• Journal of the Korea Society of Computer and Information
• /
• v.20 no.6
• /
• pp.37-42
• /
• 2015

In this paper, we propose malware database in mobile memory for realtime malware URL detection and we support realtime malware URL detection engine, that is control the web service for more secure mobile service. Recently, mobile malware is on the rise and to be new threat on mobile environment. In particular the mobile characteristics, the damage of malware is more important, because it leads to monetary damages for the user. There are many researches in cybercriminals prevention and malware detection, but it is still insufficient. Additionally we propose the method for prevention Smishing within SMS, MMS. In the near future, mobile venders must build the secure mobile environment with fundamental measures based on our research.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2736-2754
• /
• 2015

Android dominates the mobile operating system market, which stimulates the rapid spread of mobile malware. It is quite challenging to detect mobile malware. System call sequence analysis is widely used to identify malware. However, the malware detection accuracy of existing approaches is not satisfactory since they do not consider correlation of system calls in the sequence. In this paper, we propose a new scheme called Artificial Neural Networks (ANNs) on Co-occurrence Matrices Droid (ANNCMDroid), using co-occurrence matrices to mine correlation of system calls. Our key observation is that correlation of system calls is significantly different between malware and benign software, which can be accurately expressed by co-occurrence matrices, and ANNs can effectively identify anomaly in the co-occurrence matrices. Thus at first we calculate co-occurrence matrices from the system call sequences and then convert them into vectors. Finally, these vectors are fed into ANN to detect malware. We demonstrate the effectiveness of ANNCMDroid by real experiments. Experimental results show that only 4 applications among 594 evaluated benign applications are falsely detected as malware, and only 18 applications among 614 evaluated malicious applications are not detected. As a result, ANNCMDroid achieved an F-Score of 0.981878, which is much higher than other methods.

• International journal of advanced smart convergence
• /
• v.6 no.1
• /
• pp.1-8
• /
• 2017

Diverse types of malicious code such as evasive Server-side Polymorphic are developed and distributed in third party open markets. The suspicious new type of polymorphic malware has the ability to actively change and morph its internal data dynamically. As a result, it is very hard to detect this type of suspicious transaction as an evidence of Server-side polymorphic mobile malware because its C&C server was shut downed or an IP address of remote controlling C&C server was changed irregularly. Therefore, we implemented Simulated C&C Server to aggregate activated events perfectly from various Server-side polymorphic mobile malware. Using proposed Simulated C&C Server, we can proof completely and classify veiled server-side polymorphic malicious code more clearly.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.2
• /
• pp.47-54
• /
• 2015

The popularity and adoption of smart-phones has greatly stimulated the spread of mobile malware, especially on the popular platforms such as Android. The fluidity of application markets complicate smart-phone security. There is a pressing need to develop effective solutions. Although recent efforts have shed light on particular security issues, there remains little insight into broader security characteristics of smart-phone application. Now, the analytical methods used mainly are the reverse engineering-based analysis and the sandbox-based analysis. Such methods are can be analyzed in detail. but, they take a lot of time and have a one-time payout. In this study, we develop a system to monitor that mobile application permissions at application update. We had to overcome a one-time analysis. This study is a service-based malware analysis, It will be based will be based on the mobile security study.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.8
• /
• pp.1457-1471
• /
• 2011

A method to detect Trojan horses in messaging and Bluetooth in mobile phones by means of monitoring the events produced by the infections is presented in this paper. The structure of the detection approach is split into two modules: the first is the Monitoring module which controls connection requests and sent/received files, and the second is the Graphical User module which shows messages and, under suspicious situations, reports the user about a possible malware. Prototypes have been implemented on different mobile operating systems to test its feasibility on real cellphone malware. Experimental results are shown to be promising since this approach effectively detects various known malware.

• Journal of Information Processing Systems
• /
• v.3 no.2
• /
• pp.54-63
• /
• 2007

The high-speed mobile Internet has recently been expanded, many attractive services are provided. However, these services require some form of security-related technology. This paper outlines Japanese mobile services and exposits some mobile security topics including mobile spam, mobile malware, mobile DRM system, mobile WiMAX security, and mobile key management.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.8
• /
• pp.738-745
• /
• 2014

Recently, mobile users continuously increase, and mobile applications also increase As mobile applications increase, the mobile users used to store sensitive and private information such as Bank information, location information, ID, password on their mobile devices. Therefore, recent malicious application targeted to mobile device instead of PC environment is increasing. In particular, since the Android is an open platform and includes security vulnerabilities, attackers prefer this environment. This paper analyzes the performance of malware detection system applying linear SVM machine learning classifier to detect Android malware application. This paper also performs feature selection in order to improve detection performance.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.3
• /
• pp.357-367
• /
• 2020

According to Symantec's 2018 internet security threat report, The number of new mobile malware variants increased by 54 percent in 2017, as compared to 2016. And last year, there were an average of 24,000 malicious mobile applications blocked each day. Existing signature-based technologies of malware detection have limitations. So, malware detection technique through machine learning is being researched to detect malware variant. However, even in the case of applying machine learning, if the proper features of the malware are not properly selected, the machine learning cannot be shown correctly. We are focusing on feature selection method to find the features of malware variant in this research.

• Journal of Information Technology Services
• /
• v.13 no.2
• /
• pp.113-131
• /
• 2014

Smartphone security threat has become an important issue in Information Science field following the wide distribution of smartphones. However, there are few studies related to such. Therefore, this study examined the factors affecting the intention of smartphone users to use the mobile vaccine against malware with the Protection Motivation Theory. To secure the reliability of the study, a surveying agency was commissioned. A total of 263 respondents, excluding 37 respondents who are users of iOS, which does not have mobile vaccine in the smart phone, or who gave invalid responses, were surveyed. The results showed that perception of the installed mobile vaccine significantly affected the Response Efficacy and Self-efficacy, and that the Perceived Severity, Perceived Vulnerability, Response Efficacy, and Self-efficacy significantly influenced the intention to use the mobile vaccine. On the other hand, Installation Perception of mobile vaccine itself did not affect the Perceived Severity and Perceived Vulnerability. This study is significant since it presented the new evaluation model of threat evaluation and response evaluation in the Protection Motivation Theory in accepting the security technology and raised the need for the promotion and exposure of mobile vaccine, since perception of mobile vaccine installation affects the response evaluation. It also found that the promotion must consider the seriousness of smartphone security, outstanding attribute of mobile vaccine, and user-friendliness of mobile vaccine above all.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.3
• /
• pp.53-62
• /
• 2015

Recently, number of tablet or Smartphone users increased significantly in domestic and around the world. But violation of personal information such as leakage, misuse and abuse are constantly occurring by using mobile devices which is very useful in our society. Therefore, in this paper it will talk about the problems in the network environment of the mobile environment such as tablet and Smartphone, Mobile Malware, hacking of the public key certificate, which could be potential threat to mobile environment. This thesis will research for people to use their mobile devices more reliable and safer in mobile environment from invasion and leakage of personal information. In order to use Smartphone safely, users have to use Wi-Fi and Bluetooth carefully in the public area. This paper will research how to use App safely and characteristic of risk of worm and Malware spreading. Because of security vulnerabilities of the public key certificate, it will suggest new type of security certification. In order to prevent from the information leakage and infect from Malware in mobile environment without knowing, this thesis will analyze the improved way to manage and use the mobile device.