• The Journal of the Korea Contents Association
• /
• v.4 no.1
• /
• pp.49-55
• /
• 2004

DDoS is an attack type that interfere with normal service by running out network bandwidth, process throughput, and system resource. It can be recognized intuitively by network slowdown and connection impossibility state, but it is necessary to detect DDoS attack by exact and quantitative analysis. In this paper, the exact and efficient DDoS attack detection system which is able to detect traffic flooding by MIB information, and attack traffic by packet analysis is proposed and realized.

• Smart Media Journal
• /
• v.4 no.4
• /
• pp.24-32
• /
• 2015

Recently, SDN is actively used as datacenter networks and gradually increase its applied areas. Along with this change of networking environment, research of deploying network security systems on SDN becomes highlighted. Especially, systems for detecting network flooding attacks by monitoring every packets through ports of OpenFlow switches have been proposed. However, because of the centralized management of a SDN controller which manage multiple switches, it may be substantial overhead that the attack detection system continuously monitors all the flows. In this paper, a sampling based network flooding attack detection and prevention system is proposed to reduce the overhead of monitoring packets and to achieve reasonable functionality of attack detection and prevention. The proposed system periodically takes sample packets of network flows with the given sampling conditions, analyzes the sampled packets to detect network flooding attacks, and block the attack flows actively by managing the flow entries in OpenFlow switches. As network traffic sampler, sFlow agent is used, and snort, an opensource IDS, is used to detect network flooding attack from the sampled packets. For active prevention of the detected attacks, an OpenDaylight application is developed and applied. The proposed system is evaluated on the local testbed composed with multiple OVSes (Open Virtual Switch), and the performance and overhead of the proposed system under various sampling condition is analyzed.

• The Journal of the Korea Contents Association
• /
• v.5 no.5
• /
• pp.172-181
• /
• 2005

The latest attack type against network traffic appeared by worm and bot that are advanced in DDoS. It is difficult to detect them because they are diversified, intelligent, concealed and automated. The exisiting traffic analysis method using SNMP has a vulnerable problem; it considers normal P2P and other application program to be harmful traffic. It also has limitation that does not analyze advanced programs such as worm and bot to harmful traffic. Therefore, we analyzed harmful traffic out Protocol and Port analysis. We also classified traffic by protocol, well-known port, P2P port, existing attack port, and specification port, apply singularity weight to detect, and analyze attack availability. As a result of simulation, it is proved that it can effectively detect P2P application, worm, bot, and DDoS attack.

• Proceedings of the Korea Contents Association Conference
• /
• 2003.11a
• /
• pp.105-108
• /
• 2003

The recent hacking trend is a traffic flooding attack against a bandwidth in the network grows more and more. On the other hand, technology, which extracts attack traffic in the network from these threats, is still short. Therefore, we propose methodology which can measure traffic that threaten network services, and algorithm which can detect DDoS attacks effectively.

• The KIPS Transactions:PartC
• /
• v.15C no.5
• /
• pp.351-358
• /
• 2008

Recently, as network flooding attacks such as DoS/DDoS and Internet Worm have posed devastating threats to network services, rapid detection and proper response mechanisms are the major concern for secure and reliable network services. However, most of the current Intrusion Detection Systems(IDSs) focus on detail analysis of packet data, which results in late detection and a high system burden to cope with high-speed network environment. In this paper we propose a lightweight and fast detection mechanism for traffic flooding attacks. Firstly, we use SNMP MIB statistical data gathered from SNMP agents, instead of raw packet data from network links. Secondly, we use a machine learning approach based on a Support Vector Machine(SVM) for attack classification. Using MIB and SVM, we achieved fast detection with high accuracy, the minimization of the system burden, and extendibility for system deployment. The proposed mechanism is constructed in a hierarchical structure, which first distinguishes attack traffic from normal traffic and then determines the type of attacks in detail. Using MIB data sets collected from real experiments involving a DDoS attack, we validate the possibility of our approaches. It is shown that network attacks are detected with high efficiency, and classified with low false alarms.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.2
• /
• pp.39-46
• /
• 2011

