• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.34 no.2
• /
• pp.245-261
• /
• 2024

The COVID-19 pandemic has led to the widespread adoption of contactless transactions, resulting in a noticeable increase in the trend towards fully unmanned stores. In such stores, all operational processes are automated, primarily using artificial intelligence (AI) technology. However, this AI technology has several security vulnerabilities, which can be critical in the environment of fully unmanned stores. This paper analyzes the security vulnerabilities that AI-based fully unmanned stores may face, focusing particularly on the object detection model YOLO, demonstrating that Hiding Attacks and Altering Attacks using adversarial patches are possible. It is confirmed that objects with adversarial patches attached may not be recognized by the detection model or may be incorrectly recognized as other objects. Furthermore, the paper analyzes how Data Augmentation techniques can mitigate security threats by providing a defensive effect against adversarial patch attacks. Based on these results, we emphasize the need for proactive research into defensive measures to address the inherent security threats in AI technology used in fully unmanned stores.

• Convergence Security Journal
• /
• v.24 no.2
• /
• pp.201-207
• /
• 2024

Voice is a critical element of human communication, and the development of speech recognition models is one of the significant achievements in artificial intelligence, which has recently been applied in various aspects of human life. The application of speech recognition models in the military field is also inevitable. However, before artificial intelligence models can be applied in the military, it is necessary to research their vulnerabilities. In this study, we evaluates the military applicability of the multilingual speech recognition model "Whisper" by examining its vulnerabilities to battlefield noise, white noise, and adversarial attacks. In experiments involving battlefield noise, Whisper showed significant performance degradation with an average Character Error Rate (CER) of 72.4%, indicating difficulties in military applications. In experiments with white noise, Whisper was robust to low-intensity noise but showed performance degradation under high-intensity noise. Adversarial attack experiments revealed vulnerabilities at specific epsilon values. Therefore, the Whisper model requires improvements through fine-tuning, adversarial training, and other methods.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.3
• /
• pp.119-127
• /
• 2013

The merits of Smartphone are portability, convenience and especially a lot of information can be stored in the device. Especially in Smartphone, users can install programs that cannot install to normal cell phone and users can use many different services through these Smartphone programs. Also Smartphone can connect to Internet through network, so it can access information anytime, anywhere easily. Security of personal information and variety of information which stored in Smartphone are in risk. In Chapter 2 of thesis, it will discuss the definition and features of the Smartphone and market trends. In Chapter 3 of thesis, it will discuss security vulnerabilities of Smartphone and it will analyze and research security vulnerabilities of Smartphone in Chapter 4. In conclusion, it will check users' identification twice in useful application especially application that relate to finance and mobile payment. By checking users' identification several times, it will help to defend from security threats. Users can use Smartphone safely and convenience by know how to prevent from mobile hacking for personal and private information. the quality of APIs matching by the clustering and hierarchical relationships mechanism.

• Journal of KIISE
• /
• v.44 no.2
• /
• pp.171-178
• /
• 2017

In this study, we propose an automated unit test generation technique for detecting vulnerabilities of Android kernel modules. The technique automatically generates unit test drivers/stubs and unit test inputs for each function of Android kernel modules by utilizing dynamic symbolic execution. To reduce false alarms caused by function pointers and missing pre-conditions of automated unit test generation technique, we develop false alarm reduction techniques that match function pointers by utilizing static analysis and generate pre-conditions by utilizing def-use analysis. We showed that the proposed technique could detect all existing vulnerabilities in the three modules of Android kernel 3.4. Also, the false alarm reduction techniques removed 44.9% of false alarms on average.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.3
• /
• pp.635-642
• /
• 2018

In the Era of the Fourth Industrial Revolution, we live in huge amounts of software. However, as software increases, software vulnerabilities are also increasing. Therefore, it is important to detect and remove software vulnerabilities. Currently, many researches have been studied to predict and detect software security problems, but it takes a long time to detect and does not have high prediction accuracy. Therefore, in this paper, we describe a method for efficiently predicting software vulnerabilities using machine learning algorithms. In addition, various machine learning algorithms are compared through experiments. Experimental results show that the k-nearest neighbors prediction model has the highest prediction rate.

