Search

The proliferation of the internet has allowed various online games such as Massive Multiplayer Online Role Playing Game (MMORPG) and First-Person Shooter (FPS) to garner much attention. Both MMORPG and FPS requires lower network latency, as the users are constantly required to assess and respond to the gaming environment and other users’ decisions. Our study aims to investigate the users’ psychological behavior by changing the gaming environment. We present CPTED as a risk control measure. Based on the principle of CPTED, two types of maps were designed and compared to analyze the game violence of users in each map. In order to compare the game violence of the users, 100 questionnaires were conducted. In this study, we used FAIR, a risk analysis model, to assess the threat and violence of the users.

The critical success of online games has led the industry to global success, as the market size is expected to reach 18,194 USD by the year 2020. However, the success of the online game market has led to the growth of illegal activities, such as the use of game bots. Game bots are software applications capable of collecting game items, which are often banned from online game service providers. The illegal activities are not limited to tax evasion and money laundering. In order to help detect these bots, this study employs the dataset from an MMORPG called Aion. By detecting the bots using the server-side analysis, this paper analyzed user behavior and used features based on the experience, skill, and gravy value that represents the cost-efficiency. We experimented with machine learning algorithms such as MLP, SVM, and Random Forest. As a result, the F-score for detecting the total sum of the accounts that consists of the game bots and real users reached 0.9638. We believe our study may help online game service providers, future researchers, and governmental agencies to detect and classify the MMORPG game bots.

With the inception of online betting in S. Korea, various foreigner professional gambling groups have exploited the betting regulations. This phenomenon has occurred mainly in Asia, because the regulations on gambling in these countries are complex and robust. Our study focuses on the horse racing in S. Korea, which is operated under the government funding. The foreigner gambling groups tried unlimited betting by modifying the official IoT (Internet of Things) based APP arbitrarily. We have checked that some abnormal transactions can occur by modifying this application. Our study proposes a fraud detection method that can help detecting abnormal activities and prevent them. Currently, the Korea Racing Authority (KRA) has been criticized for being ill-equipped to detect abnormal activities with the Walkerhill Incident. Our study presents a new anomaly detection model that uses a flexible window. In this study, we propose an idea that aims to detect abnormal betting transactions.

Android’s permission system is asked to users before installing applications. It is intended to warn users about the risks of the app installation and gives users opportunities to review the application’s permission requests and uninstall it if they find it threatening. However, not all android permissions ask for the user’s decision. Those who are defined as ‘Dangerous’ in the permission protection level are only being confirmed by the users in Android Google Market. We examine whether the ‘Dangerous permissions’ are actually being a main component of detection when it comes to defining the app as malicious or benign. To collect important features and to investigate the correlation between the malicious app and the permission’s protection level, feature selection and deep learning algorithms were used. The study evaluates the feature by using the confusion matrix. We used 10,818 numbers of malicious and benign applications, and 457 permission lists to investigate our examination, and it appeared that ‘Dangerous’ permissions may not be the only important factor, and we suggest a different perspective of viewing permissions.

As the Russian government is revealed that it had intervened in the US presidential election by hacking, the social confusion caused by cyber attacks increased. This incident has led to the impeachment of the president by the dismissal of FBI director James Comey. In the French presidential election held in 2017, the social confusion created because of fake news during the period of election silence. The past cyber attacks were used as deception tactics, like the Georgian war. Nowadays, these attacks are concentrated in the period of social issues. In other words, these recent changes in cyber attacks have begun to have an adverse effect on systems in the real world, such as hybrid battlefields. This attack is called cyber influence attacks. This paper identifies the weaknesses of the basic democratic election system and classifies it against cyber influence attacks. In addition, we analyze the cyber influence attacks in Russia during the US presidential election in 2016 as a case study.

CAPTCHA is a simple challenge-response tool to determine whether the user is a bot or human. The user must answer required text, calculate questions, or choose some images from the provider’s choice. D portal site, which is one of the most famous web portal site in Korea, asks text response in CAPTCHA image when joining a cafe group, but this CAPTCHA is structured in a very regular format which can be read very simply if used repeatedly. We can read the text characters by bot with very high accuracy through some easy steps, among 2,000 sample CAPTHCAs.

The presentation entitled ICS Spear Phishing, held at the 2013 edition of Digital Bond’s Supervisory Control and Data Acquisition (SCADA) Security Scientific Symposium (S4) demonstrated that an attacker could employ a spear phishing attack to obtain rights to the accounts of the Industrial Control System (ICS) administrators or technicians. Motivated by this announcement, this paper analyzes the definition, principle, and problem of spear phishing, which is a social engineering attack. Furthermore, the need for countermeasures to the attack was presented. Attacks with spear phishing are gradually increased, but the existing system used in many organizations (e.g. e-mail filtering system) cannot follow the trend utilized by most attackers. Also, organizations have yet to establish adequate countermeasures, much less any standards for the countermeasures, to the problem of spear phishing. There is an urgent need to accomplish these objectives because the attack is gradually evolving. In summary, this paper advocates the awareness of the spear phishing threat and the implementation of countermeasures such as security education or simulation. In addition, it suggests on how to carry out the simulation effectively and how to quantify the gathered data.

Initially, the field only dealt with sensitive security information. However, as operations on cyber space increases, the need for security in internet also increased. Thus, areas that requires security assessment also increased. But, to date, a security evaluation for each area is performed partially. Since security assessment does not reflect the characteristics of each area, the correct security level is difficult to determine. Therefore, new security indicator is required for the effective and efficient management. In this paper, we provide an advanced security assessment using edited indicators and common indicators.