• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.67-74
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• 2022

One type of network security breach is the availability breach, which deprives legitimate users of their right to access services. The Denial of Service (DoS) attack is one way to have this breach, whereas using the Intrusion Detection System (IDS) is the trending way to detect a DoS attack. However, building IDS has two challenges: reducing the false alert and picking up the right dataset to train the IDS model. The survey concluded, in the end, that using a real dataset such as MAWILab or some tools like ID2T that give the researcher the ability to create a custom dataset may enhance the IDS model to handle the network threats, including DoS attacks. In addition to minimizing the rate of the false alert.

• Journal of applied mathematics & informatics
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• 제30권5_6호
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• pp.847-864
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• 2012

In recent years, using computer networks (wired and wireless networks) has been widespread in many applications. As computer networks become increasingly complex, the accompanied potential threats also grow to be more sophisticated and as such security has become one of the major concerns in them. Prevention methods alone are not sufficient to make them secure; therefore, detection should be added as another defense before an attacker can breach the system. Intrusion Detection Systems (IDSs) have become a key component in ensuring systems and networks security. An IDS monitors network activities in order to detect malicious actions performed by intruders and then initiate the appropriate countermeasures. In this paper, we present a survey and taxonomy of intrusion detection systems and then evaluate and compare them.

• 한국전자통신학회논문지
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• 제8권2호
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• pp.339-344
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• 2013

공항 경비보안은 공항의 시설 및 자산을 도난, 범죄 등으로부터 예방하기 위하여 살피고 지키는 활동이다. 이러한 활동을 효율적으로 할 수 있도록 지원하는 시스템을 보안시스템이라 할 수 있다. 보안시스템은 보안센터시스템, CCTV시스템, 출입통제 시스템, 침입감지시스템, 경비통신시스템, 경고방송시스템, 보안네트워크시스템, 외곽침입감지시스템, 검색시스템 및 정보보안시스템이 있으며 이에 대하여 살펴보고자 한다.

• 한국시뮬레이션학회논문지
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• 제11권4호
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• pp.91-105
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• 2002

The attackers on Internet-connected systems we are seeing today are more serious and technically complex than those in the past. So it is beyond the scope of amy one system to deal with the intrusions. That the multiple IDSes (Intrusion Detection System) coordinate by sharing attacker's information for the effective detection of the intrusion is the effective method for improving the intrusion detection performance. The system which uses BBA (BlackBoard Architecture) for the information sharing can be easily expanded by adding new agents and increasing the number of BB (BlackBoard) levels. Moreover the subdivided levels of blackboard enhance the sensitivity of the intrusion detection. For the simulation, security models are constructed based on the DEVS (Discrete EVent system Specification) formalism. The intrusion detection agent uses the ES (Expert System). The intrusion detection system detects the intrusions using the blackboard and the firewall responses these detection information.

• 한국시뮬레이션학회논문지
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• 제12권4호
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• pp.25-40
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• 2003

With the growing usage of the networks, the world-wide Internet has become the main means to exchange data and carry out transactions. It has also become the main means to attack hosts. To solve the security problems which occur in the network such as Internet, we import software products of network security elements like an IDS (Intrusion Detection System) and a firewall. In this paper, we have designed and constructed the general simulation environment of network security model composed of multiple IDSes and a firewall which coordinate by CNP (Contract Net Protocol) for the effective detection of the intrusion. The CNP, the methodology for efficient integration of computer systems on heterogeneous environment such as distributed systems, is essentially a collection of agents, which cooperate to resolve a problem. Command console in the CNP is a manager who controls the execution of agents or a contractee, who performs intrusion detection. In the network security model, each model of simulation environment is hierarchically designed by DEVS(Discrete Event system Specification) formalism. The purpose of this simulation is that the application of rete pattern-matching algorithm speeds up the inference cycle phases of the intrusion detection expert system and we evaluate the characteristics and performance of CNP architecture with rete pattern-matching algorithm.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.197-206
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• 2003

With the growing usage of the networks, the world-wide Internet has become the main means to exchange data and carry out transactions. It has also become the main means to attack hosts. To solve the security problems which occur in the network such as Internet, we import software products of network security elements like an IDS (Intrusion Detection System) and a firewall. In this paper, we have designed and constructed the General Simulation Environment of Network Security model composed of multiple IDSes and a firewall which coordinate by CNP (Contract Net Protocol) for the effective detection of the intrusion. The CNP, the methodology for efficient integration of computer systems on heterogeneous environment such as distributed systems, is essentially a collection of agents, which cooperate to resolve a problem. Command console in the CNP is a manager who controls tie execution of agents or a contractee, who performs intrusion detection. In the Network Security model, each model of simulation environment is hierarchically designed by DEVS (Discrete EVent system Specification) formalism. The purpose of this simulation is to evaluate the characteristics and performance of CNP architecture with rete pattern matching algorithm and the application of rete pattern matching algorithm for the speeding up the inference cycle phases of the intrusion detection expert system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권7호
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• pp.1874-1893
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• 2012