• Convergence Security Journal
• /
• v.4 no.2
• /
• pp.43-51
• /
• 2004

Operating systems and application programs have security vulnerabilities derived from the software development process. Recently, incident cases related with the abuses of these vulnerabilities are increasing and the damages caused by them are becoming very important security issues all over the nations. Patch management is one of the most important processes to fix vulnerabilities of softwares and to ensure a security of systems. Since an institute or a company has distributed hierarchical and heterogeneous systems, it is not easy to update patches promptly. In this paper, we propose patch management framework to safely distribute and install the patches on Windows, Linux, and Solaris client systems. Besides, we considered extensibility and hierarchical structure for our patch management framework to support large scaled network environment.

• Journal of the Korea Convergence Society
• /
• v.2 no.4
• /
• pp.1-7
• /
• 2011

As the developing of the information technology, M2M market that is using communication between devices is growing rapidly and many companies are involved in M2M business. In this paper, the concept of telematics and vulnerabilities of vehicle network security are discussed. The convergence of vehicle and information technology, the development of mobile communication technology have improved quality of service that provided to user but as a result security threats has diverse. We proposed new business model that be occurred to the participation of mobile carriers in telematics business and we analyzed mobile radio communication network security vulnerabilities. We proposed smart phone and Vehicle authentication scheme with M2M device as a way to solve vulnerabilities.

• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.209-210
• /
• 2008

In the case of unauthorized individuals, systems and entities or process threatening the instrumentation and control systems of nuclear facilities using the intrinsic vulnerabilities of digital based technologies, those systems may lose their own required functions. The loss of required functions of the critical systems of nuclear facilities may seriously affect the safety of nuclear facilities. Consequently, digital instrumentation and control systems, which perform functions important to safety, should be designed and operated to respond to cyber threats capitalizing on the vulnerabilities of digital based technologies. To make it possible, the developers and licensees of nuclear facilities should perform appropriate cyber security program throughout the whole life cycle of digital instrumentation and control systems. Under the goal of securing the safety of nuclear facilities, this paper presents the KINS' regulatory position on cyber security program to remove the cyber threats that exploit the vulnerabilities of digital instrumentation and control systems and to mitigate the effect of such threats. Presented regulatory position includes establishing the cyber security policy and plan, analyzing and classifying the cyber threats and cyber security assessment of digital instrumentation and control systems.

• The KIPS Transactions:PartC
• /
• v.14C no.4
• /
• pp.313-320
• /
• 2007

In this paper, we propose a method to analyze security vulnerabilities of MS word-processor by checking the validation of its input files. That is, this study is to detect some vulnerabilities in the input file of the word processor by analyzing the header information of its input file. This validation test can not be conducted by the existing software fault injection tools including Holodeck and CANVAS. The proposed method can be also applied to identify the input file vulnerabilities of Hangul and Microsoft Excel which handle a data file with a header as an input. Moreover, our method can provide a means for assessing the fault tolerance and trustworthiness of the target software.

• Journal of KIISE
• /
• v.43 no.11
• /
• pp.1179-1187
• /
• 2016

Android- and Linux-based embedded systems require device drivers, which are structured and built in kernel functions. However, device driver software (firmware) provided by various 3rd parties is not usually checked in terms of their security requirements but is simply included in the final products, that is, Android-based smart phones. In addition, static analysis, which is generally used to detect vulnerabilities, may result in extra cost to detect critical security issues such as privilege escalation due to its large proportion of false positive results. In this paper, we propose and evaluate an effective technique to detect vulnerabilities in Android device drivers using both static and dynamic analyses.