• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.45-52
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• 2020

Traditional methods of detecting security vulnerabilities in source-code require a lot of time and effort. If there is good data, the issue could be solved by using the data with machine learning. Thus, this paper proposes a source-code vulnerability detection method based on machine learning. Our method employs the code2vec model that has been used to propose the names of methods, and uses as a data set, Juliet Test Suite that is a collection of common security vulnerabilities. The evaluation shows that our method has high precision of 97.3% and recall rates of 98.6%. And the result of detecting vulnerabilities in open source project shows hopeful potential. In addition, it is expected that further progress can be made through studies covering with vulnerabilities and languages not addressed here.

• Convergence Security Journal
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• v.16 no.5
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• pp.49-55
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• 2016

Recently mobile service industry has grown very rapidly. In this paper, We investigated the changes in mobile service network as well as security vulnerabilities of network in future 5G mobile service network, too. Recently, there are rapid developement of information and communication and rapid growth of mobile e-business users. Therefore We try to solve security problem on the internet environment which charges from wire internet to wireless internet or wire/wireless internet. Since the wireless mobile environment is limited, researches such as small size, end-to-end and privacy security are performed by many people. In addition, there is a need of internetworking between mobile and IoT services. Wireless Application Protocol has weakness of leaking out information from Gateway which connected wire and wireless communication. As such, We investigate the structure of mobile service network in order to gain security vulnerabilities and insights in this paper.

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

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.906-918
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• 2018

The advent of the Internet of Things (IoT) technology, which brings many benefits to our lives, has resulted in numerous IoT devices in many parts of our living environment. However, to adapt to the rapid changes in the IoT market, numerous IoT devices were widely deployed without implementing security by design at the time of development. As a result, malicious attackers have targeted IoT devices, and IoT devices lacking security features have been compromised by attackers, resulting in many security incidents. In particular, an attacker can take control of an IoT device, such as Mirai Botnet, that has insufficient security features. The IoT device can be used to paralyze numerous websites by performing a DDoS attack against a DNS service provider. Therefore, this study proposes a scheme to minimize security vulnerabilities and threats in IoT devices to improve the security of the IoT service environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.256-259
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• 2013

Data and network security for e-Healthcare Systems are a primary concern due to the easiest deployment area accessibility of the sensor devices. Furthermore, they are often interacting closely in cooperation with the physical environment and the surrounding people, where such exposure increases security vulnerabilities in cases of improperly managed security of the information sharing among different healthcare organizations. Hence, healthcare-specific security standards such as authentication, data integrity, system security and internet security are used to ensure security and privacy of patients' information. This paper discusses security threats on e-Healthcare Systems where an attacker can access both data and network using masquerade attack. Moreover, an efficient and cost effective approach for countermeasures is discussed for the delivery of secure services.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.2
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• pp.263-277
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• 2021

Taint analysis techniques are popularly used to detect web vulnerabilities originating from unverified user input data, such as Cross-Site Scripting (XSS) and SQL Injection, in web applications written in JavaScript. To detect such vulnerabilities, it would be necessary to trace variables affected by user-submitted inputs. However, because of the dynamic nature of JavaScript, it has been a challenging issue to identify those variables without running the web application code. Therefore, most existing taint analysis tools have been developed based on dynamic taint analysis, which requires the overhead of running the target application. In this paper, we propose a novel static taint analysis technique using symbol information obtained from the TypeScript (a superset of JavaScript) compiler to accurately track data flow and detect security vulnerabilities in TypeScript code. Our proposed technique allows developers to annotate variables that can contain unverified user input data, and uses the annotation information to trace variables and data affected by user input data. Since our proposed technique can seamlessly be incorporated into the TypeScript compiler, developers can find vulnerabilities during the development process, unlike existing analysis tools performed as a separate tool. To show the feasibility of the proposed method, we implemented a prototype and evaluated its performance with 8 web applications with known security vulnerabilities. We found that our prototype implementation could detect all known security vulnerabilities correctly.

• ETRI Journal
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• v.42 no.3
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• pp.433-445
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• 2020

A denial-of-service (DoS) attack is a serious attack that targets web applications. According to Imperva, DoS attacks in the application layer comprise 60% of all the DoS attacks. Nowadays, attacks have grown into application- and business-layer attacks, and vulnerability-analysis tools are unable to detect business-layer vulnerabilities (logic-related vulnerabilities). This paper presents the business-layer dynamic application security tester (BLDAST) as a dynamic, black-box vulnerability-analysis approach to identify the business-logic vulnerabilities of a web application against DoS attacks. BLDAST evaluates the resiliency of web applications by detecting vulnerable business processes. The evaluation of six widely used web applications shows that BLDAST can detect the vulnerabilities with 100% accuracy. BLDAST detected 30 vulnerabilities in the selected web applications; more than half of the detected vulnerabilities were new and unknown. Furthermore, the precision of BLDAST for detecting the business processes is shown to be 94%, while the generated user navigation graph is improved by 62.8% because of the detection of similar web pages.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.218-232
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• 2015

According to the development of information processing technology and mobile communication technology, the utilization of mobile banking systems is drastically increasing in banking system. In the foreseeable future, it is expected to increase rapidly the demands of mobile banking in bank systems with the prevalence of smart devices and technologies. However, the keeping 'security' is very important in banking systems that handles personal information and financial assets. But it is very difficult to improve the security of banking systems only with the vulnerabilities and faults analysis methods of information security. Hence, in this paper, we accomplish the analysis of security risk factor and security vulnerability that occur in mobile banking system. With analyzed results, we propose the information security control and management processes for assessing and improving security based on the mechanisms which composes mobile banking system.

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

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.354-357
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• 2021

Software vulnerabilities are becoming more and more increasing, their role is to harm the computer systems of companies, governmental organizations and agencies. The main objective of this paper is to propose a method that will cluster future software vulnerabilities that may spread. This method is developed by combining the Multiple Correspondence Analysis (MCA), the Elbow procedure and the Kmeans Algorithm. A simulation was done on a dataset of 15713 observations. This simulation allowed us to identify families of future vulnerabilities. This model was evaluated using the silhouette index.