• 제목/요약/키워드: Computer Security Act

검색결과 65건 처리시간 0.024초

Virtual Go to School (VG2S): University Support Course System with Physical Time and Space Restrictions in a Distance Learning Environment

  • Fujita, Koji
    • International Journal of Computer Science & Network Security
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    • 제21권12호
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    • pp.137-142
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    • 2021
  • Distance learning universities provide online course content. The main methods of providing class contents are on-demand and live-streaming. This means that students are not restricted by time or space. The advantage is that students can take the course anytime and anywhere. Therefore, unlike commuting students, there is no commuting time to the campus, and there is no natural process required to take classes. However, despite this convenient situation, the attendance rate and graduation rate of distance learning universities tend to be lower than that of commuting universities. Although the course environment is not the only factor, students cannot obtain a bachelor's degree unless they fulfill the graduation requirements. In both commuter and distance learning universities, taking classes is an important factor in earning credits. There are fewer time and space constraints for distance learning students than for commuting students. It is also easy for distance learning students to take classes at their own timing. There should be more ease of learning than for students who commute to school with restrictions. However, it is easier to take a course at a commuter university that conducts face-to-face classes. I thought that the reason for this was that commuting to school was a part of the process of taking classes for commuting students. Commuting to school was thought to increase the willingness and motivation to take classes. Therefore, I thought that the inconvenient constraints might encourage students to take the course. In this research, I focused on the act of commuting to school by students. These situations are also applied to the distance learning environment. The students have physical time constraints. To achieve this goal, I will implement a course restriction method that aims to promote the willingness and attitude of students. Therefore, in this paper, I have implemented a virtual school system called "virtual go to school (VG2S)" that reflects the actual route to school.

A Review on Advanced Methodologies to Identify the Breast Cancer Classification using the Deep Learning Techniques

  • Bandaru, Satish Babu;Babu, G. Rama Mohan
    • International Journal of Computer Science & Network Security
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    • 제22권4호
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    • pp.420-426
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    • 2022
  • Breast cancer is among the cancers that may be healed as the disease diagnosed at early times before it is distributed through all the areas of the body. The Automatic Analysis of Diagnostic Tests (AAT) is an automated assistance for physicians that can deliver reliable findings to analyze the critically endangered diseases. Deep learning, a family of machine learning methods, has grown at an astonishing pace in recent years. It is used to search and render diagnoses in fields from banking to medicine to machine learning. We attempt to create a deep learning algorithm that can reliably diagnose the breast cancer in the mammogram. We want the algorithm to identify it as cancer, or this image is not cancer, allowing use of a full testing dataset of either strong clinical annotations in training data or the cancer status only, in which a few images of either cancers or noncancer were annotated. Even with this technique, the photographs would be annotated with the condition; an optional portion of the annotated image will then act as the mark. The final stage of the suggested system doesn't need any based labels to be accessible during model training. Furthermore, the results of the review process suggest that deep learning approaches have surpassed the extent of the level of state-of-of-the-the-the-art in tumor identification, feature extraction, and classification. in these three ways, the paper explains why learning algorithms were applied: train the network from scratch, transplanting certain deep learning concepts and constraints into a network, and (another way) reducing the amount of parameters in the trained nets, are two functions that help expand the scope of the networks. Researchers in economically developing countries have applied deep learning imaging devices to cancer detection; on the other hand, cancer chances have gone through the roof in Africa. Convolutional Neural Network (CNN) is a sort of deep learning that can aid you with a variety of other activities, such as speech recognition, image recognition, and classification. To accomplish this goal in this article, we will use CNN to categorize and identify breast cancer photographs from the available databases from the US Centers for Disease Control and Prevention.

Transformation of Legal Personality in the Context of the Development of Modern Digital Technologies

  • Amelin, Roman;Channov, Sergey;Dobrobaba, Marina;Kalinina, Larisa;Kholodnaya, Elena
    • International Journal of Computer Science & Network Security
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    • 제22권11호
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    • pp.294-302
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    • 2022
  • The article explores the prospects and trends for the transformation of some basic concepts of law associated with the development of artificial intelligence systems and the problems of liability for harm caused by a robot. The prospects, conditions and consequences of vesting robots with partial (quasi) or full legal personality are explored. This process should lead to a revision of the concepts of will, subjective side and legal responsibility in the direction of their greater universalization. The legally significant signs of will, legal personality, legal liability in relation to robots, artificial intelligence systems and other complex automated information systems are clarified. The author identifies the following essential factors of legal qualification of an act committed by a robot: goals, reasons for setting goals, connections between the planned result and the action taken, the actual result, the reasons for the difference between the actual result and the planned one. The article pays special attention to the preventive function of legal liability, which, when applied to robot subjects, can be expressed in the following basic procedures. 1. Accounting for legal requirements in the behavior of the robot. 2. Timely adaptation of the robot to changes in legislation and other regulatory legal acts that affect its behavior. 3. Accounting for incidents. 4. Destruction of a series of robots whose actions lead to unacceptable consequences.

