• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.174-183
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• 2021

The advent of social media has revolutionized the speed of communication between millions of people around the world in various cultures and disciplines. Social media is the best platform for exchanging opinions and ideas, interacting with other users of similar interests and sharing different types of media and files. With the phenomenal increase in the use of social media platforms, the need to pay attention to protection and security from attacks and misuse has also increased. The present study conducts a comprehensive survey of the latest and most important research studies published from 2018-20 on security and privacy on social media and types of threats and attacks that affect the users. We have also reviewed the recent challenges that affect security features in social media. Furthermore, this research pursuit also presents effective and feasible solutions that address these threats and attacks and cites recommendations to increase security and privacy for the users of social media.

• 한국멀티미디어학회논문지
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• 제25권10호
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• pp.1433-1447
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• 2022

Recently, as the demand for physical security technology to prevent leakage of technical and business information of companies and public institutions increases, the high tech companies are operating X-ray security checkpoints at building entrances to protect their intellectual property and technology. X-ray security checkpoints are operated to detect cameras and storage media that may store or leak important technologies in the bags of people entering and leaving the building. In this study, we propose an X-ray security checkpoint system that automatically detects a storage medium in an X-ray image using a deep learning based object detection method. The proposed system consists of an edge computing unit and a cloud-computing unit. We employ the RetinaNet for automatic storage media detection in the X-ray security checkpoint images. The proposed approach achieved mAP of 95.92% on private dataset.

• 정보보호학회논문지
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• 제18권4호
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• pp.167-174
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• 2008

디지털 카메라와 캠코더의 보급이 증가함에 따라 일반 사용자들의 UCC(User Created Contents) 역시 일반화 되고 있다. 그러나 이에 따른 사생활 침해 또한 증가하고 있다. UCC는 인터넷 포탈 서비스를 통해 공유될 뿐 아니라 DVD(Digital Versatile/Video Disk)와 같은 저장매체(Recordable Media, 이하 Media)를 이용하여 보관된다. 포탈 서비스를 이용해서 콘텐츠를 게시하는 경우 포탈 시스템이 제공하는 사용자 인증 및 불법 다운로드 제어 기술을 이용하여 사생활 침해를 부분적으로 막을 수 있다. Media의 경우도 불법복제 제어기술을 채택하고 있지만, Media의 도난 또는 분실로 인한 콘텐츠 유출과 사생활 침해를 막을 수 있는 방법이 현재로서는 제공되지 않고 있다. 그러므로 Media를 이용하여 개인 콘텐츠를 관리하는 경우에도 사생활 침해를 막을 수 있는 추가적인 보안 기술의 연구가 필요하다. 본 논문에서는 Media 보안을 위해 제정된 AACS(Advanced Access Content System)의 Framework을 살펴보고 개인 콘텐츠의 접근을 제어할 수 있는 개선된 AACS 보안 Framework을 제안한다.

• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.1-10
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• 2021

Cyberbullying has become a severe issue and brought a powerful impact on the cyber world. Due to the low cost and fast spreading of news, social media has become a tool that helps spread insult, offensive, and hate messages or opinions in a community. Detecting cyberbullying from social media is an intriguing research topic because it is vital for law enforcement agencies to witness how social media broadcast hate messages. Twitter is one of the famous social media and a platform for users to tell stories, give views, express feelings, and even spread news, whether true or false. Hence, it becomes an excellent resource for sentiment analysis. This paper aims to detect cyberbully threats based on Naïve Bayes, support vector machine (SVM), and k-nearest neighbour (k-NN) classifier model. Sentiment analysis will be applied based on people's opinions on social media and distribute polarity to them as positive, neutral, or negative. The accuracy for each classifier will be evaluated.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.189-195
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• 2024

The issue "Exploring Social Media and Other Crucial Success Elements of Attitude towards Politics and Intention for Voting in Pakistan" is a huge study embracing more issues. The politics of Pakistan is basically the politics of semantic groups. Pakistan is a multilingual state more than six languages. There are 245 religious parties in Pakistan, as elaborated by the Daily Times research. The use of social media sites in Pakistan peaked to its maximum after announcement of election schedule by the Election Commission of Pakistan in March 22, 2013. Most of the political parties used it for the recent elections in Pakistan to promote their agenda and attract country's 80 million registered electors. This study was aiming to investigate the role of social media and other critical variables in the attitude towards politics and intention for voting.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.358-368
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• 2022

