• Convergence Security Journal
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• v.19 no.1
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• pp.111-120
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• 2019

As cyber-attacks become more intelligent and sophisticated, the importance of Security Operations Center(SOC) has increased and the number of SOC has been increasing. In order to cope with cyber threats, institutions and organizations use a variety of cyber security standards to create business procedures. However, SOC often need to be improved in accordance with the SOC environment because they collaborate with managed security service specialists rather than their own personnel. The NIST cyber security framework, information security management system, and managed security service companies were compared and analyzed. As a result, it was found that the NIST CSF is a framework that is easy to apply to managed security service, The content was judged to be insufficient. Therefore, in this study, NIST CSF was used as a reference model to derive the management items required for SOC environment, and the necessity, importance and ease of each item were confirmed through an Delphi technique and an improved cyber security framework was proposed.

• Convergence Security Journal
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• v.19 no.2
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• pp.21-28
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• 2019

The emergence of a hyper-connected-super-intelligence society, called the era of the Fourth Industrial Revolution, brought about a new change in the security environment. With ICT (Information Communication Technology) convergence and high-tech technologies introduced across the board, the person-centered driving force that moved the real space is replaced by the code-oriented cyberspace, and its dependency is constantly increasing. Paradoxically, however, these technological changes serve as another security vulnerability that threatens our society, and have brought about the justification for building a cyber defense system while simultaneously facing the opportunities and challenges brought by technology. In this study, the theory of self-defense was put forward on the basis of the theoretical basis for actively responding to the increasingly intelligent and mass-evolving cyberattacks, and firstly, the need to enact a cybersecurity law, secondly, and thirdly, the need to develop a response cooperation system with the U.S. and other cyber powers.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.73-82
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• 2018

In this work, a hardware based cryptographic module for the cyber security of nuclear power plant is developed using a system engineering approach. Nuclear power plants are isolated from the Internet, but as shown in the case of Iran, Man-in-the-middle attacks (MITM) could be a threat to the safety of the nuclear facilities. This FPGA-based module does not have an operating system and it provides protection as a firewall and mitigates the cyber threats. The encryption equipment consists of an encryption module, a decryption module, and interfaces for communication between modules and systems. The Advanced Encryption Standard (AES)-128, which is formally approved as top level by U.S. National Security Agency for cryptographic algorithms, is adopted. The development of the cyber security module is implemented in two main phases: reverse engineering and re-engineering. In the reverse engineering phase, the cyber security plan and system requirements are analyzed, and the AES algorithm is decomposed into functional units. In the re-engineering phase, we model the logical architecture using Vitech CORE9 software and simulate it with the Enhanced Functional Flow Block Diagram (EFFBD), which confirms the performance improvements of the hardware-based cryptographic module as compared to software based cryptography. Following this, the Hardware description language (HDL) code is developed and tested to verify the integrity of the code. Then, the developed code is implemented on the FPGA and connected to the personal computer through Recommended Standard (RS)-232 communication to perform validation of the developed component. For the future work, the developed FPGA based encryption equipment will be verified and validated in its expected operating environment by connecting it to the Advanced power reactor (APR)-1400 simulator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1205-1212
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• 2022

Cyber threat targeting ICS (Industrial Control System) has indicated drastic increases over the past decade and Cyber Incident in Critical Infrastructure such as Energy, Gas Terminal and Petrochemical industries can lead to disaster-level accidents including casualties and large-scale fires. In order to effectively respond to cyber attacks targeting ICS, a multi-layered defense-in-depth strategy considering Control System Architecture is necessary. In particular, the centralized security log system integrating OT (Operational Technology) and IT (Information Technology) plays an important role in the ICS incident response plan. The paper suggests the way of implementing centralized security log system that collects security events and logs using OPC Protocol from Level 0 to Level 5 based on IEC62443 Purdue Model to integrate ICS security logs with SIEM (Security Information Event Management) operated in IT environment.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.21-31
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• 2018

Cyber penetration attacks can not only damage cyber space but can attack entire infrastructure such as electricity, gas, water, and nuclear power, which can cause enormous damage to the lives of the people. Also, cyber space has already been defined as the fifth battlefield, and strategic responses are very important. Most of recent cyber attacks are caused by malicious code, and since the number is more than 1.6 million per day, automated analysis technology to cope with a large amount of malicious code is very important. However, it is difficult to deal with malicious code encryption, obfuscation and packing, and the dynamic analysis technique is not limited to the performance requirements of dynamic analysis but also to the virtual There is a limit in coping with environment avoiding technology. In this paper, we propose a machine learning based malicious code analysis technique which improve the weakness of the detection performance of existing analysis technology while maintaining the light and high-speed analysis performance applicable to commercial endpoints. The results of this study show that 99.13% accuracy, 99.26% precision and 99.09% recall analysis performance of 71,000 normal file and malicious code in commercial environment and analysis time in PC environment can be analyzed more than 5 per second, and it can be operated independently in the endpoint environment and it is considered that it works in complementary form in operation in conjunction with existing antivirus technology and static and dynamic analysis technology. It is also expected to be used as a core element of EDR technology and malware variant analysis.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.33-40
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• 2021