CCTV 개인영상 정보보호를 위한 오프라인 객체추적 (Offline Object Tracking for Private Information Masking in CCTV Data)

  • 이석호
    • 한국정보통신학회논문지
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    • 제18권12호
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    • pp.2961-2967
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    • 2014
  • 최근 CCTV의 영상정보 공개시 타인의 영상에 대해서는 모자이크 처리하여 식별이 불가능하도록 하는 개인정보 보호법이 발표되었다. 반면에 CCTV를 통하여 획득된 영상 데이터를 활용한 범죄 수사는 점차 더 많이 활용되고 있는 추세이다. 이렇게 상반된 2가지의 요구사항에 의해 촬영된 CCTV 동영상을 수사기관 등의 기관에서 요청할 경우 개인정보(개인 얼굴 이미지 등)을 마스킹(Masking)해 배포함으로써 개인정보 유출을 차단하는 마스킹/ 언마스킹 솔루션에 대한 시장의 요구가 크게 성장할 것으로 예측된다. 정보주체가 정보열람 의뢰기관에 정보를 요구하기 전에 객체에 대한 선별 마스킹을 하기 위한 정보보호 솔루션에 있어서 가장 핵심되는 기술은 객체에 대한 추적기술이다. 본 논문에서는 CCTV영상에 대한 후처리로써의 정보보호 솔루션에 적합한 객체추적 알고리즘을 제안한다. 안정적인 추적이 가능하도록 하기 위해 움직임정보와 색상정보를 함께 사용하였다. 그러면서도 시간이 많이 걸리지 않는 컬러 중심점 이동(Color Centroid Shifting) 기반의 방법을 사용하여 추적의 속도 성능을 높였다.

정보화 사회의 위험적 요소와 민간시큐리티의 역할 (The risk of the Information-oriented society and the role of private security)

  • 공배완
    • 한국재난정보학회 논문집
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    • 제8권1호
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    • pp.1-9
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    • 2012
  • 현대사회의 정보화는 컴퓨터와 인터넷을 통해 대량의 정보를 생산 교류하므로 새로운 커뮤니케이션 방식을 탄생시키고 있다. 과거 피동적 방식의 일방적 정보흐름이 능동적 상호작용 방식으로 진화하여 정보생산자와 정보소비자의 구별을 약회시키고 있으며, 온라인상의 인적관계를 강화시키는 Social Networking Service의 사회구조로 발전하고 있다. 따라서 정보의 확산은 사회적 네트워크 구조를 긴밀하게 작용시킴으로 사회적 갈등을 불러일으키는 하나의 요인으로도 작용하기도 하고, 제도와 환경, 개인의 문화적 적응이 과학 기술의 빠른 발전 속도를 따라가지 못함으로 갈등과 혼란을 초래하기도 한다. 이에 본 논문은 정보화 사회의 특성과 진화과정을 살펴보면서 정보화의 파장으로서 사회적 위험요인을 살펴보고 이에 대한 민간시큐리티의 역할을 모색해 보고자 한다. 정보화 사회는 시간과 공간의 영역을 축소시켜 인간생활의 편리성과 간편성을 가져다 준 반면, 비대면성과 익명성이라는 특성으로 인해 많은 사회적 부작용도 발생시키고 있다. 이에 국가차원의 제도적 대책 마련이 이루어지고 있지만 개인생활보호를 위한 민간차원의 보호장치는 아직 논의되지 않고 있다. 주문자 방식의 개인의 생명과 재산을 보호하는 민간시큐리티가 이를 담당해야 할 것이다.

Design the Autopilot System of using Fuzzy Algoritim

  • Kim, Young-Hwi;Bae, Gyu-Han;Park, Jae-Hyung;Kang, Sin-Chool;Lee, Ihn-Yong;Lim, Young-Do
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.296-300
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    • 2003
  • The autopilot system targets decreasing labor, working environment improvement, service safety security and elevation of service efficiency. Ultimate purpose is minimizing number of crew for guarantee economical efficiency of shipping service. Recently, being achieving research about Course Keeping Control, Track Keeping Control, Roll-Rudder Stabilization. Dynamic Ship Positioning and Automatic Mooring Control etc. which compensate nonlinear characteristic using optimizing control technique. And application research is progressing using real ship on actual field. Relation of Rudder angle which adjusted by Steering Machine and ship-heading angle are non-linear. And Load Condition of ship as non-linear element that influence to Parameter of ship. Also, because the speed of a current and direction of waves, velocity and quantity of wind etc. that is disturbance act in non-linear from, become factor who make serv ice of shipping painfully. Therefore, service system of shipping requires robust control algorithm that can overcome nonlinearity. In this paper, Using fuzzy algorithm ,Design autopilot system of ship that could overcome the non-linear factor of ship and disturbance and examined result through simulation.

