• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.631-634
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• 2002

Video conference system has guided swiftness of information transmission and business processing taking away time and manufacturing drug of space that is happened that long-distance gather and talk. But, leakage of important meeting content, peculation etc., in that execute video-conferences can happen. Therefore, research about video conference system of safety is progressing under secure superhigh speed information communication fetters. This treatise studied about techniques to encipher videotex to prevent variation and outward flow of burn information, peculation etc., except general encryption notation such as user certification to have drawn problem about stability of general video conference system, and is used present as countermeasure about here. Used improved Vernam's encryption techniques to encrypt videotex.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.12
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• pp.1355-1360
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• 2015

Recently MANET application is diversified studies on the MANET routing security and the reliable authentication mechanism is actively in progress. Stand-alone network structure of a MANET is an important field of ubiquitous computing environment of interest, Authentication techniques are already provided safety when applied to MANET reliability and efficiency in a secure authentication mechanism using the session key. However, most of the MANET environment, the model has been based on the assumption that the safety is guaranteed, When applied to an actual network situation, we can not rule out a variety of threats. This study is the testing and analysis to add the malicious node extracted at random to demonstrate the safety and efficacy of the session key certification techniques of the MANET environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4889-4908
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• 2020

With the advances in Information Technology (IT), users can download or stream copyrighted works, such as videos, music, and webtoons, at their convenience. Thus, the frequency of use of copyrighted works has increased. Consequently, the number of unauthorized copies and sharing of copyrighted works has also increased. Monitoring is being conducted on sites suspected of conducting copyright infringement activities to reduce copyright holders' damage due to unauthorized sharing of copyrighted works. However, suspected copyright infringement sites respond by changing their domains or blocking access requests. Although research has been conducted for improving the effectiveness of suspected copyright infringement site detection by defining suspected copyright infringement sites' response techniques as a lifecycle step, there is a paucity of studies on automation techniques for lifecycle detection. This has reduced the accuracy of lifecycle step detection on suspected copyright infringement sites, which change domains and lifecycle steps in a short period of time. Thus, in this paper, an automated detection technique for suspected copyright infringement sites is proposed for efficient detection and response to suspected copyright infringement sites. Using our proposed technique, the response to each lifecycle step can be effectively conducted by automatically detecting the lifecycle step.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4537-4556
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• 2020

This research was based on the study conducted by Khodaei et al. (2012), namely, the least-significant-bit (LSB) substitution combined with the pixel-value differencing (PVD) steganography, and presented an improved irreversible image steganography method. Such a method was developed through integrating the improved LSB substitution with the modulus function-based PVD steganography to increase steganographic capacity of the original technique while maintaining the quality of images. It partitions the cover image into non-overlapped blocks, each of which consists of 3 consecutive pixels. The 2nd pixel represents the base, in which secret data are embedded by using the 3-bit LSB substitution. Each of the other 2 pixels is paired with the base respectively for embedding secret data by using an improved modulus PVD method. The experiment results showed that the method can greatly increase steganographic capacity in comparison with other PVD-based techniques (by a maximum amount of 135%), on the premise that the quality of images is maintained. Last but not least, 2 security analyses, the pixel difference histogram (PDH) and the content-selective residual (CSR) steganalysis were performed. The results indicated that the method is capable of preventing the detection of the 2 common techniques.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.163-169
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• 2022

In this paper, we propose a data hiding technique that effectively hides confidential data in the LSB of an image pixel by using the characteristics of the neighboring pixels of the image and the encryption techniques. In the proposed technique, the boundary surface of the image and the flat surface with little change in pixel values are investigated. At the boundary surface of the image, 1 bit of confidential data is encrypted and hidden in the LSB of the boundary pixel to preserve the characteristics of the boundary surface. In the pixels of the plane where the change in pixel value is small, 2 bits secret data is encrypted and hidden in the lower 2 bits of the corresponding pixel. In this way, when confidential data is hidden in an image, the amount of confidential data hidden in the image is greatly increased while maintaining excellent image quality. In addition, the security of hidden confidential data is strongly maintained. When confidential data is hidden by applying the proposed technique, the amount of confidential data concealed increases by up to 92.2% compared to the existing LSB method. The proposed technique can be effectively used to hide copyright information in commercial images.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1119-1127
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• 2018

