• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.73-80
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• 2009

Internet accidents have skyrocketed every year. It always has been threatened by the methods such as hacking and Spyware. The majority of security accident is formed of the loss of authentication information, and the internal user who is not authorized. The importance of security is also emphasized when someone tries to do something accessing to the main information system. Accordingly, Biometrics has been used in many ways. OTP, however, must have a few devices accessing to several systems, and Biometrics involve some risk of mis-recognition rate and mis-denial rate. It also has the risk possible to access to the main information system when losing OTP. This research reduced risks about the loss as separating RFID leader for mobile, Tag and the accessor's cellular phone, and is about pseudo random validation key generated from the administration system through contact with RFID leader for mobile and Tag. As sending the key to user's cell phone which is already registered, security is strengthened more than existing connection methods through the ID and password. RFID for mobile not generalized to the present has been studied as a tool accessing to the main information system.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.186-192
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• 2023

Malwares are becoming a major problem nowadays all around the world in android operating systems. The malware is a piece of software developed for harming or exploiting certain other hardware as well as software. The term Malware is also known as malicious software which is utilized to define Trojans, viruses, as well as other kinds of spyware. There have been developed many kinds of techniques for protecting the android operating systems from malware during the last decade. However, the existing techniques have numerous drawbacks such as accuracy to detect the type of malware in real-time in a quick manner for protecting the android operating systems. In this article, the authors developed a hybrid model for android malware detection using a decision tree and KNN (k-nearest neighbours) technique. First, Dalvik opcode, as well as real opcode, was pulled out by using the reverse procedure of the android software. Secondly, eigenvectors of sampling were produced by utilizing the n-gram model. Our suggested hybrid model efficiently combines KNN along with the decision tree for effective detection of the android malware in real-time. The outcome of the proposed scheme illustrates that the proposed hybrid model is better in terms of the accurate detection of any kind of malware from the Android operating system in a fast and accurate manner. In this experiment, 815 sample size was selected for the normal samples and the 3268-sample size was selected for the malicious samples. Our proposed hybrid model provides pragmatic values of the parameters namely precision, ACC along with the Recall, and F1 such as 0.93, 0.98, 0.96, and 0.99 along with 0.94, 0.99, 0.93, and 0.99 respectively. In the future, there are vital possibilities to carry out more research in this field to develop new methods for Android malware detection.