• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.517-520
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• 2008

Wireless sensor network supporting healthcare environment should provide customized service in accordance with context information such as continuous location change and status information for people or movable object. In addition, we should consider data transmission guarantees a person's bio information and privacy security provided through sensor network. In this paper analyzes LEACH protocol which guarantees the dynamic self-configuration, energy efficiency through configuration of inter-node hierarchical cluster between nodes and key distribution protocol used for security for data transmission between nodes. Based on this analysis result, we suggested self-configuration routing protocol supporting node mobility which is weakness of the existing LEACH protocol and data transmission method by applying key-pool pre-distribution method whose memory consumption is low, cluster unit public key method to sensor node.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.726-735
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• 2009

In this paper, we proposed a novel conditional access system to reduce the overhead transmission rate for messages which verify the entitlement of subscribers in bandwidth-limited system. We adapted a key update system with the tree structure which had been used for IP multicast to a group hierarchy for the subscriber groups or channel groups. We also analyzed the overhead transmission rate for periodic key update and aperiodic one for change in a subscriber. The numerical evaluations show that the proposed system can significantly reduce the overhead transmission rate for dynamic subscriber change up to several hundred thousands times for various system configuration.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.161-166
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• 2023

In recent years, new and variant hacking of binary codes has increased, and the limitations of techniques for detecting malicious codes in source programs and defending against attacks are often exposed. Advanced software security vulnerability detection technology using machine learning and deep learning technology for binary code and defense and response capabilities against attacks are required. In this paper, we propose a malware clustering method that groups malware based on the characteristics of the taint information after entering dynamic taint information by tracing the execution path of binary code. Malware vulnerability detection was applied to a three-layered Few-shot learning model, and F1-scores were calculated for each layer's CPU and GPU. We obtained 97~98% performance in the learning process and 80~81% detection performance in the test process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1060-1070
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• 2022

With the development of information technology, the size of the system has become larger and diversified, and the existing role-based access control has faced limitations. Blockchain technology is being used in various fields by presenting new solutions to existing security vulnerabilities. This paper suggests efficient role-based access control in a blockchain where the required gas and processing time vary depending on the access frequency and capacity of the storage. The proposed method redefines the role of reusable units, introduces a hierarchical structure that can efficiently reflect dynamic states to enhance efficiency and scalability, and includes user-centered authentication functions to enable cryptocurrency linkage. The proposed model was theoretically verified using Markov chain, implemented in Ethereum private network, and compared experiments on representative functions were conducted to verify the time and gas efficiency required for user addition and transaction registration. Based on this in the future, structural expansion and experiments are required in consideration of exception situations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.143-151
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• 2011

When a real-time data transfer is not possible between a reader and a back-end server in the mobile environment, the reader should support a capability to search a certain tag without communicating with a back-end server. Some recent papers related to the mobile reader-based tag search protocol have addressed privacy concerns for the reader and the tags. However, to our best knowledge, there are no papers addressing the problem arising from reusing tag lists existed in the mobile reader. In other words, there arise a problem that a mobile reader which has lost an right to access to a specific tag is able to search that tag by reusing a tag list for searching a particular tag. If mobile reader having an unauthorized tag list, the mobile reader can reuse a particular tag list. Our protocol provides the enhanced secure tag lists preventing the reuse of the tag lists and an efficient tag search protocol based on dynamic identity in the mobile reader-based RFID environments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.779-791
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• 2021

Common web services have been continuously targeted by hackers due to an access control policy that must be allowed to an unspecified number of people. In order to cope with this situation, companies regularly check web vulnerabilities and take measures according to the risk of discovered vulnerabilities. The risk of these web vulnerabilities is calculated through preliminary statistics and self-evaluation of domestic and foreign related organizations. However, unlike static diagnosis such as security setting and source code, web vulnerability check is performed through dynamic diagnosis. Even with the same vulnerability item, various attack results can be derived, and the degree of risk may vary depending on the subject of diagnosis and the environment. In this respect, the predefined risk level may be different from that of the actual vulnerability. In this paper, to improve this point, we present a web vulnerability risk assessment model based on the attack result centering on the cyber kill chain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.458-460
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• 2021

The provision and application of public safety network in Korea is still insufficient for security response to the mobile app of public safety network in the stages of development, initial construction, demonstration, and initial service. The available terminals on the Disaster Safety Network (PS-LTE) are open, Android-based, dedicated terminals that potentially have vulnerabilities that can be used for a variety of mobile malware, requiring preemptive responses similar to FirstNet Certified in U.S and Google's Google Play Protect. In this paper, before listing the application service app on the public safety network mobile app store, we construct a data set for malicious and normal apps, extract features, select the most effective AI model, perform static and dynamic analysis, and analyze Based on the result, if it is not a malicious app, it is suggested to list it in the App Store. As it becomes essential to provide a service that blocks malicious behavior app listing in advance, it is essential to provide authorized authentication to minimize the security blind spot of the public safety network, and to provide certified apps for disaster safety and application service support. The safety of the public safety network can be secured.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2A
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• pp.79-85
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• 2006

Generally, it is essential that high-speed routers, switches, and network security appliances should have an efficient packet classification scheme in order to achieve the high-speed packet forwarding capability. For the multi-gigabit packet-processing network equipment the high-speed content search hardware such as TCAM and search engine is recently used to support the content-based packet inspection. During the packet classification process, hundreds and thousands of rules are applied to provide the network security policies regarding traffic screening, traffic monitoring, and traffic shaping. In addition, these rules could be dynamically changed during operations of systems if anomaly traffic patterns would vary. Particularly, in the high-speed network, an efficient algorithm that updates and reorganizes the packet classification rules is critical so as not to degrade the performance of the network device. In this paper, we have proposed an efficient update algorithm using a partial-ordering that can relocate the dynamically changing rules at the TCAM. Experimental results should that our algorithm does not need to relocate existing rules feature until 70$\%$ of TCAM utilization.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.