Most of the cyber attacks are caused by malicious codes. The damage caused by cyber attacks are gradually expanded to IoT and CPS, which is not limited to cyberspace but a serious threat to real life. Accordingly, various malicious code analysis techniques have been appeared. Dynamic analysis have been widely used to easily identify the resulting malicious behavior, but are struggling with an increase in Anti-VM malware that is not working in VM environment detection. On the other hand, static analysis has difficulties in analysis due to various packing techniques. In this paper, we proposed malware classification techniques regardless of known packers or unknown packers through the proposed model. To do this, we designed a model of supervised learning and unsupervised learning for the features that can be used in the PE structure, and conducted the results verification through 98,000 samples. It is expected that accurate analysis will be possible through customized analysis technology for each class.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.1-8
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• 2018

Extreme climate phenomena are occurring around the world caused by global climate change. The heavy rains exceeds the previous record of highest rainfall. In particular, as flash floods generate heavy rainfall on the mountains over a relatively a short period of time, the likelihood of landslides increases. Gangwon region is especially suffered by landslide damages, because the most of the part is mountainous, steep, and having shallow soil. Therefore, in this study, is to predict the risk of disasters by applying topographic classification techniques and landslide risk prediction techniques to mountain watersheds. Classify the hazardous area by calculating the topographic position index (TPI) as a topographic classification technique. The SINMAP method, one of the earth rock predictors, was used to predict possible areas of a landslide. Using the SINMAP method, we predicted the area where the mountainous disaster can occur. As a result, the topographic classification technique classified more than 63% of the total watershed into open slope and upper slope. In the SINMAP analysis, about 58% of the total watershed was analyzed as a hazard area. Due to recent developments, measures to reduce mountain disasters are urgently needed. Stability measures should be established for hazard zone.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.101-106
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• 2023

In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.973-980
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• 2024

Fuzzing is an automated testing technique that generates a lot of testcases and monitors for exceptions to test a program. Recently, fuzzing research using machine learning has been actively proposed to solve various problems in the fuzzing process, but a comprehensive evaluation of fuzzing research using machine learning is lacking. In this paper, we analyze recent research that applies machine learning to scheduling techniques for fuzzing, categorizing them into reinforcement learning-based and supervised learning-based fuzzers. We evaluated the coverage performance of the analyzed machine learning-based fuzzers against real-world programs with four different file formats and bug detection performance against the LAVA-M dataset. The results showed that AFL-HIER, which applied seed clustering and seed scheduling with reinforcement learning outperformed in coverage and bug detection. In the case of supervised learning, it showed high coverage on tcpdumps with high code complexity, and its superior bug detection performance when applied to hybrid fuzzing. This research shows that performance of machine learning-based fuzzer is better when both machine learning and additional fuzzing techniques are used to optimize the fuzzing process. Future research is needed on practical and robust machine learning-based fuzzing techniques that can be effectively applied to programs that handle various input formats.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.86-95
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• 2011

Sensor nodes in wireless sensor networks are vulnerable to security than wired network due to using limited hardware performance and wireless communications that network topology changes frequently. Among techniques to enhance the security, the node authentication mechanism is used to defend against data forgery attacks using the ID of the node or to interfere with the routing of the network routing. In this paper, we proposed the AM-E mechanism that makes authentication key by using the energy value of node requesting authentication and performs the communication procedures for data transfer between different nodes. Because the energy value of node is changed depending on time, every time the authentication request is, an authentication key is changed. These features enhance the security of sensor networks and will help to configure the more secure WSN.