• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.148-153
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• 2003

A DoS(Denial of Service) attack appears in the form of the intrusion attempt and Syn Flooding attack is a typical example. The Syn Flooding attack takes advantage of the weak point of 3-way handshake between the end-points of TCP which is the connection-oriented transmission service and has the reliability This paper proposes a NIIP(Network based Intelligent Intrusion Prevention) model. This model captures and analyzes the packet informations for the detection of Syn Flooding attack. Using the result of analysis of decision module, the decision module, which utilizes FCM(Fuzzy Cognitive Maps), measures the degree of danger of the DoS and trains the response module to deal with attacks. This model is a network based intelligent intrusion prevention model that reduces or prevents the danger of Syn Flooding attack.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.203-205
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• 2022

As digital transformation and remote work environment advanced by Covid-19 become more common, the scale of leakage damage to industrial secrets and personal information caused by information leakage attacks is increasing. Recently, advanced and persistent information leakage attacks have become a serious security threat because they do not quickly leak large amounts of information, but continuously leak small amounts of information over a long period of time. In this study, we propose a framework for detecting advanced and persistent information leakage attacks based on traffic characteristics. The proposed method can effectively detect advanced and persistent information leakage attacks using traffic patterns, packet sizes, and metadata, even if the payload is encrypted.

• Convergence Security Journal
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• v.21 no.1
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• pp.93-100
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• 2021

Damage caused by intelligent cyber attacks not only disrupts system operations and leaks information, but also entails massive economic damage. Recently, cyber attacks have a distinct goal and use advanced attack tools and techniques to accurately infiltrate the target. In order to minimize the damage caused by such an intelligent cyber attack, it is necessary to block the cyber attack at the beginning or during the attack to prevent it from invading the target's core system. Recently, technologies for predicting cyber attack paths and analyzing risk level of cyber attack using big data or artificial intelligence technologies are being studied. In this paper, a cyber attack path analysis method using attack tree and RFI is proposed as a basic algorithm for the development of an automated cyber attack path prediction system. The attack path is visualized using the attack tree, and the priority of the path that can move to the next step is determined using the RFI technique in each attack step. Based on the proposed mechanism, it can contribute to the development of an automated cyber attack path prediction system using big data and deep learning technology.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• The Journal of Korean Association of Computer Education
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• v.14 no.6
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• pp.65-73
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• 2011

As we can see from the recent cyber attack, APT(Advanced Persistent Threat) is trend of hacking attack in the World. Thus, HTTP Get Flooding attack is considered to be one of the most successful attacks in cyber attack method. In this paper, designs and implements new technique for the cyber attack using HTTP get flooding technology. also, I need a defence about DDoS attack through APT Tools.

• Review of KIISC
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• v.24 no.1
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• pp.13-22
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• 2014

정보기술이 발전함에 따라 편리성이 향상되고 있지만, 사이버 공간에서의 보안 위협은 증가하고 있다. 최근에는 국가 기반시설과 같은 주요 인프라와 기관 및 기업을 목표로 하여 사이버 공격을 시도하고 있고, 해당 공격 방법도 지능적으로 발전하고 있다. 따라서 사이버 공간의 보안 위협에 대응하기 위해 국가적 차원에서 전략을 마련하고 있다. 특히 사이버 보안과 관련하여 미국은 사이버 공격에 대응하기 위해 각 기관의 연계성 및 협력을 위한 전략을 타 국가보다 앞서 준비하고 실행을 하고 있다. 따라서 본 고에서는, 국내 사이버 공격에 대한 보안 전략 수립을 위해 최근 사이버 공격이 이루어지는 유형과 사례를 분석하고, 이에 대처하는 미국 각 기관의 전략과 역할에 대해 분석한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.449-455
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• 2021

This paper proposes an encryption web transaction attack detection system based on the existing web application monitoring system. Although there was difficulty in detecting attacks on the encrypted web traffic because the existing web traffic security systems detect and defend attacks based on encrypted packets in the network area of the encryption section between the client and server, by utilizing the technology of the web application monitoring system, it is possible to detect various intelligent cyber-attacks based on information that is already decrypted in the memory of the web application server. In addition, since user identification is possible through the application session ID, statistical detection of attacks such as IP tampering attacks, mass web transaction call users, and DDoS attacks are also possible. Thus, it can be considered that it is possible to respond to various intelligent cyber attacks hidden in the encrypted traffic by collecting and detecting information in the non-encrypted section of the encrypted web traffic.

• Annual Conference of KIPS
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• 2024.05a
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• pp.401-402
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• 2024

인공지능 기술은 사회 전반에 걸쳐 다양한 분야에서 활용되고 있다. 그러나 인공지능 기술의 발전과 함께 인공지능 기술을 악용한 적대적 공격의 위험성도 높아지고 있다. 적대적 공격은 작은 왜곡으로도 의료, 교통, 커넥티드카 등 인간의 생명과 안전에 직결되는 인공지능 학습 모델의 성능에 악영향을 미치기 때문에 효과적인 탐지 기술이 요구되고 있다. 본 논문에서는 설명 가능한 AI 를 활용한 적대적 공격을 탐지하는 최신 연구 동향을 분석한다.

• Review of KIISC
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• v.32 no.3
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• pp.33-39
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• 2022

전 세계적으로 다양한 피해를 입히고 있는 랜섬웨어는 사이버 공간에서 가장 위협적인 공격으로 인식되고 있다. 최근 랜섬웨어는 단순히 데이터를 암호화하는 것 뿐만 아니라 데이터 유출, DDoS 공격을 수행하는 등 고도화 되고 있다. 최근 랜섬웨어 공격 조직들은 서비스형 랜섬웨어를 제작/판매하고 있으며, 그에 따라 전문 지식이 없는 악의적인 사용자들도 랜섬웨어 공격이 가능한 실정이다. 본 논문은 지능화 되고 있는 랜섬웨어의 최신 동향을 분석하고 세대별 발전 방향을 살펴본다.