• Convergence Security Journal
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• v.21 no.1
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• pp.45-53
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• 2021

When the security monitoring system is performed in a separation network, there is little normal anomaly detection in internal networks or high-risk sections. Therefore, after the establishment of the security network, a model is needed to evaluate state-of-the-art cyber threat anomalies for internal network in separation network to complete the optimized security structure. In this study, We evaluate it by generating datasets of cyber vulnerabilities and malicious code arising from general and separation networks, It prepare for the latest cyber vulnerabilities in internal network cyber attacks to analyze threats, and established a cyber security test evaluation system that fits the characteristics. The study designed an evaluation model that can be applied to actual separation network institutions, and constructed a test data set for each situation and applied a real-time security assessment model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.893-900
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• 2004

While security traditionally has been an important issue in information systems, the problem of the greatest concern today is related to the availability of information and continuity of services. Since people and organizations now rely on distributed systems in accessing and processing critical services and mission, the availability of information and continuity of services are becoming more important. Therefore the importance of implementing systems that continue to function in the presence of security breaches cannot be overemphasized. One of the solutions to provide the availability and continuity of information system applications is introducing an intrusion tolerance system. Security mechanism and adaptation mechanism can ensure intrusion tolerance by protecting the application from accidental or malicious changes to the system and by adapting the application to the changing conditions. In this paper we propose an intrusion tolerance model that improves the developmental structure while assuring security level. We also design and implement an adaptive intrusion tolerance system to verify the efficiency of our model by integrating proper functions extracted from CORBA security modules.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.231-237
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• 2017

Threat intelligences collected from cyber incident sharing system and security events collected from Security Information & Event Management system are analyzed and coped with expanding malicious code rapidly with the advent of big data. Analytical classification of the threat intelligence in cyber incidents requires various features of cyber observable. Therefore it is necessary to improve classification accuracy of the similarity by using multi-profile which is classified as the same features of cyber observables. We propose a multi-profile ensemble model performed similarity analysis on cyber incident of threat intelligence based on both attack types and cyber observables that can enhance the accuracy of the classification. We see a potential improvement of the cyber incident analysis system, which enhance the accuracy of the classification. Implementation of our suggested technique in a computer network offers the ability to classify and detect similar cyber incident of those not detected by other mechanisms.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.139-153
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• 2016

Cyber incident collected from cyber-threat-intelligence sharing Center is growing rapidly due to expanding malicious code. It is difficult for Incident analysts to extract and classify similar features due to Cyber Attacks. To solve these problems the existing Similarity Analysis Method is based on single or multiple cyber observable of similar incidents from Cyber Attacks data mining. This method reduce the workload for the analysis but still has a problem with enhancing the unreality caused by the provision of improper and ambiguous information. We propose a incident analysis model performed similarity analysis on the hierarchically classified cyber observable based on cyber incident that can enhance both availability by the provision of proper information. Appling specific cyber incident analysis model, we will develop a system which will actually perform and verify our suggested model.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.6
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• pp.339-348
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• 2006

Recently, many researches on detecting and responding worms due to the fatal infrastructural damages explosively damaged by automated attack tools, particularly worms. Network service vulnerability exploiting worms have high propagation velocity, exhaust network bandwidth and even disrupt the Internet. Previous worm researches focused on signature-based approaches however these days, approaches based on behavioral features of worms are more highlighted because of their low false positive rate and the attainability of early detection. In this paper, we propose a Distributed Worm Detection Model based on packet marking. The proposed model detects Worm Cycle and Infection Chain among which the behavior features of worms. Moreover, it supports high scalability and feasibility because of its distributed reacting mechanism and low processing overhead. We virtually implement worm propagation environment and evaluate the effectiveness of detecting and responding worm propagation.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.855-864
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• 2005

In this paper, we propose an intrusion detection system(IDS) architecture which can detect and respond against the generation of abnormal traffic such as malicious code and Internet worms. We model the system, design and implement a simulator using OPNET Modeller, for the performance analysis on the response capacity of alert information in the proposed system. At first, we model the arrival process of alert information resulted from abnormal traffic. In order to model the situation in which alert information is intensively produced, we apply the IBP(Interrupted Bernoulli Process) which may represent well the burstiness of traffic. Then we perform the simulation in order to gain some quantitative understanding of the system for our performance parameters. Based on the results of the performance analysis, we analyze factors which may hinder in accelerating the speed of security node, and would like to present some methods to enhance performance.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.305-310
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• 2013

To provide medical services to patients who have a terminal illness, recent hospital patients to monitor the state of the device attached to the body, the body insertion device is. U-Healthcare Environment and hospital officials indiscriminately exploited by the patient's vital information, however, could threaten the patient's life problems are appearing. In this paper, depending on the level of authority, hospital officials, Union of ID-based authentication model is proposed to use a patient's vital information. Union proposed model identify different authentication system is used in hospitals that exist in various forms in a number of ID information, health / medical information sharing between hospitals without exposure to unnecessary personal information, you can be assured of the anonymity. In particular, with easy access to patient information, hospital officials about the malicious act to protect patient information to access level for the rights granted by third parties to prevent easy access.

• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.434-442
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• 2018

Recently, the threat to the security and damage of important data leaked by devices of intranet infected by malicious code through the Internet have been increasing. Therefore, the partitioned intranet model that blocks access to the server for business use by implementing authentication of devices connected to the intranet is required. For this, logical net partition with the VDI(Virtual Desktop Infrastructure) method is no information exchange between physical devices connected to the intranet and the virtual device so that it could prevent data leakage and improve security but it is vulnerable to the attack to expose internal data, which has access to the server for business connecting a nonregistered device into the intranet. In order to protect the server for business, we suggest a blockchain based network partition model applying blockchain technology to VDI. It contributes to decrease in threat to expose internal data by improving not only capability to verify forgery of devices, which is the vulnerability of the VDI based logical net partition, but also the integrity of the devices.

• 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.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.9-16
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• 2019

In this paper, it will analyze security problems, so technology's potential can apply to business security area. First, in order to deep learning do security tasks sufficiently in the business area, deep learning requires repetitive learning with large amounts of data. In this paper, to acquire learning ability to do stable business tasks, it must detect abnormal IP packets and attack such as normal software with malicious code. Therefore, this paper will analyze whether deep learning has the cognitive ability to detect various attack. In this paper, to deep learning to reach the system and reliably execute the business model which has problem, this paper will develop deep learning technology which is equipped with security engine to analyze new IP about Session and do log analysis and solve the problem of mathematical role which can extract abnormal data and distinguish infringement of system data. Then it will apply to business model to drop the vulnerability and improve the business performance.