• Title/Summary/Keyword: 개인 컴퓨터 보안

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Design and Implementation of HDFS Data Encryption Scheme Using ARIA Algorithms on Hadoop (하둡 상에서 ARIA 알고리즘을 이용한 HDFS 데이터 암호화 기법의 설계 및 구현)

  • Song, Youngho;Shin, YoungSung;Chang, Jae-Woo
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.2
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    • pp.33-40
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    • 2016
  • Due to the growth of social network systems (SNS), big data are realized and Hadoop was developed as a distributed platform for analyzing big data. Enterprises analyze data containing users' sensitive information by using Hadoop and utilize them for marketing. Therefore, researches on data encryption have been done to protect the leakage of sensitive data stored in Hadoop. However, the existing researches support only the AES encryption algorithm, the international standard of data encryption. Meanwhile, Korean government choose ARIA algorithm as a standard data encryption one. In this paper, we propose a HDFS data encryption scheme using ARIA algorithms on Hadoop. First, the proposed scheme provide a HDFS block splitting component which performs ARIA encryption and decryption under the distributed computing environment of Hadoop. Second, the proposed scheme also provide a variable-length data processing component which performs encryption and decryption by adding dummy data, in case when the last block of data does not contains 128 bit data. Finally, we show from performance analysis that our proposed scheme can be effectively used for both text string processing applications and science data analysis applications.

Fast Algorithm for Polynomial Reconstruction of Fuzzy Fingerprint Vault (지문 퍼지볼트의 빠른 다항식 복원 방법)

  • Choi, Woo-Yong;Lee, Sung-Ju;Chung, Yong-Wha;Moon, Ki-Young
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.2
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    • pp.33-38
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    • 2008
  • Biometric based authentication can provide strong security guarantee about the identity of users. However, security of biometric data is particularly important as compromise of the data will be permanent. Cancelable biometrics stores a non - invertible transformed version of the biometric data. Thus, even if the storage is compromised, the biometric data remains safe. Cancelable biometrics also provide a higher level of privacy by allowing many templates for the same biometric data and hence non-linkability of user's data stored in different databases. In this paper, we proposed the fast polynomial reconstruction algorithm for fuzzy fingerprint vault. The proposed method needs (k+1) real points to reconstruct the polynomial of degree (k-1). It enhances the speed, however, by $300{\sim}1500$ times according to the degree of polynomial compared with the exhaust search.

Performance Comparison for Exercise Motion classification using Deep Learing-based OpenPose (OpenPose기반 딥러닝을 이용한 운동동작분류 성능 비교)

  • Nam Rye Son;Min A Jung
    • Smart Media Journal
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    • v.12 no.7
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    • pp.59-67
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    • 2023
  • Recently, research on behavior analysis tracking human posture and movement has been actively conducted. In particular, OpenPose, an open-source software developed by CMU in 2017, is a representative method for estimating human appearance and behavior. OpenPose can detect and estimate various body parts of a person, such as height, face, and hands in real-time, making it applicable to various fields such as smart healthcare, exercise training, security systems, and medical fields. In this paper, we propose a method for classifying four exercise movements - Squat, Walk, Wave, and Fall-down - which are most commonly performed by users in the gym, using OpenPose-based deep learning models, DNN and CNN. The training data is collected by capturing the user's movements through recorded videos and real-time camera captures. The collected dataset undergoes preprocessing using OpenPose. The preprocessed dataset is then used to train the proposed DNN and CNN models for exercise movement classification. The performance errors of the proposed models are evaluated using MSE, RMSE, and MAE. The performance evaluation results showed that the proposed DNN model outperformed the proposed CNN model.

An Encryption Algorithm Based on Light-Weight SEED for Accessing Multiple Objects in RFID System (RFID 시스템에서 다중 객체를 지원하기 위한 경량화된 SEED 기반의 암호화 알고리즘)

  • Kim, Ji-Yeon;Jung, Jong-Jin
    • Journal of Korea Society of Industrial Information Systems
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    • v.15 no.3
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    • pp.41-49
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    • 2010
  • Recently, RFID systems are spreading in various industrial areas faster but cause some serious problems of information security because of its unstable wireless communication. Moreover, traditional RFID systems have a restriction that one tag per each application object. This restriction deteriorates their usability because it is difficult to distinguish many tags without some kind of effort. Therefore, efficient information sharing of objects based on information security has to be studied for more spreading of RFID technologies. In this paper, we design a new RFID tag structure for supporting multiple objects which can be shared by many different RFID applications. We also design an encryption/decryption algorithm to protect the identifying information of objects stored in our tag structure. This algorithm is a light revision of the existing SEED algorithm which can be operated in RFID tag environment. To evaluate the performance of our algorithm, we measure the encryption and decryption times of this algorithm and compare the results with those of the original SEED algorithm.

Comparative Analysis of Information Security Textbooks for Chinese Elementary and Secondary Students (중국의 초·중등학생 대상 정보보호 교재 비교 고찰)

  • Eunsun Choi;Namje Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.183-192
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    • 2023
  • Digital transformation is taking place rapidly around the world. As the development of digital technology becomes very fast, more information is expected to be digitized. Therefore, the possibility of cyber threats is increasing in transmitting and storing sensitive information such as personal and financial information online. In this paper, we compared and analyzed information security textbooks for elementary and secondary school students in China, where the recent development of artificial intelligence and digital transformation are rapidly occurring. After we collected related textbooks, textbooks suitable for analysis were selected. Then, we analyzed the external and internal systems of the textbooks separately. As a result of the external system analysis, all the textbook covers were properly produced, but the quality difference was significant among textbooks. In the case of textbooks for elementary school students, the excellence of layout and content placement was noticed. On the other hand, due to the internal system analysis, various contents were not included evenly when looking at the learning contents based on the "information society responsibility" learning goals presented in China. Through this paper, we hope to provide implications for information security-related education and textbook development research.

