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In order to improve the security strength in the password based user authentication, in which the security vulnerability is increased while the same password is repeatedly used, the OTP(One-Time Password) system has been introduced. In the OTP systems, however, the user account information and OTP value may be hacked if the user PC is infected by the malicious codes, because the user types the OTP value, which is generated by the mobile device synchronized with the server, directly onto the user PC. In this paper, we propose a new method, called DTOTP(Dual Transmission OTP), to solve this security problem. The DTOTP system is an improved two-factor authentication method by using the dual transmission, in which the user performs the server authentication by typing the user account and password information onto the PC, and then for the OTP authentication the mobile device scans the QR code displayed on the PC and the OTP value is sent to the server directly. The proposed system provides more improved security strength than that of the existing OTP system, and also can adopt the existing OTP algorithm without any modification. As a result, the proposed system can be safely applied to various security services such like banking, portal, and game services.

As the surveillance CCTVs are increasing every year, big data image processing for the CCTV image data has become a hot issue. In this paper, we propose a Hadoop-based big data image processing technique to recognize a vehicle number from a large amount of automatic number plate images taken from CCTVs. We also implement the vehicle route tracking system that displays the moving path of the searched vehicle on Google Maps with the related information together. In order to evaluate the performance we compare and analysis the vehicle number recognition time for a lot of CCTV image data in Hadoop and the single PC environment.

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