• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.153-158
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• 2022

The Internet of Things (IoT) has gotten a lot of research attention in recent years. IoT is seen as the internet's future. IoT will play a critical role in the future, transforming our lifestyles, standards, and business methods. In the following years, the use of IoT in various applications is likely to rise. In the world of information technology, cyber security is critical. In today's world, protecting data has become one of the most difficult tasks. Different type of emerging cyber threats such as malicious, network based and abuse of network have been identified in the IoT. These can be done by virus, Phishing, Spam and insider abuse. This paper focuses on emerging threats, various challenges and vulnerabilities which are faced by the cyber security in the field of IoT and its applications. It focuses on the methods, ethics, and trends that are reshaping the cyber security landscape. This paper also focuses on an attempt to classify various types of threats, by analyzing and characterizing the intruders and attacks facing towards the IoT devices and its services.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.172-187
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• 2021

In remote villages without access to modern IT technology, simple devices such as smartcards can be used to carry out business transactions. These devices typically store multiple business applications from multiple vendors. Although devices must prevent malicious or accidental security breaches among the applications, a secure communication channel between two applications from different vendors is often required. In this paper, first, we propose a method of establishing secure communication channels between applications in embedded operating systems that run on multi-applet smart cards. Second, we enforce the high assurance using an intransitive noninterference security policy. Thirdly, we formalize the method through the Z language and create the formal specification of the proposed secure system. Finally, we verify its correctness using Rushby's unwinding theorem.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1145-1157
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• 2012

Google Android employs a security model based on application permissions to control accesses to system resources and components of other applications from a potentially malicious program. But, this model has security vulnerabilities due to lack of user comprehension and excessive permission requests by 3rd party applications. Broadcast intent message is widely used as a primary means of communication among internal application components. However, this mechanism has also potential security problems because it has no security policy related with it. In this paper, we first present security breach scenarios caused by inappropriate use of application permissions and broadcast intent messages. We then analyze and compare usage patterns of application permissions and broadcast intent message for popular applications on Android market and malwares, respectively. The analysis results show that there exists a characteristic set for application permissions and broadcast intent receiver that are requested by typical malwares. Based on the results, we propose a scheme to detect applications that are suspected as malicious and notify the result to users at installation time.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.280-287
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• 2022

Recently, the number of mobile ransomware types has increased. Moreover, the number of cases of damage caused by mobile ransomware is increasing. Representative damage cases include encrypting files on the victim's smart device or making them unusable, causing financial losses to the victim. This study classifies ransomware apps by analyzing several representative ransomware apps to identify trends in the malicious behavior of ransomware. We present a technique for recovering from the damage, from a digital forensic perspective, using reverse engineering ransomware apps to analyze vulnerabilities in malicious functions applied with various cryptographic technologies. Our study found that ransomware applications are largely divided into three types: locker, crypto, and hybrid. In addition, we presented a method for recovering the damage caused by each type of ransomware app using an actual case. This study is expected to help minimize the damage caused by ransomware apps and respond to new ransomware apps.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3738-3760
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• 2022

Due to increasing spectrum demand for new wireless devices applications, cooperative spectrum sensing (CSS) paradigm is the most promising solution to alleviate the spectrum shortage problem. However, in the interweave cognitive radio (CR) system, the inherent nature of CSS opens a hole to Byzantine attack, thereby resulting in a significant drop of the CSS security and efficiency. In view of this, a weighted differential sequential single symbol (WD3S) algorithm based on MATLAB platform is developed to accurately identify malicious users (MUs) and benefit useful sensing information from their malicious reports in this paper. In order to achieve this, a dynamic Byzantine attack model is proposed to describe malicious behaviors for MUs in an interweave CR system. On the basis of this, a method of data transmission consistency verification is formulated to evaluate the global decision's correctness and update the trust value (TrV) of secondary users (SUs), thereby accurately identifying MUs. Then, we innovatively reuse malicious sensing information from MUs by the weight allocation scheme. In addition, considering a high spectrum usage of primary network, a sequential and differential reporting way based on a single symbol is also proposed in the process of the sensing information submission. Finally, under various Byzantine attack types, we provide in-depth simulations to demonstrate the efficiency and security of the proposed WD3S.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.27-35
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• 2018

This paper is a study to classify malicious applications in Android environment. And studying the threat and behavioral analysis of malicious Android applications. In addition, malicious apps classified by machine learning were performed as experiments. Android behavior analysis can use dynamic analysis tools. Through this tool, API Calls, Runtime Log, System Resource, and Network information for the application can be extracted. We redefined the properties extracted for machine learning and evaluated the results of machine learning classification by verifying between the overall features and the main features. The results show that key features have been improved by 1~4% over the full feature set. Especially, SVM classifier improved by 10%. From these results, we found that the application of the key features as a key feature was more effective in the performance of the classification algorithm than in the use of the overall features. It was also identified as important to select meaningful features from the data sets.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.698-701
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• 2013

Mobile social networking applications are getting increasingly popular among today's mobile applications. Mobile users find their old or new friends anywhere or anytime through mobile social network (MSN) services. MSN uses matchmaking mechanisms to discover mutual interests among different people. To discover friends in MSN, a user must share his/her private information which can be a risk for his/her personal privacy as this information can be learned by a malicious or semi honest user. In this paper we give a brief survey on MSN that includes MSN categories, components, architecture and applications. In the rest of the paper we discuss the matchmaking protocols. Finally we give some suggestions to improve the previous protocols.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.111-120
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• 2011

The concept of Smart-Homes is becoming more and more popular. It is anticipated that Radio Frequency IDentification (RFID) technology will play a major role in such environments. We can find many previously proposed schemes that focus solely on: authentication between the RFID tags and readers, and user privacy protection from malicious readers. There has also been much talk of a very popular RFID application: a refrigerator/bookshelf that can scan and list out the details of its items on its display screen. Realizing such an application is not as straight forward as it seems to be, especially in securely deploying such RFID-based applications in a smart home environment. Therefore this paper describes some of the RFID-based applications that are applicable to smart home environments. We then identify their related privacy and security threats and security requirements and also propose a secure approach, where RFID-tagged consumer items, RFID-reader enabled appliances (e.g., refrigerators), and RFID-based applications would securely interact among one another. At the moment our approach is just a conceptual idea, but it sheds light on very important security issues related to RFID-based applications that are beneficial for consumers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.453-462
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• 2021

The number of foreign applications available in Korea is increasing. Among them, there are many cases where applications having a large number of domestic users collect users' personal information in an unauthorized manner, causing serious problems. Unauthorized collection of personal information conducted through such applications is highly dangerous, because sensitive personal information of users can be used in a malicious way. Further, this is violation of business ethics and may interrupt the creation of the sound information technology ecosystem. This research is purposed to analyze the current status of unauthorized collection of users' personal information by foreign applications available in Korea and to derive countermeasures thereof.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.145-154
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• 2014

In this paper, we propose a novel anti-malware system based on behavior profiling, called Andro-profiler. Andro-profiler consists of mobile devices and a remote server, and is implemented in Droidbox. Our aim is to detect and classify malware using an automatic classifier based on behavior profiling. First, we propose the representative behavior profiling for each malware family represented by system calls coupled with Droidbox system logs. This is done by executing the malicious application on an emulator and extracting integrated system logs. By comparing the behavior profiling of malicious applications with representative behavior profiling for each malware family, we can detect and classify them into malware families. Andro-profiler shows over 99% of classification accuracy in classifying malware families.