• 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 Society of Computer and Information
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• v.10 no.3 s.35
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• pp.249-257
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• 2005

In this paper proposed automated attack reaction tool based on IPv6. Currently, much researches are performing focused on application program and standardization for IPv6. But, It is not enough for future IPv6 security. The proposed method detect attacks on IPv6 and conventional IPv4, therefore it is possible to protect personal information using automated reaction method. Usually, IDS just perform detection, therefore damages may be repeated. However, this paper considered the problems described above, and suggested solution for this problems. The proposed algorithm suggested in this paper is simulated on IPv6 network based on Linux. As a simulation result, it is proved that proposed algorithm can detect attacks efficiently.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.151-159
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• 2010

Currently, by using the Internet, We can do varius things such as Web surfing, email, on-line shopping, stock trading on your home or office. However, as being out of the concept of security from the beginning, it is the big social issues that malicious user intrudes into the system through the network, on purpose to steal personal information or to paralyze system. In addition, network intrusion by ordinary people using network attack tools is bringing about big worries, so that the need for effective and powerful intrusion detection system becomes very important issue in our Internet environment. However, it is very difficult to prevent this attack perfectly. In this paper we proposed the algorithm for the detection of DoS attacks, and developed attack detection tools. Through learning in a normal state on Step 1, we calculate thresholds, the number of packets that are coming to each port, the median and the average utilization of each port on Step 2. And we propose values to determine how to attack detection on Step 3. By programing proposed attack detection algorithm and by testing the results, we can see that the difference between the median of packet mounts for unit interval and the average utilization of each port number is effective in detecting attacks. Also, without the need to look into the network data, we can easily be implemented by only using the number of packets to detect attacks.

• Convergence Security Journal
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• v.4 no.2
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• pp.17-25
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• 2004

As Internet and Internet users are rapidly increasing and getting popularized in the world the existing firewall has limitations to detect attacks which exploit vulnerability of web server. And these attacks are increasing. Most of all, intrusions using web application's programming error are occupying for the most part. In this paper, we introduced real-time web-server agent which analyze web-server based log and detect web-based attacks after the analysis of the web-application's vulnerability. We propose the method using real-time agent which remove Process ID(pid) and block out attacker's If if it detects the intrusion through the decision stage after judging attack types and patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1689-1705
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• 2023

To deal with the potential XSS vulnerabilities in the source code of the power communication network, an XSS vulnerability detection method combining the static analysis method with the dynamic testing method is proposed. The static analysis method aims to analyze the structure and content of the source code. We construct a set of feature expressions to match malignant content and set a "variable conversion" method to analyze the data flow of the code that implements interactive functions. The static analysis method explores the vulnerabilities existing in the source code structure and code content. Dynamic testing aims to simulate network attacks to reflect whether there are vulnerabilities in web pages. We construct many attack vectors and implemented the test in the Selenium tool. Due to the combination of the two analysis methods, XSS vulnerability discovery research could be conducted from two aspects: "white-box testing" and "black-box testing". Tests show that this method can effectively detect XSS vulnerabilities in the source code of the power communication network.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.125-132
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• 2011

A hierarchical Web Security System, which is a solution to various web-based attacks, seemingly is not able to keep up with the improvement of detoured or compound attacks. In this paper, we suggest an efficient detecting scheme for web-based attacks like Malware, XSS, Creating Webshell, URL Spoofing, and Exposing Private Information through monitoring HTTP outbound traffics in real time. Our proposed scheme detects web-based attacks by comparing the outbound traffics with the signatures of HTML tag or Javascript created by the attacks. Through the verification analysis under the real-attacked environment, we show that our scheme installed in a hierarchical web security system has superior detection capability for detoured web-based attacks.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.49-50
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• 2024

본 논문에서는 웹쉘 악성코드를 정확하게 분류하고, 빠른시간안에 자동으로 웹쉘 분류 및 분석을 통하여 웹쉘을 탐지하기 위하여 인공지능 머신러닝 기반의 Supervised AI ML 및 Classification 알고리즘을 적용하여 빠른 시간안에 분류, 정확한 분석을 통하여 자동화된 탐지시스템인 MWSDS를 제안하고 웹쉘 실험 데이터를 통하여 실증하였다. 본제안의 경우 웹쉘악성코드 공격에 대한 대응뿐만아니라 관리적인 정보보호 체계수립을 통하여 보다 효과적이며, 지속적으로 대응할 수 있을 것으로 전망된다.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.207-212
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• 2021

A buffer overflow attack is carried out to subvert privileged program functions to gain control of the program and thus control the host. Buffer overflow attacks should be prevented by risk managers by eradicating and detecting them before the software is utilized. While calculating the size, correct variables should be chosen by risk managers in situations where fixed-length buffers are being used to avoid placing excess data that leads to the creation of an overflow. Metamorphism can also be used as it is capable of protecting data by attaining a reasonable resistance level [1]. In addition, risk management teams should ensure they access the latest updates for their application server products that support the internet infrastructure and the recent bug reports [2]. Scanners that can detect buffer overflows' flaws in their custom web applications and server products should be used by risk management teams to scan their websites. This paper presents an experiment of buffer overflow vulnerability and attack. The aims to study of a buffer overflow mechanism, types, and countermeasures. In addition, to comprehend the current detection plus prevention approaches that can be executed to prevent future attacks or mitigate the impacts of similar attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

• Journal of Platform Technology
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• v.6 no.4
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• pp.69-77
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• 2018

In the case of personal information files containing personal information, there is insufficient awareness of personal information protection in end-point areas such as personal computers, smart terminals, and personal storage devices. In this study, we use Diffie-Hellman method to securely retrieve personal information files generated by web crawler. We designed SEED and ARIA using hybrid slicing to protect against attack on personal information file. The encryption performance of the personal information file collected by the Web crawling method is compared with the encryption decryption rate according to the key generation and the encryption decryption sharing according to the user key level. The simulation was performed on the personal information file delivered to the external agency transmission process. As a result, we compared the performance of existing methods and found that the detection rate is improved by 4.64 times and the information protection rate is improved by 18.3%.