• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.201-211
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• 2022

According to the recent change in the cybersecurity paradigm, research on anomaly detection methods using machine learning and deep learning techniques, which are AI implementation technologies, is increasing. In this study, a comparative study on data preprocessing techniques that can improve the anomaly detection performance of a GRU (Gated Recurrent Unit) neural network-based intrusion detection model using NGIDS-DS (Next Generation IDS Dataset), an open dataset, was conducted. In addition, in order to solve the class imbalance problem according to the ratio of normal data and attack data, the detection performance according to the oversampling ratio was compared and analyzed using the oversampling technique applied with DCGAN (Deep Convolutional Generative Adversarial Networks). As a result of the experiment, the method preprocessed using the Doc2Vec algorithm for system call feature and process execution path feature showed good performance, and in the case of oversampling performance, when DCGAN was used, improved detection performance was shown.

• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.95-102
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• 2003

In order to guarantee the survivability of essential services against attacks based on new methodology, we need a solution to recognize important resources for the services and to adapt the urgent situation properly. In this paper, we present a dynamic resource reallocation scheme which is one of the core technologies for the construction of intrusion tolerant systems. By means of resource reallocation within a host, this scheme enables selected essential services to survive even after the occurrence if a system attack. Experimental result obtained on a test-bed reveals the validity of the proposed scheme for resource reallocation. This scheme may work together with IDS (Intrusion Detection System) to produce more effective responsive mechanisms against attacks.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.177-186
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• 2017

With the latest developments in ICT(Information Communication Technology) technology, research on Intelligent Car, Connected Car that support autonomous driving or services is actively underway. It is true that the number of inputs linked to external connections is likely to be exposed to a malicious intrusion. I studied possible security issues that may occur within the Connected Car. A variety of security issues may arise in the use of CAN, the most typical internal network of vehicles. The data can be encrypted by encrypting the entire data within the CAN network system to resolve the security issues, but can be time-consuming and time-consuming, and can cause the authentication process to be carried out in the event of a certification procedure. To resolve this problem, CAN network system can be used to authenticate nodes in the network to perform a unique authentication of nodes using nodes in the network to authenticate nodes in the nodes and By encoding the ID, identifying the identity of the data, changing the identity of the ID and decryption algorithm, and identifying the cipher and certification techniques of the external invader, the encryption and authentication techniques could be detected by detecting and verifying the external intruder. Add a monitoring node to the CAN network to resolve this. Share a unique ID that can be authenticated using the server that performs the initial certification of nodes within the network and encrypt IDs to secure data. By detecting external invaders, designing encryption and authentication techniques was designed to detect external intrusion and certification techniques, enabling them to detect external intrusions.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.156-162
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• 2003

With the network environment and user's application service increasing information protection and private information protection fields are very important fields. But it is necessary detection methodology to unspecified unknown signal, information increasing and various information media. Therefore in this thesis, we design NIDS that classify others information for detection of the unknown signal as the unauthenticated signal or illegal outer access, etc. proposed NIDS design used Synopsys Ver. 1999 and VHDL. The proposed NIDS system is practical in the system performance and cost for the individually existed NIDS, and utilized a part of system resources.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.75-82
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• 2006

The service use management for keeping up stable and effective environment is hard little by little by according to increase of internet user and being complicated network environment of the Internet little by little. being various of the requirements of the service which is provided and the user demand. And the beginning flag security was limited in IDS, But recently the integrated civil management is coming to be considered seriously according to adventting IDS. Firewall , Security or system. The development of integrated security civil management system to analyze widely through observation and detection at Network or host base, the judgment of attack, and integrated analysis of infiltration information is necessary because of detecting the various type attack.

• Convergence Security Journal
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• v.6 no.4
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• pp.49-57
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• 2006

Firewall to block a network access of unauthorized IP system and IDS (Intrusion Detection System) to detect malicious code pattern to be known consisted the main current of the information security system at the past. But, with rapid growth the diffusion speed and damage of malicious code like the worm, study of the unknown attack traffic is processed actively. One of such method is detection technique using traffic statistics information on the network viewpoint not to be an individual system. But, it is very difficult but to reserve traffic raw data or statistics information. Therefore, we present extraction technique of a network traffic Raw data and a statistics information like the time series. Also, We confirm the validity of a mixing traffic and show the evidence which is suitable to the experiment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.467-473
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• 2011

The Network-packet in this Paper to ensure the integrity of the legal evidence is effect that can have is to offer an Network-forensics system. The Paper proposed Network-forensics system in the company through legal disputes accident Networking and state agency (with investigative authority) for criminal investigations in networking for the effective and correct way to present a report of user-centric services through effective awareness can be improved.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.27-33
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• 2019

One of serious security threats is a botnet-based attack. A botnet in general consists of numerous bots, which are computing devices with networking function, such as personal computers, smartphones, or tiny IoT sensor devices compromised by malicious codes or attackers. Such botnets can launch various serious cyber-attacks like DDoS attacks, propagating mal-wares, and spreading spam e-mails over the network. To establish a botnet, attackers usually inject malicious URLs into web source codes stealthily by using data hiding methods like Javascript obfuscation techniques to avoid being discovered by traditional security systems such as Firewall, IPS(Intrusion Prevention System) or IDS(Intrusion Detection System). Meanwhile, it is non-trivial work in practice for software developers to manually find such malicious URLs which are hidden in numerous web source codes stored in web servers. In this paper, we propose a security defense system to discover such suspicious, malicious URLs hidden in web source codes, and present experiment results that show its discovery performance. In particular, based on our experiment results, our proposed system discovered 100% of URLs hidden by Javascript encoding obfuscation within sample web source files.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.3
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• pp.129-139
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• 2002

As internet expands, the possibility of attack through the network is increasing. So we need the technology which can detect the attack to the system or the network spontaneously. The purpose of this paper proposes the system to detect intrusion automatically using the Adaptive Resonance Theory2(ART2) which is one of artificial neural network The parameters of the system was tunned by ART2 algorithm using a lot of normal packets and various attack packets which were intentionally generated by attack tools. The results were compared and analyzed with conventional methods.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.425-428
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• 2003

Recently, the IDS(Intrusion Detection System) using a video camera is an important part of the home security systems which start gaining popularity. However, the video intruder detection has not been widely used in the home surveillance systems due to its unreliable performance in the environment with abrupt illumination change. In this paper, we propose an effective moving edge extraction algorithm from a sequence image. The proposed algorithm extracts edge segments from current image and eliminates the background edge segments by matching them with reference edge list, which is updated at every frame, to find the moving edge segments. The test results show that it can detect the contour of moving object in the noisy environment with abrupt illumination change.