• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.323-330
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• 2021

Recently, the advantages of high-speed arithmetic in quantum computers have been known, and interest in quantum circuits utilizing qubits has increased. The Grover algorithm is a quantum algorithm that can reduce n-bit security level symmetric key cryptography and hash functions to n/2-bit security level. Since the Grover algorithm work on quantum computers, the symmetric cryptographic technique and hash function to be applied must be implemented in a quantum circuit. This is the motivation for these studies, and recently, research on implementing symmetric cryptographic technique and hash functions in quantum circuits has been actively conducted. However, at present, in a situation where the number of qubits is limited, we are interested in implementing with the minimum number of qubits and aim for efficient implementation. In this paper, the domestic hash function LSH is efficiently implemented using qubits recycling and pre-computation. Also, major operations such as Mix and Final were efficiently implemented as quantum circuits using ProjectQ, a quantum programming tool provided by IBM, and the quantum resources required for this were evaluated.

• Convergence Security Journal
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• v.17 no.3
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• pp.31-40
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• 2017

UAV (Unmanned Aerial Vehicle) is increasingly used in diverse fields such as disaster, distributi on, and logistics, but it is pointed out that the inadequacy of related laws and invasion of privacy is an obstacle to industrial growth. The regulatory framework for UAV convergence services is pr oposed based on the regulatory framework. From the technical point of view, regulation on archite ctural design, from the market point of view, concurrent operation of services in a limited area, a l egal evaluation based on post-evaluation rather than a pre-regulation under the legislation of visua l information protection law and a social consensus will contribute to the early settlement of UAV -based convergence services.

• Convergence Security Journal
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• v.21 no.1
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• pp.121-127
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• 2021

MANET, which does not have any infrastructure other than wireless nodes, has the advantage of being able to construct a fast network. However, the movement of nodes and wireless media are also the causes of security vulnerabilities of MANET. In particular, the damage caused by the attacking nodes existing on the network is considerably greater than that of other networks. Therefore, it is necessary to detection technique for attacking nodes and techniques to reduce damage caused by attacks. In this paper, we proposed a hierarchical structure technique to increase the efficiency of intrusion detection and collaboration-based intrusion detection technique applying a P2P mesh network configuration technique to reduce damage caused by attacks. There was excluded the network participation of the attacking node in advance through the reliability evaluation of the nodes in the cluster. In addition, when an attack by an attacking node is detected, this paper was applied a method of minimizing the damage of the attacking node by transmitting quickly the attack node information to the global network through the P2P mesh network between cluster heads. The ns-2 simulator was used to evaluate the performance of the proposed technique, and the excellent performance of the proposed technique was confirmed through comparative experiments.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.39-47
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• 2009

Recently, the threat of DDoS attacks is increasing and many companies are planned to deploy the DDoS defense solutions in their networks. The DDoS attack usually transmits heavy traffic data to networks or servers and they cannot handle the normal service requests because of running out of resources. Since it is very hard to prevent the DDoS attack beforehand, the strategic plan is very important. In this work, we have conducted modeling and simulation of the DDoS attack by changing the number of servers and estimated the duration that services are available. In this work, the modeling and simulation is conducted using OPNET Modeler. The simulation result can be used as a parameter of trade-off analysis of DDoS defense cost and the service's value. In addition, we have presented a way of estimating the cost effectiveness in deployment of the DDoS defense system.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.165-184
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• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.640-654
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• 2021

Purpose: Normal education operation was difficult in the national disaster situation of Coronavirus Infection-19. Non-face-to-face education can be an alternative to face to face education, but it is not easy to provide the same level of education. In this study, the professor of disaster management field will identify problems that can occur in the overall operation and progress of non-face-to-face education and seek ways to improve non-face-to-face education. Method: Non-face-to-face real-time education was largely categorized into pre-class, in-class, post-class, and evaluation, and case studies were conducted through the professor's case studies. Result&Conclusion: The results of the survey are as follows: First, pre-class, it was worth considering providing a non-face-to-face educational place for professors, and the need for prior education on non-face-to-face educational equipment and systems was required. In addition, it seems necessary to make sure that education is operated smoothly by giving enough notice on classes and to make efforts to develop non-face-to-face education programs for practical class. Second, communication between professor and learner, and among learners can be an important factor in non-face-to-face mid classes. To this end, it is necessary to actively utilize debate-type classes to lead learners to participate in education and enhance the educational effect through constant interaction. Third, non-face-to-face post classes, policies on the protection of privacy due to video records should be prepared to protect the privacy of professors in advance, and copyright infringement on educational materials should also be considered. In addition, it is necessary to devise various methods for fair and objective evaluation. According to the results of the interview, in the contents, which are components of non-face-to-face education, non-face-to-face education requires detailed plans on the number of students, contents, and curriculum suitable for non-face-to-face education from the design of the education. In the system, it is necessary to give the professor enough time to fully learn and familiarize with the function of the program through pre-education on the program before the professor gives non-face-to-face classes, and to operate the helpdesk, which can thoroughly check the pre-examination before non-face-to-face education and quickly resolve the problem in case of a problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.636-645
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• 2008

