• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.139-145
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• 2009

This study proposes a model of collection process for real-time forensic data, in which the manager was to respond to infringement incidents in terms of system operation and inspection and to collect, analyze and restore forensic data immediately after an incident took place. The suggested model was modeled in seven processes according to functional elements. Unlike the old and managerial forensic processes, the model allowed the manager to react to infringement incidents in the aspects of system operation and inspection and to follow the processes of collecting, analyzing, and restoring forensic data in case of an incident. There also was a feedback process designed towards the step of gathering forensic data through the stages of systematizing reaction strategies in order that he or she be able to bring about comprehensive and structural responses to an incident like the former processes in which it is difficult to bring about instant responses.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.73-80
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• 2009

Internet accidents have skyrocketed every year. It always has been threatened by the methods such as hacking and Spyware. The majority of security accident is formed of the loss of authentication information, and the internal user who is not authorized. The importance of security is also emphasized when someone tries to do something accessing to the main information system. Accordingly, Biometrics has been used in many ways. OTP, however, must have a few devices accessing to several systems, and Biometrics involve some risk of mis-recognition rate and mis-denial rate. It also has the risk possible to access to the main information system when losing OTP. This research reduced risks about the loss as separating RFID leader for mobile, Tag and the accessor's cellular phone, and is about pseudo random validation key generated from the administration system through contact with RFID leader for mobile and Tag. As sending the key to user's cell phone which is already registered, security is strengthened more than existing connection methods through the ID and password. RFID for mobile not generalized to the present has been studied as a tool accessing to the main information system.

• Journal of Industrial Convergence
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• v.21 no.3
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• pp.181-188
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• 2023

The e-Government standard framework provides overall technologies such as reuse of common components for web environment development such as domestic government/public institutions, connection of standard modules, and resolution of dependencies. However, in a standardized development environment, there is a possibility of updating old versions according to core versions and leakage of personal and confidential information due to hacking or computer viruses. This study directly analyzes security vulnerabilities focusing on websites that operate eGovFrame in Korea. As a result of analyzing/classifying vulnerabilities at the internal programming language source code level, five items associated with representative security vulnerabilities could be extracted again. As a countermeasure against this, the security settings and functions through the 2 steps (1st and 2nd steps) and security policy will be explained. This study aims to improve the security function of the e-government framework and contribute to the vitalization of the service.

• Smart Media Journal
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• v.11 no.2
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• pp.25-30
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• 2022

With the recent development of device performance such as smartphones, cameras, and video cameras, it has become possible to obtain human biometric information from images and photos. A German hacker group obtained human iris information from high-definition photos and revealed hacking into iris scanners on smartphones. As high-quality images and photos can be obtained with such advanced devices, the need for a suitable security system is also emerging. Therefore, in this paper, we propose a method of automatically masking human iris information in images and photos using Haar Cascades and Blur models from openCV. It is a technology that automatically masks iris information by recognizing a person's eye in a photo or video and provides the result. If this technology is used in devices and applications such as smartphones and zoom, it is expected to provide better security services to users.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.12
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• pp.955-963
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• 2017

Nowadays, fintech becomes the key technology of the mobile banking and payments. Financial market is moved to fintech-based non-face-to-face trade/payment from traditional face-to-face process in Korea. Core of this transition is the smartphones, which have several sensitive sensors for personal identifications such as fingerprint and iris recognition sensors. But it has some originated security risks by data path attacks, for instance, hacking and pharming. Multi-level certification and security systems are applied to avoid these threats effectively, while these protections can be cause of some inconvenience for non-face-to-face certifications and financing processes. In this paper, I confirmed that it have sensible differences correspond with the data connection paths such as WiFi networks and mobile communication networks of the smartphones, and I propose a gradual certification method which alleviates the inconvenience by risk-level definitions of the data-paths.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1786-1793
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• 2022