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Strategy Design to Protect Personal Information on Fake News based on Bigdata and Artificial Intelligence

  • Kang, Jangmook;Lee, Sangwon
    • International Journal of Internet, Broadcasting and Communication
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    • 제11권2호
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    • pp.59-66
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    • 2019
  • The emergence of new IT technologies and convergence industries, such as artificial intelligence, bigdata and the Internet of Things, is another chance for South Korea, which has established itself as one of the world's top IT powerhouses. On the other hand, however, privacy concerns that may arise in the process of using such technologies raise the task of harmonizing the development of new industries and the protection of personal information at the same time. In response, the government clearly presented the criteria for deidentifiable measures of personal information and the scope of use of deidentifiable information needed to ensure that bigdata can be safely utilized within the framework of the current Personal Information Protection Act. It strives to promote corporate investment and industrial development by removing them and to ensure that the protection of the people's personal information and human rights is not neglected. This study discusses the strategy of deidentifying personal information protection based on the analysis of fake news. Using the strategies derived from this study, it is assumed that deidentification information that is appropriate for deidentification measures is not personal information and can therefore be used for analysis of big data. By doing so, deidentification information can be safely utilized and managed through administrative and technical safeguards to prevent re-identification, considering the possibility of re-identification due to technology development and data growth.

사이버범죄에 대한 국제적 대응방안 (A Study of International Confrontation on the Prevention of Cyber Crime)

  • 정정일
    • 시큐리티연구
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    • 제10호
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    • pp.323-354
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    • 2005
  • 최근 정보통신기술의 눈부신 진보와 컴퓨터의 네크워크화는 우리 인간의 생활을 급변시키고 있다. 특히 우리나라는 광대역 인터넷 망이나 전자정부의 구현, 디지털 컨버전스의 시현, 시민들의 디지털 엑세스권 등 인터넷을 통한 쇼핑이나 인터넷뱅킹${\cdot}$주식거래, 사이버교육 등 실생활에서 인터넷을 활용하는 수준은 세계 최고이다. 이렇듯 이전에 누려보지 못했던 편리함과 효율성을 제공하는 소위 ‘사이버세계’가 새로운 생활공간으로 자리 잡게 되었다. 이러한 사이버공간은 정보습득을 하는데 있어서 여러모로 편리함과 신속함을 제공하는 등 순기능적인 측면도 있으나, 그 반면에 사이버공간을 이용한 사이버범죄는 우리가 예전에는 볼 수 없었던 신종 범죄가 기하급수적으로 늘어가는 추세에 있다. 특히 이러한 사이버범죄의 심각성은 국경을 초월하여 발생하고 범죄에 따른 피해가 전 세계 모든 국가에 미치며 효과적인 방지와 처벌이 이루어지지 못하고 있다는 데 있다. 정보사회로의 발전과정에서 필연적으로 발생하는 부정적 결과라 할 수 있는 사이버범죄는 지금까지 적용되어 오던 사회 전반의 법과 질서에 변화를 요구하고 있다. 이러한 인식하에 본 논문의 지역적 한계와 제도적 미비로 인하여 일률적이고 효과적인 통제와 관리 및 법의 적용이 효율적으로 행해지지 않는 사이버 공간상의 범죄를 규명하여 사전적 예방 대책과 범국가적 차원에서의 제도적${\cdot}$법적 공조방안을 모색하고자 한다.

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Detecting Stress Based Social Network Interactions Using Machine Learning Techniques

  • S.Rajasekhar;K.Ishthaq Ahmed
    • International Journal of Computer Science & Network Security
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    • 제23권8호
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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.

에너지 IoT 플랫폼 개발에 관한 연구 (A Study on the Development of Energy IoT Platform)

  • 박명혜;김영현;이승배
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제5권10호
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    • pp.311-318
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    • 2016
  • 사물인터넷(IoT, Internet of Things) 분야는 풍부한 정보를 기반으로 사용자가 쉽게 접근해서 서비스를 창출해야 하나, 전력시스템의 특수성으로 인해 다음의 사항이 IoT 확산에 걸림돌로 작용할 수 있으며 '지능형 전력망 정보의 보호 조치에 관한 지침'에 의거, 전력설비 접근이 용이하지 않고, 특히 AMI(Advanced Metering Infrastructure)분야에 IoT 기술적용시 엄격한 보안 정책이 요구되고 있다. 이로 인해 IoT 기술의 전력시스템에 적용 및 활용에 제약이 발생되는 실정이다. 전력정보통신망은 그간 폐쇄망으로 운영되어 왔으며, 스마트그리드(Smart Grid) 인프라인 지능형 전력망에서도 개방형 양방향 통신을 검토하고 있으나 정보보안 취약성이 높아지고 사고 위험이 증가함에 따라 종합적인 보안정책 및 기술이 요구되고 있다. 본 논문은 IoT 기반 에너지 플랫폼 개발 연구내용의 일부로 전력정보시스템의 IoT 플랫폼 아키텍쳐 설계를 목표로 한다. IoT를 기반으로 전력서비스 및 솔루션을 제공하기 위해 '센서-게이트웨이-네트워크-플랫폼-서비스'를 하나로 연결하는 표준 프레임워크를 제정하고자 한다. 프레임워크는 크게 '센서-게이트웨이-플랫폼'을 연계하는 정보모델링 및 연동규약을 다루는 표준과 이를 토대로 다양한 센서를 수용할 수 있는 게이트웨이, 실시간 데이터 수집 분석 제공 역할을 수행하는 플랫폼으로 구분하고 관련 기술을 확보하고자 한다.