• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.341-342
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• 2017

Control and development systems such as air traffic control systems, road traffic systems, and Korea Hydro &Nuclear Power are the infrastructure facilities of the country, and if the malicious hacking attacks proceed, the damage is beyond imagination. In fact, Korea Hydro & Nuclear Power has been subjected to a hacking attack, causing internal information to leak and causing social problems. In this study, we analyze the environment of the development control system and analyze the status of the convergence security research, which is a recent issue, and propose a strategy system for stabilizing various power generation control systems and propose countermeasures. We propose a method to normalize and integrate data types from various physical security systems (facilities), IT security systems, access control systems, to control the whole system through convergence authentication, and to detect risks through fusion control.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.198-201
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• 2022

Recently, new cyber threats targeting new technologies are increasing, and hackers' attack targets are becoming broader and more intelligent. To counter these attacks, major security companies are using traditional EDR (Endpoint Detection and Response) solutions. However, the conventional method does not consider the context, so there is a limit to the accuracy and efficiency of responding to an advanced attack. In order to improve this problem, the need for a security solution centered on XDR (Extended Detection and Response) has recently emerged. In this study, we present effective threat detection and countermeasures in a changing environment through XDR trends and development roadmaps using machine learning-based context analysis.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.531-540
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• 2021

As cyber attacks and crimes increase exponentially and hacking attacks become more intelligent and advanced, hacking attack methods and routes are evolving unpredictably and in real time. In order to reinforce the enemy's responsiveness, this study aims to propose a method for developing an artificial intelligence-based security control platform by building a next-generation security system using artificial intelligence to respond by self-learning, monitoring abnormal signs and blocking attacks.The artificial intelligence-based security control platform should be developed as the basis for data collection, data analysis, next-generation security system operation, and security system management. Big data base and control system, data collection step through external threat information, data analysis step of pre-processing and formalizing the collected data to perform positive/false detection and abnormal behavior analysis through deep learning-based algorithm, and analyzed data Through the operation of a security system of prevention, control, response, analysis, and organic circulation structure, the next generation security system to increase the scope and speed of handling new threats and to reinforce the identification of normal and abnormal behaviors, and management of the security threat response system, Harmful IP management, detection policy management, security business legal system management. Through this, we are trying to find a way to comprehensively analyze vast amounts of data and to respond preemptively in a short time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.791-805
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• 2022

In recent years, the number of scams related to voice phishing has been on the decline, but the number of messenger phishing attacks, a new type of crime, is increasing. In this study, by analyzing SNS posts containing messenger phishing cases, criminal trends of the main methods, imposture of trusted relative and fake payment were identified. Through the analysis, main words and patterns composing the message and the similarity and continuity of the phone numbers used were derived as criminal attributes, and criminal organizations were grouped. As the results of the analysis, we propose a cooperative system to prevent damage from messenger phishing by disseminating the criminal information collected by investigative agencies to private operators, and a plan to respond to messenger phishing predicted through grouping of criminal organizations.

• ETRI Journal
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• v.37 no.3
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• pp.584-594
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• 2015

To date, many different kinds of logic styles for hardware countermeasures have been developed; for example, SABL, TDPL, and DyCML. Current mode-based logic styles are useful as they consume less power compared to voltage mode-based logic styles such as SABL and TDPL. Although we developed TPDyCML in 2012 and presented it at the WISA 2012 conference, we have further optimized it in this paper using a binary decision diagram algorithm and confirmed its properties through a practical implementation of the AES S-box. In this paper, we will explain the outcome of HSPICE simulations, which included correlation power attacks, on AES S-boxes configured using a compact NMOS tree constructed from either SABL, CMOS, TDPL, DyCML, or TPDyCML. In addition, to compare the performance of each logic style in greater detail, we will carry out a mutual information analysis (MIA). Our results confirm that our logic style has good properties as a hardware countermeasure and 15% less information leakage than those secure logic styles used in our MIA.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1049-1055
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• 2013

Smartphones are rapidly growing because of easy installation of the apps (application software) that users actually want. There are increasingly many apps that require cryptographic suites to be installed, for instance, for protecting account and financial data. Android platform provides protection mechanisms for memory and storage based on Linux kernel, but they are vulnerable to rooting attacks. In this paper, we analyze security mechanisms of Android platform and point out security problems. We show the security vulnerabilities of several commercial apps and suggest appropriate countermeasures.

• Journal of the Korea Society for Simulation
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• v.16 no.1
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• pp.59-68
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• 2007

IT (Intrusion Tolerant) technology is for guaranteeing the availability of service for certain amount time against the attacks which couldn't be prevented by the currently deployed information security countermeasures. IT (Intrusion Tolerant) technology mainly makes use of the replication of service and system fur enhancing availability, and voting scheme and GMP (Croup Management Protocol) are used for the correctness of service. This paper presents a scheme to analyze dependability of IT (Intrusion Tolerant) technology through probabilistic and simulation method. Using suggested analysis scheme, we can analyze the robustness and make a sensible trade-offs in of IT (Intrusion Tolerant) technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.221-223
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• 2014

Power analysis attack on cryptographic hardware device aims to study the power consumption while performing operations using secrets keys. Power analysis is a form of side channel attack which allow an attacker to compute the key encryption from algorithm using Simple Power Analysis (SPA), Differential Power Analysis (DPA) or Correlation Power Analysis (CPA). The theoretical weaknesses in algorithms or leaked informations from physical implementation of a cryptosystem are usually used to break the system. This paper describes how power analysis work and we provide an overview of countermeasures against power analysis attacks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1107-1113
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• 2015

The number of phishing/pharming attacks occurring has increased and consequently, the number of studies on anti-phishing/pharming has also increased. The target sites of phishing/pharming are financial sites, and these have a low connection rate compared to those of portal sites. In this paper, we propose an anti-phishing/pharming method that uses a portal site as a stopover. The proposed method is based on the reliability of portal sites. This method is intended for general users rather than for professional users or developers. We also analyze the safety of the proposed method by separating the method into sub components of module safety assumption.