Automatic Speech Recognition(ASR) is a technology that analyzes human speech sound into speech signals and then automatically converts them into character strings that can be understandable by human. Speech recognition technology has evolved from the basic level of recognizing a single word to the advanced level of recognizing sentences consisting of multiple words. In real-time voice conversation, the high recognition rate improves the convenience of natural information delivery and expands the scope of voice-based applications. On the other hand, with the active application of speech recognition technology, concerns about related cyber attacks and threats are also increasing. According to the existing studies, researches on the technology development itself, such as the design of the Automatic Speaker Verification(ASV) technique and improvement of accuracy, are being actively conducted. However, there are not many analysis studies of attacks and threats in depth and variety. In this study, we propose a cyber attack model that bypasses voice authentication by simply manipulating voice frequency and voice speed for AI voice recognition service equipped with automated identification technology and analyze cyber threats by conducting extensive experiments on the automated identification system of commercial smartphones. Through this, we intend to inform the seriousness of the related cyber threats and raise interests in research on effective countermeasures.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.7-10
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• 2014

In order to develop smart grid communications infrastructure, a high level of interconnectivity and reliability among its nodes is required. Sensors, advanced metering devices, electrical appliances, and monitoring devices, just to mention a few, will be highly interconnected allowing for the seamless flow of data. Reliability and security in this flow of data between nodes is crucial due to the low latency and cyber-attacks resilience requirements of the Smart Grid. In particular, Artificial Intelligence techniques such as Fuzzy Logic, Bayesian Inference, Neural Networks, and other methods can be employed to enhance the security gaps in conventional IDSs. A distributed FPGA-based network with adaptive and cooperative capabilities can be used to study several security and communication aspects of the smart grid infrastructure both from the attackers and defensive point of view. In this paper, the vital issue of security in the smart grid is discussed, along with a possible approach to achieve this by employing FPGA based Radial Basis Function (RBF) network intrusion.

• International Journal of Contents
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• v.11 no.3
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• pp.39-46
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• 2015

When host images are watermarked with CRT (Chinese Remainder Theorem), the watermark images are still robust in spite of the damage of the host images by maintaining the remainders in an unchanged state within some range of the changes that are incurred by the attacks. This advantage can also be attained by "zero-watermarking," which does not change the host images in any way. This paper proposes an improved zero-watermarking scheme for color images on the DCT (Discrete Cosine Transform) domain that is based on the CRT. In the scheme, RGB images are converted into YCbCr images, and one channel is used for the DCT transformation. A key is then computed from the DC and three low-frequency AC values of each DCT block using the CRT. The key finally becomes the watermark key after it is combined four times with a scrambled watermark image. When watermark images are extracted, each bit is determined by majority voting. This scheme shows that watermark images are robust against a number of common attacks such as sharpening, blurring, JPEG lossy compression, and cropping.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.61-66
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• 2019

FinTech has expanded to the extent that not only businesses but almost everyone can feel the impact. The spread of the scope of use has introduced a variety of new financial services that are changing the way we live. In these environments, it is important to develop reliable security measures to protect against cyber attacks. The number of mobile financial transactions in the financial sector is also increasing, making security vulnerable. In this study, we studied security through mutual authentication method that can safely handle financial security and focused on FinTech's security processing through multi-party mutual authentication method that strongly prevents leakage of information even in the event of continuous and sophisticated attacks.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.42-49
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• 2021

As cyber attacks become more intelligent, there is difficulty in detecting advanced attacks in various fields such as industry, defense, and medical care. IPS (Intrusion Prevention System), etc., but the need for centralized integrated management of each security system is increasing. In this paper, we collect big data for intrusion detection and build an intrusion detection platform using deep learning and CNN (Convolutional Neural Networks). In this paper, we design an intelligent big data platform that collects data by observing and analyzing user visit logs and linking with big data. We want to collect big data for intrusion detection and build an intrusion detection platform based on CNN model. In this study, we evaluated the performance of the Intrusion Detection System (IDS) using the KDD99 dataset developed by DARPA in 1998, and the actual attack categories were tested with KDD99's DoS, U2R, and R2L using four probing methods.