• International Journal of Computer Science & Network Security
• /
• v.21 no.1
• /
• pp.174-183
• /
• 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.

• Journal of Korea Multimedia Society
• /
• v.25 no.10
• /
• pp.1433-1447
• /
• 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.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.18 no.4
• /
• pp.167-174
• /
• 2008

As both a digital camera and a digital camcorder are popularized in recent years, UCC created by general users is also popularized. Unfortunately, according to that, the lack of privacy is also increasing more and more. The UCC is saved on the recordable media(Media) like DVD and deposited personally as well as distributed through Internet portal service. If you use Internet portal service to put up your contents, you can partially prevent the violation of privacy using security technologies such as authentication and illegal copy protection offered by internet portal service providers. Media also has technologies to control illegal copy. However, it is difficult to protect your privacy if your Media having personal contents is stolen or lost. Therefore, it is necessary to develope an additional security mechanism to guarantee privacy protection when you use Media. In this paper, we describe AACS framework for Media Security and propose improved AACS framework to control the access to personal contents saved on Media.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.1-10
• /
• 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
• /
• v.24 no.2
• /
• pp.189-195
• /
• 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
• /
• v.22 no.9
• /
• pp.358-368
• /
• 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.

• Convergence Security Journal
• /
• v.10 no.3
• /
• pp.1-7
• /
• 2010

One of celebrities using Social media caught public's eye and interest in Korea. Thereby the number of the user has grown rapidly and by last year it had reached to about 770 million. But at the same time, it has brought us social issues such as invasion of privacy, spreading of malicious code, and stealing of ID. To solve these problems, first the government need to establish adequate law and policy. Second, Service provider should remove vulnerability in the security system and filter illegal information. Third, individual user should put more effort to protect their own privacy. This paper will suggest a solution of using the Social media more sound and secure.

• Smart Media Journal
• /
• v.6 no.3
• /
• pp.95-102
• /
• 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)
• /
• v.14 no.3
• /
• pp.1228-1248
• /
• 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.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.11
• /
• pp.195-200
• /
• 2019

The purpose of this paper is to explore security guard's status and roles in society through media reports. Research method is to anlyze security Guard's 'Keyword Trend' and 'Keyword Frequency Analysis' by 'Big Kind' which enables 'News Big Data' analysis. The result came out by the analysis in sectional private security guard's history of settling down, growing up (quantity), and growing up (quality) by separating generations is that there are lots of attention and exposure from media about crime, security guard job, minimum wage, and 'Gabjil', but the images of security guard are recognized as victim of crime and 'Gabjil', and working in poor environment with minimum waged and ambiguous job, instead of people preventing crimes. In the future, stabilizing security guard's social status and work responsibility, and developing job professionalism are necessary to improve the images of security guard.