• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.99-110
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• 2009

Currently, there are many applications being developed based on sensor network technology. A tracking method for moving objects in sensor network is one of the main issue of this field. There is a little research on this issue, but most of the existing work has two problems. The first problem is a communication overhead for visiting sensor nodes many times to track a moving object. The second problem is an disability for dealing with many moving objects at a time. To resolve the problems, we, in this paper, propose a signature-based tracking method using efficient data aggregation for moving objects, called SigMO-TRK. For this, we first design a local routing hierarchy tree to aggregate moving objects' trajectories efficiently by using a space filtering technique. Secondly, we do the tracking of all trajectories of moving objects by using signature in a efficient way, our approach generates signatures to method. In addition, by extending the SigMO-TRK, we can retrieve the similar trajectories of moving objects for given a query. Finally, by using the TOSSIM simulator, we show that our signature-based tracking method outperforms the existing tracking method in terms of energy efficiency.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.193-195
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• 2016

오늘날의 백신은 일반적으로 시그니처 기반 탐지법을 이용한다. 시그니처 탐지기법은 악성코드의 특정한 패턴을 비교하여 효율적이고 오탐율이 낮은 기법이다. 하지만 알려지지 않은 악성코드와 난독화 기법이 적용된 악성코드를 분석하는데 한계가 있다. 악성코드를 실행하여 나타나는 행위를 분석하는 동적분석 방법은 특정한 조건에서만 악성행위를 나타내는 은닉형 악성코드(Evasive Malware)를 탐지하는 데 한계를 지닌다. 본 논문에서는 은닉형 악성코드에 적용된 기법에 관하여 소개하고 나아가 이를 탐지하기 위한 방법에 관한 기술동향을 소개한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.423-424
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• 2024

본 논문은 TCP/IP 네트워크 및 암호 프로토콜을 결합하여 CCTV 카메라 영상 데이터를 안전하게 전송하는 시스템에 관한 것이다. 특히, TCP Handshake에서 암호 키를 교환하고, 디바이스의 시그니처 정보를 활용하여 키를 생성하는 키 교환 암호 프로토콜을 도입한다. 이를 통해 CCTV 카메라의 영상 데이터를 암호화하여 전송하고, 수신 시 복호화하여 저장한다. 또한, 적어도 하나 이상의 CCTV 카메라에 대한 보안 인증과 네트워크 연결 상태를 제어하며, 중간자 공격을 방지하기 위한 안전한 키 교환을 수행한다. 이로써 안전성이 강화된 CCTV 카메라 시스템을 제공할 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.45-54
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• 2014

In this paper, an improved two-step P2P traffic classification scheme is proposed to overcome the limitations of the existing methods. The first step is a signature-based classifier at the packet-level. The second step consists of pattern heuristic rules and a statistics-based classifier at the flow-level. With pattern heuristic rules, the accuracy can be improved and the amount of traffic to be classified by statistics-based classifier can be reduced. Based on the analysis of different decision tree algorithms, the statistics-based classifier is implemented with REPTree. In addition, the ensemble algorithm is used to improve the performance of statistics-based classifier Through the verification with the real datasets, it is shown that our hybrid scheme provides higher accuracy and lower overhead compared to other existing schemes.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.569-571
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• 2020

시맨틱 파싱은 주어진 자연어 발화를 domain specific language(DSL)를 따르는 프로그램으로 변환하는 방법이다. 시맨틱 파서가 다형성을 가지는 DSL을 사용할 경우, 적은 수의 토큰으로 다양한 프로그램을 출력할 수 있지만, 탐색 공간이 넓어진다는 문제가 있다. 본 연구에서는 해당 문제를 완화하기 위해 다형성을 가지는 DSL의 타입 시그니처를 제한하는 방법을 제안한다. 해당 방법은 sequence-to-sequence 기반의 시맨틱 파싱 성능을 향상시키는데 효율적임을 보였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.667-677
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• 2012

