• 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.32 no.5
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• pp.869-879
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• 2022

Through this study, we discovered that among three types of compressed data blocks generated through the Deflate algorithm, No-Payload Non-Compressed Block type (NPNCB) which has no literal data can be randomly generated and inserted between normal compressed blocks. In the header of the non-compressed block, there is a data area that exists only for byte alignment, and we called this area as DBA (Disposed Bit Area), where an attacker can hide various malicious codes and data. Finally we found the vulnerability that hides malicious codes or arbitrary data through inserting NPNCBs with infected DBA between normal compressed blocks according to a pre-designed attack scenario. Experiments show that even though contaminated NPNCB blocks were inserted between normal compressed blocks, commercial programs decoded normally contaminated zip file without any warning, and malicious code could be executed by the malicious decoder.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.187-196
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• 2016

Android applications are inherently vulnerable to a repackaging attack such that malicious codes are easily inserted into an application and then resigned by the attacker. These days, it occurs often that such private or individual information is leaked. In principle, all Android applications are composed of user defined methods and APIs. As well as accessing to resources on platform, APIs play a role as a practical functional feature, and user defined methods play a role as a feature by using APIs. In this paper we propose a scheme to analyze sensitive APIs mostly used in malicious applications in terms of how malicious applications operate and which API they use. Based on the characteristics of target APIs, we accumulate the knowledge on such APIs using a machine learning scheme based on Naive Bayes algorithm. Resulting from the learned results, we are able to provide fine-grained numeric score on the degree of vulnerabilities of mobile applications. In doing so, we expect the proposed scheme will help mobile application developers identify the security level of applications in advance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.871-883
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• 2014

New types of attacks that mainly compromise the public, portal and financial websites for the purpose of economic profit or national confusion are being emerged and evolved. In addition, in case of 'drive by download' attack, if a host just visits the compromised websites, then the host is infected by a malware. Website falsification detection system is one of the most powerful solutions to cope with such cyber threats that try to attack the websites. Many domestic CERTs including NCSC (National Cyber Security Center) that carry out security monitoring and response service deploy it into the target organizations. However, the existing techniques for the website falsification detection system have practical problems in that their time complexity is high and the detection accuracy is not high. In this paper, we propose website falsification detection system based on image and code analysis for improving the performance of the security monitoring and response service in CERTs. The proposed system focuses on improvement of the accuracy as well as the rapidity in detecting falsification of the target websites.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.859-866
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• 2019

Cybersecurity attack targeting a specific user is rising in number, even enterprises are trying to strengthen their cybersecurity. Network segmentation environment where public network and private network are separated could block information coming from the outside, however, it is unable to control outside information for business efficiency and productivity. Even if enterprises try to enhance security policies and introduce the network segmentation system and a solution incorporating CDR technology to remove unnecessary data contained in files, it is still exposed to security threats. Therefore, we suggest a system that uses file format conversion to transmit a secure file in the network separation environment. The secure file is converted into an image file from a document, as it reflects attack patterns of inserting malicious code into the document file. Additionally, this paper proposes a system in the environment which functions that a document file can keep information for incident response, considering forensic readiness.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.27-35
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• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.499-510
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• 2023

Recently, an intelligent and advanced cyber attack attacks a computer network of a public institution using a file containing malicious code or leaks information, and the damage is increasing. Even in public institutions with various information protection systems, known attacks can be detected, but unknown dynamic and encryption attacks can be detected when existing signature-based or static analysis-based malware and ransomware file detection methods are used. vulnerable to The detection method proposed in this study extracts the detection result data of the system that can detect malicious code and ransomware among the information protection systems actually used by public institutions, derives various attributes by combining them, and uses a machine learning classification algorithm. Results are derived through experiments on how the derived properties are classified and which properties have a significant effect on the classification result and accuracy improvement. In the experimental results of this paper, although it is different for each algorithm when a specific attribute is included or not, the learning with a specific attribute shows an increase in accuracy, and later detects malicious code and ransomware files and abnormal behavior in the information protection system. It is expected that it can be used for property selection when creating algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.1-8
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• 2017

As the IT environment becomes more sophisticated, various threats and their associated serious risks are increasing. Threats such as DDoS attacks, malware, worms, and APT attacks can be a very serious risk to enterprises and must be efficiently managed in a timely manner. Therefore, the government has designated the important system as the main information communication infrastructure in consideration of the impact on the national security and the economic society according to the 'Information and Communication Infrastructure Protection Act', which, in particular, protects the main information communication infrastructure from cyber infringement. In addition, it conducts management supervision such as analysis and evaluation of vulnerability, establishment of protection measures, implementation of protection measures, and distribution of technology guides. Even now, security consulting is proceeding on the basis of 'Guidance for Evaluation of Technical Vulnerability Analysis of Major IT Infrastructure Facilities'. There are neglected inspection items in the applied items, and the vulnerability of APT attack, malicious code, and risk are present issues that are neglected. In order to eliminate the actual security risk, the security manager has arranged the inspection and ordered the special company. In other words, it is difficult to check against current hacking or vulnerability through current system vulnerability checking method. In this paper, we propose an efficient method for extracting diagnostic data regarding the necessity of upgrading system vulnerability check, a check item that does not reflect recent trends, a technical check case for latest intrusion technique, a related study on security threats and requirements. Based on this, we investigate the security vulnerability management system and vulnerability list of domestic and foreign countries, propose effective security vulnerability management system, and propose further study to improve overseas vulnerability diagnosis items so that they can be related to domestic vulnerability items.