Privacy IP hacking problems such as invasion of privacy, password cracking, voice wiretapping and internet over charged occurred, because VoIP internet voice phone service gradually spread. This thesis attempted to attack the VoIP service network by application. First use application to spoof IP address then attempted wiretap the VoIP service and sends a lot of messages to disturb service movement. At this point, we connected VoIP soft terminal, so we can operate real-time filtering operator to block the SIP Flooding offence by monitor the traffic and detect the location where it got attacked. This thesis used experiment to prove it is possible to detect the offence and defend from SIP Flooding offence.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.22 no.4
• /
• pp.809-817
• /
• 2012

One of the OSI 7 Layer DDoS Attack, HTTP POST DDoS can deny legitimate service by web server resource depletion. This Attack can be executed with less network traffic and legitimate TCP connections. Therefore, It is difficult to distinguish DDoS traffic from legitimate users. In this paper, I propose an anomaly HTTP POST traffic detection algorithm and http each page Content-Length field size limit with defense method for HTTP POST DDoS attack. Proposed method showed the result of detection and countermeasure without false negative and positive to use the r-u-dead-yet of HTTP POST DDoS attack tool and the self-developed attack tool.

• KSCI Review
• /
• v.14 no.2
• /
• pp.235-244
• /
• 2006

This paper attacked the unknown DoS which mixed a DoS attack, Worm and the Trojan horse which used IP Source Address Spoofing and Smurf through the SYN Flooding way that UDP, ICMP, Echo, TCP Syn packet operated. the applications that used TCP/UDP in VoIP service networks. Define necessity of a Dynamic Update Engine for a prevention, and measure Miss traffic at RT statistics of inbound and outbound parts in case of designs of an engine at IPS regarding an Self-learning module and a statistical attack spread. and design a logic engine module. Three engines judge attack grades (Attack Suspicious, Normal), and keep the most suitable filtering engine state through AND or OR algorithms at Footprint Lookup modules. A Real-Time Dynamic Engine and Filter updated protected VoIP service from DoS attacks, and strengthened Ubiquitous Security anger, and were turned out to be.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.6 s.44
• /
• pp.165-174
• /
• 2006

This paper attacked the unknown DoS which mixed a DoS attack, Worm and the Trojan horse which used IP Source Address Spoofing and Smurf through the SYN Flooding way that UDP, ICMP, Echo, TCP Syn packet operated, the applications that used TCP/UDP in VoIP service networks. Define necessity of a Dynamic Update Engine for a prevention, and measure Miss traffic at RT statistics of inbound and outbound parts in case of designs of an engine at IPS regarding an Self-learning module and a statistical attack spread, and design a logic engine module. Three engines judge attack grades (Attack, Suspicious, Normal), and keep the most suitable filtering engine state through AND or OR algorithms at Footprint Lookup modules. A Real-Time Dynamic Engine and Filter updated protected VoIP service from DoS attacks, and strengthened Ubiquitous Security anger, and were turned out to be.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.1
• /
• pp.203-209
• /
• 2014

Today, Distributed denial of service (DDoS) attack present a very serious threat to the stability of the internet. The DDoS attack, which is consuming all of the computing or communication resources necessary for the service, is known very difficult to protect. The DDoS attack usually transmits heavy traffic data to networks or servers and they cannot handle the normal service requests because of running out of resources. It is very hard to prevent the DDoS attack. Therefore, an intrusion detection system on large network is need to efficient real-time detection. In this paper, we propose the detection mechanism using analysis of flow information against DDoS attacks in order to guarantee the transmission of normal traffic and prevent the flood of abnormal traffic. The OPNET simulation results show that our ideas can provide enough services in DDoS attack.