• Journal of Korean Society of Water and Wastewater
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• v.32 no.2
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• pp.193-200
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• 2018

Owing to the development in information and communications technologies have improved the technology for high-speed transmission of massive data, which has changed closed-circuit television (CCTV) video transmission technology. In particular, digitization of the CCTV video format and streaming technology has made it possible to minimize transmission loss and integrate video transmission and camera control(pan/tilt). It has also become possible to provide additional services like remote emergency warning broadcasting with just Internet Protocol (IP). However, because of the structural problems of IP, these changes have also brought about the threat of hacking of CCTV monitoring systems. In this study, we propose a methode to optimize network management by examining cases of enhancement of operational efficiency and security by improving the structure of CCTV monitoring network.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.94-99
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• 2016

Application layer attacks have for years posed an ever-serious threat to network security, since they always come after a technically legitimate connection has been established. In recent years, cyber criminals have turned to fully exploiting the web as a medium of communication to launch a variety of forbidden or illicit activities by spreading malicious automated software (auto-ware) such as adware, spyware, or bots. When this malicious auto-ware infects a network, it will act like a robot, mimic normal behavior of web access, and bypass the network firewall or intrusion detection system. Besides that, in a private and large network, with huge Hypertext Transfer Protocol (HTTP) traffic generated each day, communication behavior identification and classification of auto-ware is a challenge. In this paper, based on a previous study, analysis of auto-ware communication behavior, and with the addition of new features, a method for classification of HTTP auto-ware communication is proposed. For that, a Not Only Structured Query Language (NoSQL) database is applied to handle large volumes of unstructured HTTP requests captured every day. The method is tested with real HTTP traffic data collected through a proxy server of a private network, providing good results in the classification and detection of suspicious auto-ware web access.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1447-1454
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• 2012

Recently P2P is the most popular network service on Internet and is applied various areas such as streaming, file sharing and software distribution, but there are many security threats depending on vulnerabilities by P2P network environments. Conceptually P2P network is a overlay network based on Internet, and it has security concerns of itself as well as those of Internet environments. In this paper, we analyze the vulnerabilities and threats for domestic P2P services through various experiments and describe their risk analysis. We expect that this work contributes to new domestic P2P services in consideration of service qualities and security vulnerabilities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.1
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• pp.23-34
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• 2022

With the development of network technology, the application area has also been diversified, and protocols for various purposes have been developed and the amount of traffic has exploded. Therefore, it is difficult for the network administrator to meet the stability and security standards of the network with the existing traditional switching and routing methods. Software Defined Networking (SDN) is a new networking paradigm proposed to solve this problem. SDN enables efficient network management by programming network operations. This has the advantage that network administrators can flexibly respond to various types of attacks. In this paper, we design a threat level management module, an attack detection module, a packet statistics module, and a flow rule generator that collects attack information through the controller and switch, which are components of SDN, and detects attacks based on these attributes of SDN. It proposes a method to block denial of service attacks (DoS) of advanced attackers by programming and applying honeypot. In the proposed system, the attack packet can be quickly delivered to the honeypot according to the modifiable flow rule, and the honeypot that received the attack packets analyzed the intelligent attack pattern based on this. According to the analysis results, the attack detection module and the threat level management module are adjusted to respond to intelligent attacks. The performance and feasibility of the proposed system was shown by actually implementing the proposed system, performing intelligent attacks with various attack patterns and attack levels, and checking the attack detection rate compared to the existing system.

• Journal of IKEEE
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• v.22 no.1
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• pp.162-167
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• 2018

In this paper, we propose a method to classify radar signals according to the jamming technique by applying the machine learning to parameter data extracted from received radar signals. In the present army, the radar signal is classified according to the type of threat based on the library of the radar signal parameters mostly built by the preliminary investigation. However, since radar technology is continuously evolving and diversifying, it can not properly classify signals when applying this method to new threats or threat types that do not exist in existing libraries, thus limiting the choice of appropriate jamming techniques. Therefore, it is necessary to classify the signals so that the optimal jamming technique can be selected using only the parameter data of the radar signal that is different from the method using the existing threat library. In this study, we propose a method based on machine learning to cope with new threat signal form. The method classifies the signal corresponding the new jamming method for the new threat signal by learning the classifier composed of the hidden Markov model and the neural network using the existing library data.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.33-47
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• 2020

In recent years, due to the demand for operating efficiency and cost reduction of industrial facilities, remote access via the Internet is expanding. the control network accelerates from network separation to network connection due to the development of IIoT (Industrial Internet of Things) technology. Transition of control network is a new opportunity, but concerns about cybersecurity are also growing. Therefore, manufacturers must reflect security compliance and standards in consideration of the Internet connection environment, and enterprises must newly recognize the connection area of the control network as a security management target. In this study, the core target of the control system security threat is defined as the network boundary, and issues regarding the security architecture configuration for the boundary and the role & responsibility of the working organization are covered. Enterprises do not integrate the design organization with the operation organization after go-live, and are not consistently reflecting security considerations from design to operation. At this point, the expansion of the control network is a big transition that calls for the establishment of a responsible organization and reinforcement of the role of the network boundary area where there is a concern about lack of management. Thus, through the organization of the facility network and the analysis of the roles between each organization, an static perspective and difference in perception were derived. In addition, standards and guidelines required for reinforcing network boundary security were studied to address essential operational standards that required the Internet connection of the control network. This study will help establish a network boundary management system that should be considered at the enterprise level in the future.

• Convergence Security Journal
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• v.6 no.3
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• pp.21-28
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• 2006

Beginning flag security it was limited in Firewall but currently many information security solutions like Anti-virus, IDS, Firewall are come to be many. For efficiently managing different kinds of information security products ESM (Enterprise Security management) are developed and operated. Recently over the integrated security management system, TMS (Threat Management System) is rising in new area of interest. It follows in change of like this information security product and also collection information is being turning out diversification. For managing cyber threats, we have to analysis qualitative information (like vulnerabilities and malware codes, security news) as well as the quantity event logs which are from information security products of past. Information Threats and Vulnerability Auto Collector raises the accuracy of cyber threat judgement and can be utilized to respond the cyber threat which does not occur still by gathering qualitative information as well as quantity information.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.55-62
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• 2018

Recently, as the threat of cyber crime increases, the importance of security control to cope with cyber attacks on the information systems in the first place such as real-time detection is increasing. In the name of security control center, cyber terror response center and infringement response center, institutional control personnel are making efforts to prevent cyber attacks. Especially, we are detecting infringement accident by using network security equipment or utilizing control system, but it's not enough to prevent infringement accident by just controlling based on device-driven simple patterns. Therefore, the security control system is continuously being upgraded, and the development and research on the detection method are being actively carried out by the prevention activity against the threat of infringement. In this paper, we have defined the method of detecting infringement of major component module in order to improve the problem of existing infringement detection method. Through the performance tests for each module, we propose measures for effective security control and study effective infringement threat detection method by upgrading the control system using Security Information Event Management (SIEM).