• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.499-505
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• 2014

According to the increasing use of smart devices such as smart phones and tablets, the service that targets mobile office, finance and e-government for convenience of usage and productivity has emerged significantly. As a result, important information is treated with the smart devices and also, the malicious activity that targets smart devices is increasing steadily. In particular, the damage case by harmful sites, malware distribution sites and phishing sites that targets smart devices has occurred steadily and it has emerged as a social issue. In the case of smart devices, the Android platform is occupied the 90% in Korea, 2013 therefore the method of device block level is required to resolve the social issues of smart devices. In this paper, we propose a method that can be effectively blocked when you try to access an illegal site to Web browser on the Android platform and develop the application and also analyze the wrong site block function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.360-361
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• 2017

The infrastructure of the country and society is connected to cyberspace. Malicious codes that steal financial information from websites such as plastic surgeons, dentists, and hospitals that are confirmed as IP in Daegu South Korea area are spreading In particular, financial information is an important privacy target. Takeover of financial information leads to personal financial loss. In this paper, we analyze the recent pharming malicious code that takes financial information. Attack files with social engineering methods are spread as executables in the banner, disguised as downloaders. When the user selects the banner, the attack file infects the PC with malicious code to the user. The infected PC takes users to the farming site and seizes financial information and personal security card information. The fraudulent financial information causes a financial loss to the user. The research in this paper will contribute to secure financial security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.906-918
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• 2018

The advent of the Internet of Things (IoT) technology, which brings many benefits to our lives, has resulted in numerous IoT devices in many parts of our living environment. However, to adapt to the rapid changes in the IoT market, numerous IoT devices were widely deployed without implementing security by design at the time of development. As a result, malicious attackers have targeted IoT devices, and IoT devices lacking security features have been compromised by attackers, resulting in many security incidents. In particular, an attacker can take control of an IoT device, such as Mirai Botnet, that has insufficient security features. The IoT device can be used to paralyze numerous websites by performing a DDoS attack against a DNS service provider. Therefore, this study proposes a scheme to minimize security vulnerabilities and threats in IoT devices to improve the security of the IoT service environment.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.277-283
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• 2022

Email phishing has become very prevalent especially now that most of our dealings have become technical. The victim receives a message that looks as if it was sent from a known party and the attack is carried out through a fake cookie that includes a phishing program or through links connected to fake websites, in both cases the goal is to install malicious software on the user's device or direct him to a fake website. Today it is difficult to deploy robust cybersecurity solutions without relying heavily on machine learning algorithms. This research seeks to detect phishing emails using high-accuracy machine learning techniques. using the WEKA tool with data preprocessing we create a proposed methodology to detect emails phishing. outperformed random forest algorithm on Naïve Bayes algorithms by accuracy of 99.03 %.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1290-1295
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• 2016

Recently, as mobile internet usage has been increasing rapidly, malware attacks through user's web browsers has been spreading in a way of social engineering or drive-by downloading. Existing defense mechanism against drive-by download attack mainly focused on final download sites and distribution paths. However, detection and prevention of injection sites to inject malicious code into the comprised websites have not been fully investigated. In this paper, for the purpose of improving defense mechanisms against these malware downloads attacks, we focus on detecting the injection site which is the key source of malware downloads spreading. As a result, in addition to the current URL blacklist techniques, we proposed the enhanced method which adds features of detecting the injection site to prevent the malware spreading. We empirically show that the proposed method can effectively minimize malware infections by blocking the source of the infection spreading, compared to other approaches of the URL blacklisting that directly uses the drive-by browser exploits.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Convergence Security Journal
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• v.18 no.3
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• pp.37-44
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• 2018

Today we live in a flood of web sites and access numerous websites through the Internet to obtain various information. However, unless the security of the Web site is secured, Web site security can not be secured from various malicious attacks. Hacking attacks, which exploit Web site security vulnerabilities for various reasons, such as financial and political purposes, are increasing. Various attack techniques such as SQL-injection, Cross-Site Scripting(XSS), and Drive-By-Download are being used, and the technology is also evolving. In order to defend against these various hacking attacks, it is necessary to remove the vulnerabilities from the development stage of the website, but it is not possible due to various problems such as time and cost. In order to compensate for this, it is important to identify vulnerabilities in Web sites through web vulnerability checking and take action. In this paper, we investigate web vulnerabilities and diagnostic techniques and try to understand the priorities of vulnerabilities in the development stage according to the actual status of each case through cases of actual web vulnerability diagnosis.

• Smart Media Journal
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• v.8 no.1
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• pp.27-34
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• 2019

Ransomware is a malicious program code evolved into various forms of attack. Unlike traditional Ransomware that is being spread out using email attachments or infected websites, a new type of Ransomware, such as WannaCryptor, may corrupt files just for being connected to the Internet. Due to global Ransomware damage, there are many studies conducted to detect and defense Ransomware. However, existing research on Ransomware detection only uses Ransomware signature database or monitors specific behavior of process. Additionally, existing Ransomware detection methods hardly detect and defense a new Ransomware that behaves differently from the traditional ones. In this paper, we propose a method to detect Ransomware by arranging decoy files and analyzing the method how Ransomware accesses and operates files in the file system. Also, we conduct experiments using proposed method and provide the results of detection and defense of Ransomware in this paper.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.4
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• pp.127-132
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• 2022

An anonymous encrypted communication networks that make it difficult to identify the trace of a user's access by passing through several virtual computers and/or networks, such as Tor, provides user and data privacy in the process of Internet communications. However, when it comes to abuse for inappropriate purposes, such as sharing of illegal contents, arms trade, etc. through such anonymous encrypted communication networks, it is difficult to detect and take appropriate countermeasures. In this paper, by extending the website fingerprinting technique that can identify access to a specific site even in anonymous encrypted communication, a method for specifying and classifying service types of websites for not only well-known sites but also unknown sites is proposed. This approach can be used to identify hidden sites that can be used for malicious purposes.

• Convergence Security Journal
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• v.23 no.3
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• pp.29-36
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• 2023

With the recent surge in exposure to fake advertising phishing sites in search engines, the damage caused by poor search quality and personal information leakage is increasing. In particular, the seriousness of the problem is worsening faster as the possibility of automating the creation of advertising phishing sites through tools such as ChatGPT increases. In this paper, the source code of fake advertising phishing sites was statically analyzed to derive structural commonalities, and among them, a detection crawler that filters sites step by step based on foreign domains and redirection was developed to confirm that fake advertising posts were finally detected. In addition, we demonstrate the need for new guide lines by verifying that the redirection page of fake advertising sites is divided into three types and returns different sites according to each situation. Furthermore, we propose new detection guidelines for fake advertising phishing sites that cannot be detected by existing detection methods.