• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.117-128
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• 2008

Compared with the existing bar code system, RFID system has lots of advantages such as it identifies automatically massive objects. We might anticipate RFID technology will be a substitution for an optical bar code system in the near future. However, their feature that uses radio waves may cause various security problems. Many kinds of solutions have been researched to overcome these security problems. In this paper, we analyze the previous proposed protocols. And then, we categorize RFID authentication into two types according to the synchronization requirement between a Back-end Database and a Tag. In addition, we introduce the previous proposed approaches to tag search problem in RFID authentication. And we propose an efficient method which provides fast tag search by using membership test algorithm, a Bloom filter.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.5
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• pp.147-157
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• 2003

We often use cryptographic systems on small devices such as mobile phones, smart cards and so on. But such devices are delicate against the tlreat of key exposure of secret keys. To reduce the damage caused by exposure of secret keys stored on such devices, the concept of forward security is introduced. In this Paper, we present a new forward secure signature scheme based on Gap Diffie-Hellman groups. Our scheme achieves security against chosen-message attacks under the computational Diffie-Hellman assumption in the random oracle model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.73-92
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• 2005

Joux's tripartite key agreement protocol is one of the most prominent developments in the area of key agreement. Although certificate-based and ID-based authentication schemes have been proposed to provide authentication for Joux's protocol, no provably secure password-based one round tripartite key agreement protocol has been proposed yet. We propose a secure one round password-based tripartite key agreement protocol that builds on Joux's protocol and adapts PAK-EC scheme for password-based authentication, and present a proof of its security.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1067-1076
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• 2023

Recently, as variant malware has increased, the scale of cyber hacking incidents is expanding. To respond to intelligent cyberhacking attack, machine learning-based research is actively underway to effectively classify malware families. However, existing classification models have problems where performance deteriorates when the dataset is obfuscated or sparse. In this paper, we propose a hybrid dataset that combines features extracted from ASM files and BYTES files, and evaluate classification performance using FNN. As a result of the experiment, the proposed method showed performance improvement of about 4% compared to a single dataset, and in particular, performance improvement of about 30% for rare families.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.629-635
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• 2019

In Deep Learning models derivative is implemented by error back-propagation which enables the model to learn the error and update parameters. It can find the global (or local) optimal points of parameters even in the complex models taking advantage of a huge improvement in computing power. However, deliberately generated data points can 'fool' models and degrade the performance such as prediction accuracy. Not only these adversarial examples reduce the performance but also these examples are not easily detectable with human's eyes. In this work, we propose the method to detect adversarial datasets with random noise addition. We exploit the fact that when random noise is added, prediction accuracy of non-adversarial dataset remains almost unchanged, but that of adversarial dataset changes. We set attack methods (FGSM, Saliency Map) and noise level (0-19 with max pixel value 255) as independent variables and difference of prediction accuracy when noise was added as dependent variable in a simulation experiment. We have succeeded in extracting the threshold that separates non-adversarial and adversarial dataset. We detected the adversarial dataset using this threshold.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.392-399
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• 2013

Due to the development of IT technology and the information age, a dependency of the network over the most of our lives have grown to a greater extent. Although it provides us to get various useful information and service, it also has negative effectiveness that can provide network intruder with vulnerable roots. In other words, we need to urgently cope with theses serious security problem causing service disableness or system connected to network obstacle with exploiting various packet information. Many experts in a field of security are making an effort to develop the various security solutions to respond against these threats, but existing solutions have a lot of problems such as lack of storage capacity and performance degradation along with the massive increase of packet data volume. Therefore we propose the packet analysis model to apply issuing Big Data technology in the field of security. That is, we used NoSQL which is technology of massive data storage to collect the packet data growing massive and implemented the packet analysis model based on K-means clustering using MapReudce which is distributed programming framework, and then we have shown its high performance by experimenting.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.163-169
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• 2020

A smart key has been used in a variety of embedded environments and there also have been attacks from a remote place by amplifying signals at a location of a user. Existing studies on defence techniques suggest multiple sensors and hash functions to improve authentication speed; these, however, increase the electricity usage and the probability of type 1 error. For these reasons, I suggest an embedded security controller based on client authentication and user movement information improving the authentication method between a controller and a host device. I applied encryption algorithm to the suggested model for communication using an Arduino board, GPS, and Bluetooth and performed authentication through path analysis utilizing user movement information for the authentication. I found that the change in usability was nonsignificant when performing actions using the suggested model by evaluating the time to encode and decode. The embedded security controller in the model can be applied to the system of a remote controller for a two-wheeled vehicle or a mobile and stationary host device; in the process of studying, I found that encryption and decryption could take less then 100ms. The later study may deal with protocols to speed up the data communication including encryption and decryption and the path data management.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.1019-1034
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• 2022

Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.148-155
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• 2002

Multithreaded models improve the efficiency of parallel systems by combining inner parallelism, asynchronous data availability and the locality of von Neumann model. This model executes thread code which is generated by compiler and of which quality is given by the method of generation. But multithreaded models have the demerit that execution model is restricted to a specific platform. On the contrary, Java has the platform independency, so if we can translate from threads code to Java bytecode, we can use the advantages of multithreaded models in many platforms. Java executes Java bytecode which is intermediate language format for Java virtual machine. Java bytecode plays a role of an intermediate language in translator and Java virtual machine work as back-end in translator. But, Java bytecode which is translated from multithreaded models have the demerit that it is not secure. This paper, multhithread code whose feature of platform independent can execute in java virtual machine. We design and implement translator which translate from thread code of multithreaded code to Java bytecode and which check secure problems from Java bytecode.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.43-54
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• 2016

The occurrence of cyber crime is on the rise every year, and the security control center, which should play a crucial role in monitoring and early response against the cyber attacks targeting various information systems, its importance has increased accordingly. Every endeavors to prevent cyber attacks is being attempted by information security personnel of government and financial sector's security control center, threat response Center, cyber terror response center, Cert Team, SOC(Security Operator Center) and else. The ordinary method to monitor cyber attacks consists of utilizing the security system or the network security device. It is anticipated, however, to be insufficient since this is simply one dimensional way of monitoring them based on signatures. There has been considerable improvement of the security control system and researchers also have conducted a number of studies on monitoring methods to prevent threats to security. In accordance with the environment changes from ESM to SIEM, the security control system is able to be provided with more input data as well as generate the correlation analysis which integrates the processed data, by extraction and parsing, into the potential scenarios of attack or threat. This article shows case studies how to detect the threat to security in effective ways, from the initial phase of the security control system to current SIEM circumstances. Furthermore, scenarios based security control systems rather than simple monitoring is introduced, and finally methods of producing the correlation analysis and its verification methods are presented. It is expected that this result contributes to the development of cyber attack monitoring system in other security centers.