Most of routing schemes that protect the source's location from a malicious attacker usually make use of a path of a long length per message for the sake of lengthening the safety period. The biggest problem to such approaches is taking a very long latency in transferring messages to the destination. In this paper we show the problem to find the least-cost single path that is enough to keep the source-location always secure from the attacker, provided that it is used for the delivery of a set of messages given in priori, is NP-complete. Consequently we propose a routing protocol GSLP-w(GPSR-based Source-Location Privacy with crew size co) that is a trade-off between two extreme approaches. The advantage of GSLP-co lies in its enhanced safety period for the source and its lowered delivery latency in messaging. We consider NSP(Normalized Sefety Period) and NDL(Normalized Delivery Latency), measured in terms of the least number of hops to the destination, to achieve tangible interpretation of the results. We ran a simulation to confirm our claim by generating 100 topologies of 50,000 nodes with the average number of neighbors being 8. The results show that GSLP-$\omega$ provides more enhanced NSP compared to other protocols GSLP, an earlier version of GSLP-$\omega$, and PR-SP(Phantom Routing - Single Path), the most notable existing protocol for the source-location privacy, and less NDL than that of GSLP but more than that of PR-SP.

• Journal of Convergence for Information Technology
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• v.8 no.2
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• pp.77-82
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• 2018

Recently, as cloud services become popular with general users, users' information is freely transmitted and received among the information used in the cloud environment, so security problems related to user information disclosure are occurring. we propose a method to secure personal information of multiple users by making personal information stored in the cloud server and a key for accessing the shared information so that the privacy information of the multi users using the cloud service can be prevented in advance do. The first key used in the proposed scheme is a key for accessing the user 's personal information, and is used to operate the information related to the personal information in the form of a multi - layer. The second key is the key to accessing information that is open to other users than to personal information, and is necessary to associate with other users of the cloud. The proposed scheme is constructed to anonymize personal information with multiple hash chains to process multiple kinds of information used in the cloud environment. As a result of the performance evaluation, the proposed method works by allowing third parties to safely access and process the personal information of multiple users processed by the multi - type structure, resulting in a reduction of the personal information management cost by 13.4%. The efficiency of the proposed method is 19.5% higher than that of the existing method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.2
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• pp.79-89
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• 2009

For preliminary diagnosis on current fishing ground environment and basic information for establishment of effective and rational management policy in fisheries resources protection area, water and sediment quality and changes of total area in the 10 marine protection areas designated for fisheries resources management in Korea were assessed. Results showed that environmental quality in these areas has been degraded by pollution sources, coastal utilization and development stress, etc. The pattern and degree of contamination differed by protection areas, suggesting that it is necessary for optimum environmental management plan considering the regional characteristics. The total designated area of protection areas in 2003 changed by $-22.9{\sim}2.4%$, on average -6.4%, compared with the first year of designation; Wando-Doam Bay showd the highest increase rate (2.4%), and Hansan Bay has the highest decrease rate (-22.9%) Decrease rate of land and sea in total area showd 6.1% and 6.6%. An integrated management of environmental data in protection areas is required for systematic assessment. Therefore, the suitable environmental and information management is needed specifically considering the environment characteristics such as development and utilization conditions of land and sea area Furthermore, bemuse urbanization and industrialization threats the junctions of the protection areas, authorized ministry (MIFAFF) should develope and establish monitoring and management procedures based on the related laws.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.439-449
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• 2024

Recent rapid advancements in voice generation technology have enabled the natural synthesis of voices using text alone. However, this progress has led to an increase in malicious activities, such as voice phishing (voishing), where generated voices are exploited for criminal purposes. Numerous models have been developed to detect the presence of synthesized voices, typically by extracting features from the voice and using these features to determine the likelihood of voice generation.This paper proposes a new model for extracting voice features to address misuse cases arising from generated voices. It utilizes a deep learning-based audio codec model and the pre-trained natural language processing model BERT to extract novel voice features. To assess the suitability of the proposed voice feature extraction model for voice detection, four generated voice detection models were created using the extracted features, and performance evaluations were conducted. For performance comparison, three voice detection models based on Deepfeature proposed in previous studies were evaluated against other models in terms of accuracy and EER. The model proposed in this paper achieved an accuracy of 88.08%and a low EER of 11.79%, outperforming the existing models. These results confirm that the voice feature extraction method introduced in this paper can be an effective tool for distinguishing between generated and real voices.