An approach to detect abnormal activities based on reputations created individually by each node is vulnerable to a false accusation since intrusion detection in ad-hoc networks is done in a distributed and cooperative manner. Detection of false accusation is considered important because the efficiency or survivability of the network can be degraded severely if normal nodes were excluded from the network by being considered as abnormal ones in the intrusion detection process. In this paper, we propose an improved reputation-based intrusion detection technique to efficiently detect and manage false accusations in ad-hoc networks. Additionally, we execute simulations of the proposed technique to analyze its performance and feasibility to be implemented in a real environment.

• 한국컴퓨터정보학회논문지
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• 제9권2호
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• pp.81-87
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• 2004

네트워크를 기반으로 하는 시스템들의 발전으로 인하여 매우 다양한 침입이 확산되고 있다. 이러한 침입을 탐지 및 대응하기 위하여 방화벽 또는 IDS와 같은 보안 솔루션들이 생겨나고 있으며 이들을 탑재한 보안시스템의 관리가 더욱 힘들어지고 있다. 더욱이 보안을 요구하는 시스템들의 환경이 다양하여 그에 적합한 보안정책을 수립하여 관리하기가 어려워지고 있다. 따라서 다양한 보안시스템의 통합관리와 각 시스템들의 침입탐지 및 대응에 대한 모델이 필요하게 되었다. 본 논문에서는 광범위한 네트워크 자원을 관리하는 PBNM구조를 개선하고 보안시스템의 침입탐지 및 대응에 적합한 새로운 모델을 제시하였다. 또한 제시된 모델을 통합보안관리시스템에 적용시킴으로써 효과적인 침입탐지 및 대응을 위한 보안 정책 모델을 기반으로 통합보안관리시스템을 설계하였다.

• 정보처리학회논문지C
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• 제10C권1호
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• pp.1-10
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• 2003

본 논문에서는 취약점 검색공격 탐지시스템 DS-NVSA(Detection System of Network Vulnerability Scan Attacks)에서 서버와 에이전트들 사이의 상호연동을 위한 안전한 통신 프레임워크를 제안한다. 기존 시스템과의 상호연동을 위하여 제안 프레임워크는 IETF의 IDWG에서 제안한 IDMEF와 IAP를 확장 적용하였다. 또한 공개키 기반의 환경을 지원하지 못하는 네트워크 시스템을 위해 대칭키 기반의 암호화 통신 프로토콜 SKTLS(Symmetric Key based Transport Layer Security Protocol)를 제시하였다. 제안된 프레임워크는 DS-NVSA 이외에도 기존의 이기종 침입탐지 시스템의 제사용과 탐지 영역의 확대를 제공하며, 또한 기업내 통합 보안환경시스템 ESM(Enterprise Security Management) 시스템에도 적용될 수 있다.

• Journal of Multimedia Information System
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• 제6권4호
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• pp.165-172
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• 2019

Machine-learning techniques have been actively employed to information security in recent years. Traditional rule-based security solutions are vulnerable to advanced attacks due to unpredictable behaviors and unknown vulnerabilities. By employing ML techniques, we are able to develop intrusion detection systems (IDS) based on anomaly detection instead of misuse detection. Moreover, threshold issues in anomaly detection can also be resolved through machine-learning. There are very few datasets for network intrusion detection compared to datasets for malicious code. KDD CUP 99 (KDD) is the most widely used dataset for the evaluation of IDS. Numerous studies on ML-based IDS have been using KDD or the upgraded versions of KDD. In this work, we develop an IDS model using CSE-CIC-IDS 2018, a dataset containing the most up-to-date common network attacks. We employ deep-learning techniques and develop a convolutional neural network (CNN) model for CSE-CIC-IDS 2018. We then evaluate its performance comparing with a recurrent neural network (RNN) model. Our experimental results show that the performance of our CNN model is higher than that of the RNN model when applied to CSE-CIC-IDS 2018 dataset. Furthermore, we suggest a way of improving the performance of our model.