Social media is a window for everyone, individuals, communities, and companies to spread ideas and promote trends and products. With these opportunities, challenges and problems related to security, privacy and rights arose. Also, the data accumulated from social media has become a fertile source for many analytics, inference, and experimentation with new technologies in the field of data science. In this chapter, emphasis will be given to methods of trend analysis, especially ensemble learning methods. Ensemble learning methods embrace the concept of cooperation between different learning methods rather than competition between them. Therefore, in this chapter, we will discuss the most important trends in ensemble learning and their applications in analysing social media data and anticipating the most important future trends.

• 융합보안논문지
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• 제10권3호
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• pp.1-7
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• 2010

최근 소셜 미디어(Social Media)는 유명 인사들의 사용이 늘어나면서 많은 관심과 함께 사용 인구가 급증 추세로 2009년 말 기준으로 전 세계 소셜 미디어 사이트 방문자수가 7억 7천만 명에 이르고 있다. 그러나 개인 프라이버시 침해, 악성코드 유포수단으로 악용 및 ID 도용 등 사회적인 문제가 나타나고 있다. 이러한 문제를 해결하기 위해 정부는 법 제도를 보완하고 관련 기업은 보안취약점 제거와 함께 불법정보 필터링 기능을 사용자는 개인정보보호 강화를 위한 노력과 관심을 기울여야 한다. 본 논문에서는 건전하고 안전한 소셜 미디어 사용 확산을 위한 보안대책 강구방안에 관해 모색해 보았다.

• 스마트미디어저널
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• 제6권3호
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• pp.95-102
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• 2017

A large volume of research has been devoted to the development of security tools for protecting the Smart Grid systems, however the most of them have not taken the Availability, Integrity, Confidentiality (AIC) security triad model, not like CIA triad model in traditional Information Technology (IT) systems, into account the security measures for the electricity control systems. Thus, this study would propose a novel security framework, an abnormal behavior detection system, to maximize the availability of the control systems by considering a unique set of characteristics of the systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1228-1248
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• 2020

Steganalysis & steganography have witnessed immense progress over the past few years by the advancement of deep convolutional neural networks (DCNN). In this paper, we analyzed current research states from the latest image steganography and steganalysis frameworks based on deep learning. Our objective is to provide for future researchers the work being done on deep learning-based image steganography & steganalysis and highlights the strengths and weakness of existing up-to-date techniques. The result of this study opens new approaches for upcoming research and may serve as source of hypothesis for further significant research on deep learning-based image steganography and steganalysis. Finally, technical challenges of current methods and several promising directions on deep learning steganography and steganalysis are suggested to illustrate how these challenges can be transferred into prolific future research avenues.

• 한국컴퓨터정보학회논문지
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• 제24권11호
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• pp.195-200
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• 2019

이 연구의 목적은 언론 보도 분석을 통해 우리나라에서 경비원에 대한 인식과 이미지를 살펴보고 이를 통해 경비원의 지위와 역할에 대해 살펴보는데 있다. 연구방법은 뉴스 빅데이터 분석이 가능한 빅카인즈를 통해 경비원에 대한 키워드 트랜드와 연관어 분석을 실시하였다. 민간경비의 시대적 구분에 따라 정착기, 성장기(양적), 성장기(질적)으로 구분하여 분석한 결과 범죄, 경비업, 최저임금, 갑질에 관련된 언론의 관심과 노출이 많았던 것으로 나타났지만 범죄예방의 주체가 아닌 범죄와 갑질의 피해자, 경비업무의 애매모함, 최저임금 근무자로 근무환경이 열악한 직업의 이미지로 비춰지는 것으로 나타났다. 앞으로 경비원의 이미지 제고를 위해 경비원의 지위와 업무영역을 확고히 하고 전문성을 높여야 할 것이다.