A Software Vulnerability Analysis System using Learning for Source Code Weakness History (소스코드의 취약점 이력 학습을 이용한 소프트웨어 보안 취약점 분석 시스템)

  • Lee, Kwang-Hyoung;Park, Jae-Pyo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.11
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    • pp.46-52
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    • 2017
  • Along with the expansion of areas in which ICT and Internet of Things (IoT) devices are utilized, open source software has recently expanded its scope of applications to include computers, smart phones, and IoT devices. Hence, as the scope of open source software applications has varied, there have been increasing malicious attempts to attack the weaknesses of open source software. In order to address this issue, various secure coding programs have been developed. Nevertheless, numerous vulnerabilities are still left unhandled. This paper provides some methods to handle newly raised weaknesses based on the analysis of histories and patterns of previous open source vulnerabilities. Through this study, we have designed a weaknesses analysis system that utilizes weakness histories and pattern learning, and we tested the performance of the system by implementing a prototype model. For five vulnerability categories, the average vulnerability detection time was shortened by about 1.61 sec, and the average detection accuracy was improved by 44%. This paper can provide help for researchers studying the areas of weaknesses analysis and for developers utilizing secure coding for weaknesses analysis.

Design and Analysis of Data File Protection based on the Stream Cipher (데이터파일의 보호를 위한 스트림 암호방식 설계와 해석)

  • 이경원;이중한;김정호;오창석
    • The Journal of the Korea Contents Association
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    • v.4 no.1
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    • pp.55-66
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    • 2004
  • Recently, as the personal computers are supplied rapidly, they formed the nucleus of the computer system. But, because of the easiness that anyone uses them to go near easily, it is the fact that the security of personal computer is weakness. So, in the paper, 1 propose the technical method that minimizes the loss and leakage of important data. This paper implemented a crypto system for security of data file on personal computer and assistance storage medium. The way of encryption/decryption is applied by complexity method which mixed Diffie-Hellman key exchange protocol, a typical RC4(Rivest Cipher version 4) algorithm of stream cipher and a typical MD5(Message Digest version 5) of Hash Function. For valuation implemented crypto system, three criteria is presented, which are crypto complexity, processing time and pattern matching. And according to analysis the three criteria the crypto system is verified the security, efficiency and usefulness. The crypto system is programmed with Visual C++ language of Microsoft. And so, as this is software system, we shall have a technical security system at a minimum cost for all personal computer.

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A Study on IP Camera Security Issues and Mitigation Strategies (IP 카메라 보안의 문제점 분석 및 보완 방안 연구)

  • Seungjin Shin;Jungheum Park;Sangjin Lee
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.3
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    • pp.111-118
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    • 2023
  • Cyber attacks are increasing worldwide, and attacks on personal privacy such as CCTV and IP camera hacking are also increasing. If you search for IP camera hacking methods in spaces such as YouTube, SNS, and the dark web, you can easily get data and hacking programs are also on sale. If you use an IP camera that has vulnerabilities used by hacking programs, you easily get hacked even if you change your password regularly or use a complex password including special characters, uppercase and lowercase letters, and numbers. Although news and media have raised concerns about the security of IP cameras and suggested measures to prevent damage, hacking incidents continue to occur. In order to prevent such hacking damage, it is necessary to identify the cause of the hacking incident and take concrete measures. First, we analyzed weak account settings and web server vulnerabilities of IP cameras, which are the causes of IP camera hacking, and suggested solutions. In addition, as a specific countermeasure against hacking, it is proposed to add a function to receive a notification when an IP camera is connected and a function to save the connection history. If there is such a function, the fact of damage can be recognized immediately, and important data can be left in arresting criminals. Therefore, in this paper, we propose a method to increase the safety from hacking by using the connection notification function and logging function of the IP camera.

Trends in the use of big data and artificial intelligence in the sports field (스포츠 현장에서의 빅데이터와 인공지능 활용 동향)

  • Seungae Kang
    • Convergence Security Journal
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    • v.22 no.2
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    • pp.115-120
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    • 2022
  • This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

A Study on Biometric Model for Information Security (정보보안을 위한 생체 인식 모델에 관한 연구)

  • Jun-Yeong Kim;Se-Hoon Jung;Chun-Bo Sim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.317-326
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    • 2024
  • Biometric recognition is a technology that determines whether a person is identified by extracting information on a person's biometric and behavioral characteristics with a specific device. Cyber threats such as forgery, duplication, and hacking of biometric characteristics are increasing in the field of biometrics. In response, the security system is strengthened and complex, and it is becoming difficult for individuals to use. To this end, multiple biometric models are being studied. Existing studies have suggested feature fusion methods, but comparisons between feature fusion methods are insufficient. Therefore, in this paper, we compared and evaluated the fusion method of multiple biometric models using fingerprint, face, and iris images. VGG-16, ResNet-50, EfficientNet-B1, EfficientNet-B4, EfficientNet-B7, and Inception-v3 were used for feature extraction, and the fusion methods of 'Sensor-Level', 'Feature-Level', 'Score-Level', and 'Rank-Level' were compared and evaluated for feature fusion. As a result of the comparative evaluation, the EfficientNet-B7 model showed 98.51% accuracy and high stability in the 'Feature-Level' fusion method. However, because the EfficietnNet-B7 model is large in size, model lightweight studies are needed for biocharacteristic fusion.