Vulnerable web applications have been the primary method used by the attackers to spread their malware to a large number of victims. Such attacks commonly make use of malicious links to remotely execute a rather advanced malicious code. The attackers often deploy malwares that utilizes unknown vulnerabilities so-called "zero-day vulnerabilities." The existing computer vaccines are mostly signature-based and thus are effective only against known attack patterns, but not capable of detecting zero-days attacks. To mitigate such limitations of the current solutions, there have been a numerous works that takes a behavior-based approach to improve detection against unknown malwares. However, behavior-based solutions arbitrarily introduced a several limitations that made them unsuitable for real-life situations. This paper proposes an advanced web browser based malicious behavior detection system that solves the problems and limitations of the previous approaches.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.963-974
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• 2018

With the growing interest in cryptocurrency such as bitcoin, the blockchain technology has attracted much attention in various applications as a distributed security platform with excellent security. However, Cryptojacking, an attack that hijack other computer resources such as CPUs, has occured due to vulnerability to the Cryptomining process. In particular, browser-based Cryptojacking is considered serious because attacks can occur only by visiting a Web site without installing it on a visitor's PC. The current Cryptojacking detection system is mostly signature-based. Signature-based detection methods have problems in that they can not detect a new Cryptomining code or a modification of existing Cryptomining code. In this paper, we propose a Cryptojacking detection solution using a dynamic analysis-based that uses a headless browser to detect unknown Cryptojacking attacks. The proposed dynamic analysis-based Cryptojacking detection system can detect new Cryptojacking site that cannot be detected in existing signature-based Cryptojacking detection system and can detect it even if it is called or obfuscated by bypassing Cryptomining code.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.13-22
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• 2021

Recently network based attack technologies are rapidly advanced and intelligent, the limitations of existing signature-based intrusion detection systems are becoming clear. The reason is that signature-based detection methods lack generalization capabilities for new attacks such as APT attacks. To solve these problems, research on machine learning-based intrusion detection systems is being actively conducted. However, in the actual network environment, attack samples are collected very little compared to normal samples, resulting in class imbalance problems. When a supervised learning-based anomaly detection model is trained with such data, the result is biased to the normal sample. In this paper, we propose to overcome this imbalance problem through One-Class Anomaly Detection using an auto encoder. The experiment was conducted through the NSL-KDD data set and compares the performance with the supervised learning models for the performance evaluation of the proposed method.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.305-313
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• 2018

With the explosive growth of smart phones and efficiency, the Android of an open mobile operating system is gradually increasing in the use and the availability. Android systems has proven its availability and stability in the mobile devices, the home appliances's operating systems, the IoT products, and the mechatronics. However, as the usability increases, the malicious code based on Android also increases exponentially. Unlike ordinary PCs, if malicious codes are infiltrated into mobile products, mobile devices can not be used as a lock and can be leaked a large number of personal contacts, and can be lead to unnecessary billing, and can be cause a huge loss of financial services. Therefore, we proposed a method to detect and delete malicious files in real time in order to solve this problem. In this paper, we also designed a method to detect and delete malicious codes in a more effective manner through the process of installing Android-based applications and signature-based malicious code detection method. The method we proposed and designed can effectively detect malicious code in a limited resource environment, such as mobile environments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.885-896
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• 2014

The files in computer storages can be deleted due to unexpected failures or accidents. Some malicious users often delete data by himself for anti-forensics. If deleted files are associated with crimes or important documents in business, they should be recovered and the recovery tool is necessary. The recovery methods and tools for some filesystems such as NTFS, FAT, and EXT have been developed actively. However, there has not been any researches for recovering deleted files in XFS filesystem applied to NAS or CCTV. In addition, since the current related tools are based on the traditional signature detection methods, they have low recovery rates. Therefore, this paper suggests the recovery methods for deleted files based on metadata and signature detection in XFS filesystem, and verifies the results by conducting experiment in real environment.