Cyber-attacks such as smishing and hacking mail exploiting COVID-19, political and social issues, have recently been continuous. Machine learning and deep learning technology research are conducted to prevent any damage due to cyber-attacks inducing malicious links to breach personal data. It has been concluded as a lack of basis to judge the attacks to be malicious in previous studies since the features of data set were excessively simple. In this paper, nine main features of three types, "URL Days", "URL Word", and "URL Abnormal", were proposed in addition to lexical features of URL which have been reflected in previous research. F1-Score and accuracy index were measured through four different types of machine learning algorithms. An improvement of 0.9% in a result and the highest value, 98.5%, were examined in F1-Score and accuracy through comparatively analyzing an existing research. These outcomes proved the main features contribute to elevating the values in both accuracy and performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1872-1879
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• 2022

Recently, with the development of artificial intelligence technology, research to use artificial intelligence to detect hacking attacks is being actively conducted. However, the fact that security data is a representative imbalanced data is recognized as a major obstacle in composing the learning data, which is the key to the development of artificial intelligence models. Therefore, in this paper, we propose a W-VAE oversampling technique that applies VAE, a deep learning generation model, to data extraction for oversampling, and sets the number of oversampling for each class through weight calculation using K-NN for sampling. In this paper, a total of five oversampling techniques such as ROS, SMOTE, and ADASYN were applied through NSL-KDD, an open network security dataset. The oversampling method proposed in this paper proved to be the most effective sampling method compared to the existing oversampling method through the F1-Score evaluation index.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.455-457
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• 2021

App is used on mobile devices such as smartphones and also has malicious code, which can be divided into normal and malicious depending on the presence or absence of hacking codes. Because there are many kind of malware, it is difficult to detect directly, we propose a method to detect malicious app using AI. Most of the existing methods are to detect malicious app by extracting features from malicious app. However, the number of types have increased exponentially, making it impossible to detect malicious code. Therefore, we would like to propose two more methods besides detecting malicious app by extracting features from most existing malicious app. The first method is to learn normal app to extract normal's features, as opposed to the existing method of learning malicious app and find abnormalities (malicious app). The second one is an 'ensemble technique' that combines the existing method with the first proposal. These two methods need to be studied so that they can be used in future mobile environment.

• Convergence Security Journal
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• v.22 no.2
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• pp.59-66
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• 2022

Recently, smart home technology has been developed with a great response due to the convenience of home automation. Smart home technology provides various services by connecting various Internet of Things (IoT) and sensors to a home network through wired/wireless networks. In addition, the smart home service easily and conveniently controls lighting, energy, environment, and door cameras through a wall pad. However, while it has become a social issue due to the recent hacking accident of wall pads, personal information leakage and privacy infringement are expected. Accordingly, it is necessary to prepare preventive and countermeasures against security vulnerability factors of wall pads. Therefore, this study expects that it can be used as basic data for future smart home application and response technology development by examining the weak causes and countermeasures related to wall pads.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.863-898
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• 2023

Previous studies have shown that insiders pose risks to the security of organisations' secret information. Information security policy (ISP) intentional violation can jeopardise organisations. For years, ISP violations persist despite organisations' best attempts to tackle the problem through security, education, training and awareness (SETA) programs and technology solutions. Stopping hacking attempts e.g., phishing relies on personnel's behaviour. Therefore, it is crucial to consider employee behaviour when designing strategies to protect sensitive data. In this case, organisations should also focus on improving employee behaviour on security and creating positive security perceptions. This paper investigates the role of psychological capital (PsyCap), punishment and organisational security resources in influencing employee behaviour and ultimately reducing ISP violations. The model of the proposed study has been modified to investigate the connection between self-efficacy, resilience, optimism, hope, perceived sanction severity, perceived sanction certainty, security response effectiveness, security competence and ISP violation. The sample of the study includes 364 bank employees in Jordan who participated in a survey using a self-administered questionnaire. The findings show that the proposed approach acquired an acceptable fit with the data and 17 of 25 hypotheses were confirmed to be correct. Furthermore, the variables self-efficacy, resilience, security response efficacy, and protection motivation directly influence ISP violations, while perceived sanction severity and optimism indirectly influence ISP violations through protection motivation. Additionally, hope, perceived sanction certainty, and security skills have no effect on ISP infractions that are statistically significant. Finally, self-efficacy, resiliency, optimism, hope, perceived severity of sanctions, perceived certainty of sanctions, perceived effectiveness of security responses, and security competence have a substantial influence on protection motivation.