• The Journal of Bigdata
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• v.7 no.1
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• pp.1-14
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• 2022

The proof-of-work consensus algorithm used by most blockchains is causing a massive waste of computing resources in the form of mining. A useful proof-of-work consensus algorithm has been studied to reduce the waste of computing resources in proof-of-work, but there are still resource waste and mining centralization problems when creating blocks. In this paper, the problem of resource waste in block generation was solved by replacing the relatively inefficient computation process for block generation with distributed artificial intelligence model learning. In addition, by providing fair rewards to nodes participating in the learning process, nodes with weak computing power were motivated to participate, and performance similar to the existing centralized AI learning method was maintained. To show the validity of the proposed methodology, we implemented a blockchain network capable of distributed AI learning and experimented with reward distribution through resource verification, and compared the results of the existing centralized learning method and the blockchain distributed AI learning method. In addition, as a future study, the thesis was concluded by suggesting problems and development directions that may occur when expanding the blockchain main network and artificial intelligence model.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.165-170
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• 2023

With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.9-21
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• 2004

In this paper, we proposed the image hiding method which decreases calculation amount by encrypt partial data using discrete wavelet transform and linear scale quantization which were adopted as the main technique for frequency transform in JPEG2000 standard. Also we used the chaotic system which has smaller calculation amount than other encryption algorithms and then dramatically decreased calculation amount. This method operates encryption process between quantization and entropy coding for preserving compression ratio of images and uses the subband selection method and the random changing method using the chaotic system. For ciphering the quantization index we use a novel image encryption algerian of cyclically shifted in the right or left direction and encrypts two quantization assignment method (Top-down/Reflection code), made change of data less. Also, suggested encryption method to JPEG2000 progressive transmission. The experiments have been performed with the proposed methods implemented in software for about 500 images. consequently, we are sure that the proposed are efficient image encryption methods to acquire the high encryption effect with small amount of encryption. It has been shown that there exits a relation of trade-off between the execution time and the effect of the encryption. It means that the proposed methods can be selectively used according to the application areas. Also, because the proposed methods are performed in the application layer, they are expected to be a good solution for the end-to-end security problem, which is appearing as one of the important problems in the networks with both wired and wireless sections.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.377-391
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• 2019

Recently, system studies using tokens and block chains for authentication, access control, etc in IoT environment have been going on at home and abroad. However, existing token-based systems are not suitable for IoT environments in terms of security, reliability, and scalability because they have centralized characteristics. In addition, the system using the block chain has to overload the IoT device because it has to repeatedly perform the calculation of the hash et to hold the block chain and store all the blocks. In this paper, we intend to manage the access rights through tokens for proper access control in the IoT. In addition, we apply the Tangle to configure the P2P distributed ledger network environment to solve the problem of the centralized structure and to manage the token. The authentication process and the access right grant process are performed to issue a token and share a transaction for issuing the token so that all the nodes can verify the validity of the token. And we intent to reduce the access control process by reducing the repeated authentication process and the access authorization process by reusing the already issued token.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.91-98
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• 2021

Today's information and communication technology is rapidly developing, the security of IT infrastructure is becoming more important, and at the same time, cyber attacks of various forms are becoming more advanced and sophisticated like intelligent persistent attacks (Advanced Persistent Threat). Early defense or prediction of increasingly sophisticated cyber attacks is extremely important, and in many cases, the analysis of network-based intrusion detection systems (NIDS) related data alone cannot prevent rapidly changing cyber attacks. Therefore, we are currently using data generated by intrusion detection systems to protect against cyber attacks described above through Host-based Intrusion Detection System (HIDS) data analysis. In this paper, we conducted a comparative study on machine learning algorithms using LID-DS (Leipzig Intrusion Detection-Data Set) host-based intrusion detection data including thread information, metadata, and buffer data missing from previously used data sets. The algorithms used were Decision Tree, Naive Bayes, MLP (Multi-Layer Perceptron), Logistic Regression, LSTM (Long Short-Term Memory model), and RNN (Recurrent Neural Network). Accuracy, accuracy, recall, F1-Score indicators and error rates were measured for evaluation. As a result, the LSTM algorithm had the highest accuracy.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.27-40
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• 2004

