In this paper, we propose a novel gate delay time mismatch tolerant time-mode signal accumulator whose input and output are represented by a time difference of two digital signal transitions. Within the proposed accumulator, the accumulated value is stored as the time difference between the two pulses running around the same ring of a delay line, so that there is no mismatch between the periods of the two pulses, thus the output drift of the accumulator is suppressed in principle without calibrating mismatch of two rings, which is used to store the accumulated value in the conventional one. A prototype of the proposed accumulator was fabricated in 180nm CMOS. The accumulating operation is confirmed by both time and frequency domain experiments. The standard deviation of the error of the accumulating operation is 9.8ps, and compared with the previous work, the peak error over full-scale is reduced by 46% without calibrating the output drift.

Information leakage is a significant threat to organizations, and effective measures are required to protect information assets. As confidential files can be leaked through various paths, a countermeasure is necessary to prevent information leakage from various paths, from simple drag-and-drop movements to complex transformations such as encryption and encoding. However, existing methods are difficult to take countermeasures depending on the information leakage paths. Furthermore, it is also necessary to create a visualization format that can find information leakage easily and a method that can remove unnecessary parts while leaving the necessary parts of information leakage to improve visibility. This paper proposes a new information leakage countermeasure method that incorporates file tracking and visualization. The file tracking component recursively extracts all events related to confidential files. Therefore, tracking is possible even when data have transformed significantly from the original file. The visualization component represents the results of file tracking as a network graph. This allows security administrators to find information leakage even if a file is transformed through multiple events. Furthermore, by pruning the network graph using the frequency of past events, the indicators of information leakage can be more easily found by security administrators. In experiments conducted, network graphs were generated for two information leakage scenarios in which files were moved and copied. The visualization results were obtained according to the scenarios, and the network graph was pruned to reduce vertices by 17.6% and edges by 10.9%.