Masaki Narita
Iwate Prefectural University

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Examining a display-peeping prevention method that uses real-time UI part transparency linked to motion detection by video analysis Koki Kishibata; Masaki Narita
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.2565

Abstract

In recent years, the use of various information terminals such as smartphones and personal computers have become widespread, and situations where information terminals are used have become diverse. With increased opportunities to use information terminals outdoors and during travel, some users have been using peep-prevention filters, or software with an equivalent function, on their displays, in order to protect their privacy. However, such filters have problems with regards their effectiveness, ease of use, and the user being able recognize when they are vulnerable to peeping. Decrease in display visibility, unprotected angles, and the fact that it is difficult for users to notice when others are watching their screen, are some examples of such problems. Also, recently, many information terminals recently distributed have built-in cameras. In this paper, in order to solve the aforementioned problems, we propose to detect motion, video analyze , and transparentize part of the user interface (UI) in real time by using a laptop’s built-in camera. This method is enabled with low-load and can be applied to various terminals. Further, in order to verify the effectiveness of the method, we implemented a prototype, and carried out an evaluation experiment on experimental subjects. Results from the experiment confirmed that real-time UI transparentization is a very effective method for protecting privacy of information terminals.
Countermeasures against darknet localisation attacks with packet sampling Masaki Narita; Keisuke Kamada; Kanayo Ogura; Bhed Bahadur Bista; Toyoo Takata
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp1036-1047

Abstract

The darknet monitoring system consists of network sensors widely deployed on the Internet to capture incoming unsolicited packets. A goal of this system is to analyse captured malicious packets and provide effective information to protect regular nonmalicious Internet users from malicious activities. To provide effective and reliable information, the location of sensors must be concealed. However, attackers launch localisation attacks to detect sensors in order to evade them. If the actual location of sensors is revealed, it is almost impossible to identify the latest tactics used by attackers. Thus, in a previous study, we proposed a packet sampling method, which samples incoming packets based on an attribute of the packet sender, to increase tolerance to a localisation attack and maintain the quality of information publicised by the system. We were successful in countering localisation attacks, which generate spikes on the publicised graph to detect a sensor. However, in some cases, with the previously proposed sampling method, spikes were clearly evident on the graph. Therefore, in this paper, we propose advanced sampling methods such that incoming packets are sampled based on multiple attributes of the packet sender. We present our improved methods and show promising evaluation results obtained via a simulation.