• Journal of IKEEE
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• v.24 no.2
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• pp.669-672
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• 2020

In this paper, we analyzed the characteristics of cyber attacks and major threat scenarios that could occur around intelligent building management Systems(IBS) by cyber attack security threats against cyber physics systems. Generally determined that lowering the likelihood of aggression against predictable threats would be a more realistic approach to attack response. The countermeasures against this need to be applied to multi-layered defense systems, and three alternatives were proposed: preliminary cyber safety diagnosis for protection targets and the establishment of mobile security control systems.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.381-382
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• 2024

Open RAN(Radio Access Network)을 선도적으로 연구하고 있는 O-RAN Alliance에서는 Open RAN의 E2 인터페이스에서 발생 가능한 보안 위협 중 하나로 MitM(Man-in-the-Middle) 공격을 명시하였다. 그러나 이에 대응하기 위한 보안 요구사항으로는 3계층 보안 프로토콜인 IPsec 사용을 명시하고 있으며, 2계층 공격인 ARP(Address Resolution Protocol) 스푸핑에 대한 요구사항은 명시하고 있지 않다. 따라서 본 논문에서는 MitM 공격 중 하나인 ARP 스푸핑으로부터 E2 인터페이스를 보호하기 위해, Near-RT RIC의 ARP 테이블에서 E2 인터페이스로 연결되는 장비에 대한 MAC 주소를 정적으로 설정할 수 있는 xApp을 제안한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.145-156
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• 2022

To strengthen the security of autonomous vehicles, this study derived checklists through the analysis of the status of autonomous vehicle security. The analyzed statuses include autonomous vehicle characteristics, security threats, and domestic and foreign security standards. The derived checklists are then applied to the AHP(Analytic Hierarchy Process) model to find their relative importance. Relative importance was ranked as one of cyber security management system establishment and implementation, encryption, risk assessment, etc. The significance of this study is to reduce cyber security incidents that cause human casualties as well improve the level of security management of autonomous vehicles in related companies by deriving the autonomous vehicle security level checklists and demonstrating the model. If the inspection is performed considering the relative importance of the checklists, the security level can be identified early.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.417-428
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• 2018

The intelligent video surveillance environment is a system that extracts various information about a video object and enables automated processing through the analysis of video data collected in CCTV. However, since the privacy exposure problem may occur in the process of intelligent video surveillance, it is necessary to take a security measure. Especially, video metadata has high vulnerability because it can include various personal information analyzed based on big data. In this paper, we propose a COP-Transformation scheme to protect video metadata. The proposed scheme is advantageous in that it greatly enhances the security and efficiency in processing the video metadata.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.776-779
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• 2012

Recently one of the hot topics of IT field is big data. The security's meaning changed a lot, so security tools which were used to protect the limit area traditionally, now don't have any effectiveness. In the age of Cloud Computing, big data will do the best work. This paper discusses the technology related to big data and the intelligent security system utilizing big data.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.445-451
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• 2013

Cyber terrorism has lately aimed at major domestic financial institutions and broadcasters. A large number of PCs have been infected, so normal service is difficult. As a result, the monetary damage was reported to be very high. It is important to recognize the importance of big data. But security and privacy efforts for big data is at a relatively low level, therefore the marketing offort is very active. This study concerns the analysis of Big Data industry and Big data security threats that are intelligent and the changes in defense technology. Big data, security countermeasures for the future are also presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1466-1488
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• 2022

Recently, the importance and necessity of artificial intelligence (AI), especially machine learning, has been emphasized. In fact, studies are actively underway to solve complex and challenging problems through the use of AI systems, such as intelligent CCTVs, intelligent AI security systems, and AI surgical robots. Information security that involves analysis and response to security vulnerabilities of software is no exception to this and is recognized as one of the fields wherein significant results are expected when AI is applied. This is because the frequency of malware incidents is gradually increasing, and the available security technologies are limited with regard to the use of software security experts or source code analysis tools. We conducted a study on MalDC, a technique that converts malware into images using machine learning, MalDC showed good performance and was able to analyze and classify different types of malware. MalDC applies a preprocessing step to minimize the noise generated in the image conversion process and employs an image augmentation technique to reinforce the insufficient dataset, thus improving the accuracy of the malware classification. To verify the feasibility of our method, we tested the malware classification technique used by MalDC on a dataset provided by Microsoft and malware data collected by the Korea Internet & Security Agency (KISA). Consequently, an accuracy of 97% was achieved.

• Spatial Information Research
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• v.22 no.6
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• pp.45-54
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• 2014

Establishment of safety net for the socially disadvantaged attracts large attention because of the recent crime increasing against vulnerable groups. For the successful establishment of social safety net, the test-bed for evaluation and realization of crime-related research results is required. However, previous R&D test-bed projects such as The Korean Land Specialization Program or U-Eco City project remains only to the stage of verification. Therefore, there are limitedness for realization of result technologies or sustainable operation & management of test-bed after projects finished. So, sustainable operation & management system and guideline of test-bed are necessary. Therefore, this study reviews the strengths and weaknesses of existing test-bed cases and intelligent security researches. After reviewing, the concept of a Intelligent Security Test-bed is established and appropriate test-bed selection criteria is also suggested. Based on objective criteria, selected test-bed can achieve sustainable management even after finishing the project and contribute the construction of standard model for citizen's safety.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.163-171
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• 2023

The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.