• IE interfaces
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• v.21 no.1
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• pp.33-42
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• 2008

To analyze tens of thousands of alarms triggered by the intrusion detections systems (IDS) a day has been very time-consuming, requiring human administrators to stay alert for all time. But most of the alarms triggered by the IDS prove to be the false positives. If alarms could be correctly classified into the false positive and the false negative, then we could alleviate most of the burden of human administrators and manage the IDS far more efficiently. Therefore, we present a new approach based on attribute-oriented induction (AOI) to classify alarms into the false positive and the false negative. The experimental results show the proposed approach performs very well.

• Journal of the Korea Society of Computer and Information
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• v.9 no.1
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• pp.37-43
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• 2004

Expasion of computer network and rapid growth of Internet have made computer security very important. As one of the ways to deal with security risk, much research has been made on Intrusion Detection System(IDS). The paper, also, addresses the issue of intrusion detection, but especially with Neuro-Fuzzy model. By applying the fuzzy logic which is known to deal with uncertainty to Anomaly Intrusion, it not only overcomes the difficulty of Misuse Intrusion, but also ultimately aims to detect the intrusions yet to be known.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.1-10
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• 2018

Network threats such as Internet worms and computer viruses have been significantly increasing. In particular, APTs(Advanced Persistent Threats) and ransomwares become clever and complex. IDSes(Intrusion Detection Systems) have performed a key role as information security solutions during last few decades. To use an IDS effectively, IDS rules must be written properly. An IDS rule includes a key signature and is incorporated into an IDS. If so, the network threat containing the signature can be detected by the IDS while it is passing through the IDS. However, it is challenging to find a key signature for a specific network threat. We first need to analyze a network threat rigorously, and write a proper IDS rule based on the analysis result. If we use a signature that is common to benign and/or normal network traffic, we will observe a lot of false alarms. In this paper, we propose a scheme that analyzes a network threat and extracts key signatures corresponding to the threat. Specifically, our proposed scheme quantifies the degree of correspondence between a network threat and a signature using the LDA(Latent Dirichlet Allocation) algorithm. Obviously, a signature that has significant correspondence to the network threat can be utilized as an IDS rule for detection of the threat.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.131-140
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• 2023

Network security situational awareness systems helps in better managing the security concerns of a network, by monitoring for any anomalies in the network connections and recommending remedial actions upon detecting an attack. An Intrusion Detection System helps in identifying the security concerns of a network, by monitoring for any anomalies in the network connections. We have proposed a CRF based IDS system using genetic search feature selection algorithm for network security situational awareness to detect any anomalies in the network. The conditional random fields being discriminative models are capable of directly modeling the conditional probabilities rather than joint probabilities there by achieving better classification accuracy. The genetic search feature selection algorithm is capable of identifying the optimal subset among the features based on the best population of features associated with the target class. The proposed system, when trained and tested on the bench mark NSL-KDD dataset exhibited higher accuracy in identifying an attack and also classifying the attack category.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8C
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• pp.748-757
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• 2002

Cyber-terror trials are increased in nowadays and these attacks are commonly using security vulnerability and information gathering method by variable services grew by the continuous development of Internet Technology. IDS's application environment is affected by this increasing Cyber Terror. General Network based IDS detects intrusion by signature based Intrusion Detection module about inflowing packet through network devices. Up to now security in network is commonly secure host, an regional issue adopted in special security system but these system is vulnerable intrusion about the attack in globally connected Internet systems. Security mechanism should be produced to expand the security in whole networks. In this paper, we analyzer the DARPA's program and study Infusion Detection related Technology. We design policy security framework for policy enforcing in whole network and look at the modules's function. Enforcement of security policy is acted by Intrusion Detection system on gateway system which is located in network packet's inflow point. Additional security policy is operated on-line. We can design and execute central security policy in managed domain in this method.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.223-226
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• 2017

인터넷의 발달로 인하여 네트워크 공격이 점차 발전되며 여러 가지 공격 기법들이 생겨나고 이러한 기법들은 혼합하여 사용하는 등 변칙적인 해킹기법들이 생겨나고 있다. 이로 인하여 침입 탐지 시스템(Intrusion Detection System, IDS)은 기존의 알려진 공격에 대해서만 탐지하고 변칙된 새로운 패턴의 공격을 탐지하지 못하는 경우가 생겨나고 있다. 이 문제에 적합한 해결책을 찾고자 여러 가지 알고리즘들이 연구되었고, 아직도 활발히 진행되고 있다. 본 글에서는 이러한 연구된 알고리즘들을 비교해 보았고 효율적인 방법을 제안한다.

• Convergence Security Journal
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• v.1 no.1
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• pp.57-68
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• 2001

Computer security is considered important because of the side effect generated from the expansion of computer network and rapid increase of the use of computer. Intrusion Detection System(IDS) has been an active research area to reduce the risk from intruders. In this paper, the Hybrid Intrusion Detection System(HIDS) based biometric immuntiy collects and filters audit data by misuse detection is innate immune, and anomaly detection is acquirement immune in multi-hosts. Since, collect and detect audit data from one the system in molt-hosts, it is design and implement of the intrusion detection system which has the immuntiy the detection intrusion in one host possibly can detect in multi-hosts and in the method of misuses detection subsequently.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.87-95
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• 2006

We need to check into when a security system is newly developed, we against cyber attack which is expected in real network. However it is impossible to check it under the environment of a large-scale distributive network. So it is need to simulate it under the virtual network environment. SSFNet is a event-driven simulator which can be represent a large-scale network. Unfortunately, it doesn't have the module to simulate security functions. In this paper, we added the IDS module to SSFNet. We implement the IDS module by modeling a key functions of Snort. In addition, we developed some useful functions using Java language which can manipulate easily a packet for network simulation. Finally, we performed the simulation to verify the function if our developed IDS and Packets Manipulation. The simulation shows that our expanded SSFNet can be used to further large-scale security system simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4706-4726
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• 2019

The paper is devoted to the detailed description of the distributed system for gathering data from Windows-based workstations and servers. The research presented in the beginning demonstrates that neither a solution for gathering data on attacks against Windows based PCs is available at present nor other security tools and supplementary programs can be combined in order to achieve the required attack data gathering from Windows computers. The design of the newly proposed system named Colander is presented, too. It is based on a client-server architecture while taking much inspiration from previous attempts for designing systems with similar purpose, as well as from IDS systems like Snort. Colander emphasizes its ease of use and minimum demand for system resources. Although the resource usage is usually low, it still requires further optimization, as is noted in the performance testing. Colander's ability to detect threats has been tested by real malware, and it has undergone a pilot field application. Future prospects and development are also proposed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.