법으로 DoS 공격을 탐지할 수 있다. 본 논문에서는 제안 기법을 이용하여 SYN Flooding 공격과 Teardown 공격에 대한 탐지가 가능함을 보인다.

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DoS Attack Control Design of IoT System for 5G Era

  • Rim, Kwangcheol;Lim, Dongho
    • Journal of information and communication convergence engineering
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    • v.16 no.2
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    • pp.93-98
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    • 2018
  • The Internet of Things (IoT) is a form of the emerging 4th industry in the 5G era. IoT is expected to develop naturally in our daily life in the 5G era in which high-speed communication will be completed. Along with the rise of IoT, concerns about security and malicious attacks are also increasing. This paper examines DoS attacks, which are one of the representative security threats of IoT and proposes a local detection and blocking system that are suitable for response to such attacks. First, systems of the LoRaWAN type, which are most actively researched in the IoT system field and DoS attacks that can occur in such systems were examined. Then, the inverse order tree algorithm using regional characteristics was designed as a cluster analysis form. Finally, a system capable of defending denial-of-service attacks in the 5G IoT system using local detection and blocking with the Euclidean distance was designed.