• KIPS Transactions on Computer and Communication Systems
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• v.4 no.5
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• pp.171-176
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• 2015

Because the specific security technology alone can not cope with sophisticated attacks, various security management models are applied. But, they do not focus on the vulnerability of the highest part because they offer so many common security management criteria. By analyzing the main information and confidential leakage cases inflicting enormous damage to our society, we found that attackers are using mainly an interface vulnerabilities - the paths that connect the internal and external of the organization, such as e-mail, web server, portable devices, and subcontractor employees. Considering the reality that time and resources to invest in security domain are limited, we point out the interface security vulnerabilities the possibility of attackers to exploit and present a convergence method of security measures. Finally, based of ROI(Return on Investment), we propose the real-time security management system through the intensive and continuous management.

• Review of KIISC
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• v.29 no.3
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• pp.29-36
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• 2019

폭발적으로 성장하는 소셜 미디어 서비스로 인해 개인간의 연결이 강화된 환경에서는 URL로써 전파되는 피싱 공격의 위험성이 크게 강조된다. 최근 텍스트 분류 및 모델링 분야에서 그 성능을 입증받은 딥러닝 알고리즘은 피싱 URL의 구문적, 의미적 특징을 각각 모델링하기에 적절하지만, 기존에 사용하는 규칙 기반 앙상블 방법으로는 문자와 단어로부터 추출되는 특징간의 비선형적인 관계를 효과적으로 융합하는데 한계가 있다. 본 논문에서는 피싱 URL의 구문적, 의미적 특징을 체계적으로 융합하기 위한 컨볼루션 신경망 기반의 퓨전 신경망을 제안하고 기계학습 방법 중 최고의 분류정확도 (0.9804)를 달성하였다. 학습 및 테스트 데이터셋으로 45,000건의 정상 URL과 15,000건의 피싱 URL을 수집하였고, 정량적 검증으로 10겹 교차검증과 ROC커브, 정성적 검증으로 오분류 케이스와 딥러닝 내부 파라미터를 시각화하여 분석하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.761-773
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• 2023

This paper proposes a method to increase the power-analysis resistance of the neural network model's feedforward process by replacing the exponential-based activation function, used in the deep-learning field, with an approximated function especially at the multi-layer perceptron model. Due to its nature, the feedforward process of neural networks calculates secret weight and bias, which already trained, so it has risk of exposure of internal information by side-channel attacks. However, various functions are used as the activation function in neural network, so it's difficult to apply conventional side-channel countermeasure techniques, such as masking, to activation function(especially, to exponential-based activation functions). Therefore, this paper shows that even if an exponential-based activation function is replaced with approximated function of simple form, there is no fatal performance degradation of the model, and than suggests a power-analysis resistant feedforward neural network with exponential-based activation function, by masking approximated function and whole network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.443-444
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• 2021

Security threats to information services are increasingly being developed, and the frequency and damage caused by security threats are also increasing. In particular, security threats occurring inside the organization are increasing significantly, and the size of the damage is also large. A zero trust model has been proposed as a way to improve such a security environment. In the zero trust model, a subject who has access to information resources is regarded as a malicious attacker. Subjects can access information resources after verification through identification and authentication processes. However, the initially proposed zero trust model basically focuses on the network and does not consider the security environment for systems or data. In this study, we proposed a zero trust-based access control mechanism that extends the existing zero trust model to the file system. As a result of the study, it was confirmed that the proposed file access control mechanism can be applied to implement the zero trust model.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.115-120
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• 2018

As the number ofconnected cars grows, the security of the connected cars is becoming more important. There are also increasing warnings about the threat of attacks via the CAN bus used for in-vehicle networks. An attack can attack through a vulnerability in the CAN bus because the attacker can access the CAN bus remotely, or directly to the vehicle, without a security certificate on the vehicle, and send a malicious error message to the devices connected to the CAN bus. A large number of error messages put the devices into a 'Bus-Off' state, causing the device to stop functioning. There is a way to detect the error frame, or to manage the power of the devices related to the bus, but eventually the new standard for the CAN bus will be the fundamental solution to the problem. If new standards are adopted in the future, they will need to be studied.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.373-385
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• 2021

