• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1115-1130
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• 2020

Modern vehicles are equipped with a number of ECUs(Electronic Control Units), and ECUs can control vehicles efficiently by communicating each other through CAN(Controller Area Network). However, CAN bus is known to be vulnerable to cyber attacks because of the lack of message authentication and message encryption, and access control. To find these security issues related to vehicle hacking, CAN Fuzzing methods, that analyze the vulnerabilities of ECUs, have been studied. In the existing CAN Fuzzing methods, fuzzing inputs are randomly generated without considering the structure of CAN messages transmitted by ECUs, which results in the non-negligible fuzzing time. In addition, the existing fuzzing solutions have limitations in how to monitor fuzzing results. To deal with the limitations of CAN Fuzzing, in this paper, we propose a Non-Random CAN Fuzzing, which consider the structure of CAN messages and systematically generates fuzzing input values that can cause malfunctions to ECUs. The proposed Non-Random CAN Fuzzing takes less time than the existing CAN Fuzzing solutions, so it can quickly find CAN messages related to malfunctions of ECUs that could be originated from SW implementation errors or CAN DBC(Database CAN) design errors. We evaluated the performance of Non-Random CAN Fuzzing by conducting an experiment in a real vehicle, and proved that the proposed method can find CAN messages related to malfunctions faster than the existing fuzzing solutions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.535-545
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• 2014

As the software industry has developed, the attacks making use of software vulnerability has become a big issue in society. In particular, because the attacks using the vulnerability of web browsers bypass Windows protection mechanism, web browsers can readily be attacked. To protect web browsers against security threat, research on fuzzing has constantly been conducted. However, most existing web browser fuzzing tools use a simple fuzzing technique which randomly mutates DOM tree. Therefore, this paper analyzed existing web browser fuzzing tools and the patterns of their already-known vulnerability to propose an event and command based fuzzing tool which can detect the latest web browser vulnerability more effectively. Three kinds of existing fuzzing tools were compared with the proposed tool. As a result, it was found that the event and command based fuzzing tool proposed was more effective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1989-2009
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• 2013

How to discover router vulnerabilities effectively and automatically is a critical problem to ensure network and information security. Previous research on router security is mostly about the technology of exploiting known flaws of routers. Fuzzing is a famous automated vulnerability finding technology; however, traditional Fuzzing tools are designed for testing network applications or other software. These tools are not or partly not suitable for testing routers. This paper designs a framework of discovering router protocol vulnerabilities, and proposes a mathematical model Two-stage Fuzzing Test Cases Generator(TFTCG) that improves previous methods to generate test cases. We have developed a tool called RPFuzzer based on TFTCG. RPFuzzer monitors routers by sending normal packets, keeping watch on CPU utilization and checking system logs, which can detect DoS, router reboot and so on. RPFuzzer' debugger based on modified Dynamips, which can record register values when an exception occurs. Finally, we experiment on the SNMP protocol, find 8 vulnerabilities, of which there are five unreleased vulnerabilities. The experiment has proved the effectiveness of RPFuzzer.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.11-17
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• 2021

If a vulnerability in the software connected to the network to obtain the user's privilege, a remote attacker could gain the privilege to use the computer. In addition, in a user environment in which an operating system for a specific series is used a lot, if a problem occurs in the operating system, considerable damage can occur. In particular, If an error is a security vulnerability, it can be a very big problem. Various studies have been conducted to find and respond to vulnerabilities in such a situation. Among various security technologies, the fuzzing technology is one of the most effective technologies to find errors in software. In this paper, I designed and implemented a fuzzing agent that can detect buffer overflow vulnerabilities that can occur in various applications. Through this fuzzing agent, application developers will be able to realize a more secure computing environment in which they can discover and fix vulnerabilities in their own applications.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.573-582
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• 2020

Fuzzing is a method of testing software by randomly generating test cases. Since its introduction, a variety of fuzzing techniques have been studied. Among them, mutation-based fuzzing is an efficient method that finds real-world bugs even though it uses a simple approach such as probabilistic bit-flipping and character substitution. However, the interpreter fuzzing has difficulty in applying general mutation techniques because the interpreter requires grammar and semantic correctness input values. In this paper, we present a novel mutation-based fuzzing on JavaScript interpreters with a dynamic data flow analysis. To this end, we implement JMFuzzer that can generate various types of mutated test cases that operate normally without runtime errors in JavaScript interpreter considering syntax and semantics. As a result, we found numerous unknown vulnerabilities in the latest JavaScript interpreters. We reported all of them to the vendors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.807-819
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• 2019

Greybox fuzzing is known as an effective method to discover unknown security flaws reside in software and has been actively researched today. However, most of greybox fuzzing tools require an executable file. Because of this, a library, which cannot be executed by itself requires an additional executable file for greybox fuzzing. Generating such an executable file is challengeable because it requires both understanding of the library and fuzzing. In this research, we suggest the approach to generate an executable file automatically for a library and implement this approach as a tool based on the LLVM framework. This tool shows that executable files and seed files can be generated automatically by static/dynamic analysis of a unit test in the target project. A generated executable file is compatible with various greybox fuzzers like AFL because it has a common interface for greybox fuzzers. We show the performance of this tool as code coverage and discovered unknown security bugs using generated executable files and seed files from open source projects through this tool.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3885-3906
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• 2020

Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1225-1234
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• 2019

The security of the firmware is more important because embedded devices have become popular. Network devices such as routers can be attacked by attackers through web application vulnerabilities in embedded firmware. Therefore, they must be found and removed quickly. The Firmadyne framework proposes a dynamic analysis method to find vulnerabilities after emulating firmware. However, it only performs vulnerability checks according to the analysis methods defined in the tool, thus limiting the scope of vulnerabilities that can be found. In this paper, fuzzing is performed in emulation-based environment through fuzzing, one of the software security test techniques. We also propose a Fabfuzz tool for efficient emulation based fuzzing. Experiments have shown that in addition to the vulnerabilities identified in existing tools, other types of vulnerabilities have been found.

• Journal of IKEEE
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• v.26 no.4
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• pp.614-621
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• 2022

This paper proposes RIDS (Random Forest-Based Intrusion Detection), which is an intrusion detection system to detect hacking attack based on random forest. RIDS detects three typical attacks i.e. DoS (Denial of service) attack, fuzzing attack, and spoofing attack. It detects hacking attack based on four parameters, i.e. time interval between data frames, its deviation, Hamming distance between payloads, and its diviation. RIDS was designed in memory-centric architecture and node information is stored in memories. It was designed in scalable architecture where DoS attack, fuzzing attack, and spoofing attack can be all detected by adjusting number and depth of trees. Simulation results show that RIDS has 0.9835 accuracy and 0.9545 F1 score and it can detect three attack types effectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.275-285
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• 2019

Web-assemblies are a new binary standard designed to improve the performance of Web browser JavaScript. Web-assemblies are becoming a new web standard that can run at near native speed with efficient execution, concise representation, and code written in multiple languages. However, current Web-assembly vulnerability verification is limited to the Web assembly interpreter language, and vulnerability verification of Web-assembly binary itself is insufficient. Therefore, it is necessary to verify the safety of the web assembly itself. In this paper, we analyze how to operate the web assembly and verify the safety of the current web-assembly. In addition, we examine vulnerability of existing web -assembly and analyze limitations according to existing safety verification method. Finally, we introduce web-assembly API based fuzzing method to overcome limitation of web-assembly safety verification method. This verifies the effectiveness of the proposed Fuzzing by detecting crashes that could not be detected by existing safety verification tools.