• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.94-101
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• 2007

We introduce the way to detect the mutation worm. We implemented the program that can generate signature using LCSeq(Longest Common Subsequence) technique in Suffix Tree studied as pattern recognition algorithm. We also showed the process to detect the mutation of CodeRed worm and Nimda worm and evaluated signatures generated by snort and LCSeq.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1206-1213
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• 2006

Fast detection and automatic generation of worm signatures are essential to contain zero-day worms because the speed of self-propagating worms is too fast for humans to respond. In this paper, we propose an automatic signature generation method against worm's attack, and show the effectiveness of the proposed method by implementing it and appling it to the DHT based network and generating the worm signatures for it.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.104.2-104.2
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• 2005

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.821-830
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• 2006

As internet worms are spread out worldwide, the detection and filtering of worms becomes one of hot issues in the internet security. As one of implementation methods to detect worms, the Linux Netfilter kernel module can be used. Its basic operation for worm detection is a string matching where coming packet(s) on the network is/are compared with predefined worm signatures(patterns). A worm can appear in a packet or in two (or more) succeeding packets where some part of worm is in the first packet and its remaining part is in its succeeding packet(s). Assuming that the maximum length of a worm pattern is less than 1024 bytes, we need to perform a string matching up to two succeeding packets of 2048 bytes. To do so, Linux Netfilter keeps the previous packet in buffer and performs matching with a combined 2048 byte string of the buffered packet and current packet. As the number of concurrent connections to be handled in the worm detection system increases, the total size of buffer (memory) increases and string matching speed becomes low In this paper, to reduce the memory buffer size and get higher speed of string matching, we propose a string matching scheme without using buffer. The proposed scheme keeps the partial matching result of the previous packet with signatures and has no buffering for previous packet. The partial matching information is used to detect a worm in the two succeeding packets. We implemented the proposed scheme by modifying the Linux Netfilter. Then we compared the modified Linux Netfilter module with the original Linux Netfilter module. Experimental results show that the proposed scheme has 25% lower memory usage and 54% higher speed compared to the original scheme.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.161-164
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• 2005

As the power of influence of the Internet grows steadily, attacks against the Internet can cause enormous monetary damages nowadays. A worm can not only replicate itself like a virus but also propagate itself across the Internet. So it infects vulnerable hosts in the Internet and then downgrades the overall performance of the Internet or makes the Internet not to work. To response this, worm detection and prevention technologies are developed. The worm detection technologies are classified into two categories, host based detection and network based detection. Host based detection methods are a method which checks the files that worms make, a method which checks the integrity of the file systems and so on. Network based detection methods are a misuse detection method which compares traffic payloads with worm signatures and anomaly detection methods which check inbound/outbound scan rates, ICMP host/port unreachable message rates, and TCP RST packet rates. However, single detection methods like the aforementioned can't response worms' attacks effectively because worms attack the Internet in the distributed fashion. In this paper, we propose a design of distributed worm detection system to overcome the inefficiency. Existing distributed network intrusion detection systems cooperate with each other only with their own information. Unlike this, in our proposed system, a worm detection system on a network in which worms select targets and a worm detection system on a network in which worms propagate themselves cooperate with each other with the direction-aware information in terms of worm's lifecycle. The direction-aware information includes the moving direction of worms and the service port attacked by worms. In this way, we can not only reduce false positive rate of the system but also prevent worms from propagating themselves across the Internet through dispersing the confirmed worm signature.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.517-521
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• 2008

A worm is a malware that propagates quickly from host to host without any human intervention. Need of early worm detection has changed research paradigm from signature based worm detection to the behavioral based detection. To increase effectiveness of proposed solution, in this paper we present mechanism of detection and prevention of worm in distributed fashion. Furthermore, to minimize the worm destruction; upon worm detection we propagate the possible attack aleγt to neighboring nodes in secure and organized manner. Considering worm behavior, our proposed mechanism detects worm cycles and infection chains to detect the sudden change in network performance. And our model neither needs to maintain a huge database of signatures nor needs to have too much computing power, that is why it is very light and simple. So, our proposed scheme is suitable for the ubiquitous environment. Simulation results illustrate better detection and prevention which leads to the reduction of infection rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.277-284
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• 2016

Various network attacks such as DDoS(Distributed Denial of service) and orm are one of the biggest problems in the modern society. These attacks reduce the quality of internet service and caused the cyber crime. To solve the above problem, signature based IDS(Intrusion Detection System) has been developed by network vendors. It has a high detection rate by using database of previous attack signatures or known malicious traffic pattern. However, signature based IDS have the fatal weakness that the new types of attacks can not be detected. The reason is signature depend on previous attack signatures. In this paper, we propose a k-means clustering based malicious traffic detection method to complement the problem of signature IDS. In order to demonstrate efficiency of the proposed method, we apply the bayesian theorem.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.6
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• pp.339-348
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• 2006

Recently, many researches on detecting and responding worms due to the fatal infrastructural damages explosively damaged by automated attack tools, particularly worms. Network service vulnerability exploiting worms have high propagation velocity, exhaust network bandwidth and even disrupt the Internet. Previous worm researches focused on signature-based approaches however these days, approaches based on behavioral features of worms are more highlighted because of their low false positive rate and the attainability of early detection. In this paper, we propose a Distributed Worm Detection Model based on packet marking. The proposed model detects Worm Cycle and Infection Chain among which the behavior features of worms. Moreover, it supports high scalability and feasibility because of its distributed reacting mechanism and low processing overhead. We virtually implement worm propagation environment and evaluate the effectiveness of detecting and responding worm propagation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.431-439
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• 2010

The security systems using signatures cannot protect servers from new types of Internet worms. To protect servers from Internet worms, this paper proposes a system removing malicious processes and executable files without using signatures. The proposed system consists of control servers which offer the same services as those on protected servers, and agents which are installed on the protected servers. When a control server detects multicasting attacks of Internet worm, it sends information about the attacks to an agent. The agent kills malicious processes and removes executable files with this information. Because the proposed system do not use signatures, it can respond to new types of Internet worms effectively. When the proposed system is integrated with legacy security systems, the security of the protected server will be further enhanced.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.93-103
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• 2006

Network solutions for protecting against worm attacks that complement partial end system patch deployment is a pressing problem. In the content-based worm filtering, the challenges focus on the detection accuracy and its performance enhancement problem. We present a worm filter architecture using the bloom filter for deployment at high-speed transit points on the Internet, including firewalls and gateways. Content-based packet filtering at multi-gigabit line rates, in general, is a challenging problem due to the signature explosion problem that curtails performance. We show that for worm malware, in particular, buffer overflow worms which comprise a large segment of recent outbreaks, scalable -- accurate, cut-through, and extensible -- filtering performance is feasible. We demonstrate the efficacy of the design by implementing it on an Intel IXP network processor platform with gigabit interfaces. We benchmark the worm filter network appliance on a suite of current/past worms, showing multi-gigabit line speed filtering prowess with minimal footprint on end-to-end network performance.