To provide convenience and safety of drivers, the recent vehicles are being equipped with a number of electronic control units (ECUs). Multiple ECUs construct a network inside a vehicle to share information related to the vehicle's status; in addition, the CAN protocol is normally applied. As the modern vehicles provide highly convenient and safe services, it provides many types of attack surfaces; as a result, it makes them vulnerable to cyber attacks. The automotive IDS (Intrusion Detection System) is one of the promising techniques for securing vehicles. However, the existing methods for automotive IDS are able to analyze only periodic messages. If someone attacks on non-periodic messages, the existing methods are not able to properly detect the intrusion. In this paper, we present a method to detect intrusions including an attack using non-periodic messages. Moreover, we evaluate our method on the real vehicles, where we show that our method has 0% of FPR and 0% of FNR under our attack model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1031-1041
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• 2020

Cloud computing technology plays an important role in the deep learning industry as deep learning services are deployed frequently on top of cloud infrastructures. In such cloud environment, virtualization technology provides logically independent and isolated computing space for each tenant. However, recent studies demonstrate that by leveraging vulnerabilities of virtualization techniques and shared processor architectures in the cloud system, various side-channels can be established between cloud tenants. In this paper, we propose a novel attack scenario that can steal internal information of deep learning models by exploiting the Meltdown vulnerability in a multi-tenant system environment. On the basis of our experiment, the proposed attack method could extract internal information of a TensorFlow deep-learning service with 92.875% accuracy and 1.325kB/s extraction speed.

• Journal of Internet Computing and Services
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• v.2 no.4
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• pp.41-53
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• 2001

Multi-distributed web cluster model built for high availability E-Business model exposes internal system nodes on its structural characteristics and has a potential that normal job performance is impossible due to the intentional prevention and attack by an illegal third party. Therefore, the security system which protects the structured system nodes and can correspond to the outflow of information from illegal users and unfair service requirements effectively is needed. Therefore the suggested distributed invasion detection system is the technology which detects the illegal requirement or resource access of system node distributed on open network through organic control between SC-Agents based on the shared memory of SC-Server. Distributed invasion detection system performs the examination of job requirement packet using Detection Agent primarily for detecting illegal invasion, observes the job process through monitoring agent when job is progressed and then judges the invasion through close cooperative works with other system nodes when there is access or demand of resource not permitted.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.731-740
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• 2001

Multi-distributed web cluster model expanding conventional cluster system is the cluster system which processes large-scaled work demanded from users with parallel computing method by building a number of system nodes on open network into a single imaginary network. Multi-distributed web cluster model on the structured characteristics exposes internal system nodes by an illegal third party and has a potential that normal job performance is impossible by the intentional prevention and attack in cooperative work among system nodes. This paper presents the mutual authentication protocol of system nodes through key division method for the authentication of system nodes concerned in the registration, requirement and cooperation of service code block of system nodes and collecting the results and then designs SNKDC which controls and divides symmetrical keys of the whole system nodes safely and effectively. SNKDC divides symmetrical keys required for performing the work of system nodes and the system nodes transmit encoded packet based on the key provided. Encryption packet given and taken between system nodes is decoded by a third party or can prevent the outflow of information through false message.

• The KIPS Transactions:PartC
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• v.18C no.6
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• pp.369-378
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• 2011

To ensure data confidentiality and fine-grained access control in business environment, system model using KP-ABE(Key Policy-Attribute Based Encryption) and PRE(Proxy Re-Encryption) has been proposed recently. However, in previous study, data confidentiality has been effected by decryption right concentrated on cloud server. Also, Yu's work does not consider a access privilege management, so existing work become dangerous to collusion attack between malicious user and cloud server. To resolve this problem, we propose secure system model against collusion attack through dividing data file into header which is sent to privilege manager group and body which is sent to cloud server. And we construct the model of access privilege management using AONT based XOR threshold Secret Sharing, In addition, our scheme enable to grant weight for access privilege using XOR Share. In chapter 4, we differentiate existing scheme and proposed scheme.