The OSGi service platform has several characteristics as in the followings. First, the service is deployed in the form of self-installable component called service bundle. Second, the service is dynamic according to its life-cycle and has interactions with other services. Third, the system resources of a home gateway are restricted. Due to these characteristics of a home gateway, there are a lot of rooms for malicious services can be Installed, and further, the nature of service can be changed. It is possible for those service bundles to influence badly on service gateways and users. However, there is no service bundle authentication mechanism considering those characteristics for the home gateway In this paper, we propose a service bundle authentication mechanism considering those characteristics for the home gateway environment. We design the mechanism for sharing a key which transports a service bundle safely in bootstrapping step that recognize and initialize equipments. And we propose the service bundle authentication mechanism based on MAC that use a shared secret created in bootstrapping step. Also we verify the safety of key sharing mechanism and service bundle authentication mechanism using a BAN Logic. This service bundle authentication mechanism Is more efficient than PKI-based service bundle authentication mechanism or RSH protocol in the service platform which has restricted resources such as storage spaces and operations.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.12-21
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• 2012

IEEE 802.11 MAC protocol standard, DCF(CSMA/CA), is originally designed to ensure the fair channel access between mobile nodes sharing the local wireless channel. It has been, however, revealed that some misbehavior nodes transmit more data than other nodes through artificial means in hot spot area spreaded rapidly. The misbehavior nodes may modify the internal process of their MAC protocol or interrupt the MAC procedure of normal nodes to achieve more data transmission. This problem has been referred to as a selfish node problem and almost literatures has proposed methods of analyzing the MAC procedures of all mobile nodes to detect the selfish nodes. However, these kinds of protocol analysis methods is not effective at detecting all kinds of selfish nodes enough. This paper address this problem of detecting selfish node using Tsallis-Entropy which is a kind of statistical method. Tsallis-Entropy is a criteria which can show how much is the density or deviation of a probability distribution. The proposed algorithm which operates at a AP node of wireless LAN extracts the probability distribution of data interval time for each node, then compares the one with a threshold value to detect the selfish nodes. To evaluate the performance of proposed algorithm, simulation experiments are performed in various wireless LAN environments (congestion level, how selfish node behaviors, threshold level) using ns2. The simulation results show that the proposed algorithm achieves higher successful detection rate.

• Journal of Convergence for Information Technology
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• v.10 no.11
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• pp.55-63
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• 2020

The IoT technology is a field that applies and converges the technologies in the existing industrial environment, instead of new technologies. The IoT technology is releasing various application services converged with other industries such as smart home, healthcare, construction, and automobile, and it is also possible to secure the work efficiency and convenience of users of IoT-based technologies. However, the security threats occurring in the IoT-based technology environment are succeeding to the vulnerability of the existing wireless network environment. And the occurrence of new and variant attacks in the combination with the ICT convergence environment, is causing damages. Thus, in the IoT technology-based environment, it would be necessary to have researches on the safe transmission of messages in the communication environment between user and device, and device and device. This thesis aims to design a safe communication protocol in the IoT-based technology environment. Regarding the suggested communication protocol, this thesis performed the safety analysis on the attack techniques occurring in the IoT technology-based environment. And through the performance evaluation of the existing PKI-based certificate issuance system and the suggested communication protocol, this thesis verified the high efficiency(about 23%) of communication procedure. Also, this thesis verified the reduced figure(about 65%) of the issued quantity of certificate compared to the existing issuance system and the certificate management technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.504-509
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• 2019

Recently, both wireless communications technology and the performance of small devices have developed exponentially, while the number of services using various types of Internet of Things (IoT) devices has also massively increased in line with the ongoing technological and environmental changes. Furthermore, ever more devices that were previously used in the offline environment-including small-size sensors and CCTV-are being connected to the Internet due to the huge increase in IoT services. However, many IoT devices are not equipped with security functions, and use vulnerable open source software as it is. In addition, conventional network equipment, such as switches and gateways, operates with vulnerabilities, because users tend not to update the equipment on a regular basis. Recently, the simple vulnerability of IoT devices has been exploited through the distributed denial of service (DDoS) from attackers creating a large number of botnets. This paper proposes a system that is capable of identifying Internet-connected devices quickly, analyzing and managing the vulnerability of such devices using Internet-wide scan technology. In addition, the vulnerability analysis rate of the proposed technology was verified through collected banner information. In the future, the company plans to automate and upgrade the proposed system so that it can be used as a technology to prevent cyber attacks.