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37th ACM Annual Symposium on User Interface Software and Technology (UIST)

作者： Lertvittayakumjorn, Piyawat Cai, Shanqing Dou, Billy Ho, Cedric Zhai, Shumin Google Mountain View CA 94043 USA

ISBN: (纸本)9798400706288

Capacitive touch sensors capture the two-dimensional spatial profile (referred to as a touch heatmap) of a fingers contact with a mobile touchscreen. However, the research and design of touchscreen mobile keyboards one of the most speed and accuracy demanding touch interfaces has focused on the location of the touch centroid derived from the touch image heatmap as the input, discarding the rest of the raw spatial signals. In this paper, we investigate whether touch heatmaps can be leveraged to further improve the tap decoding accuracy for mobile touchscreen keyboards. Specifically, we developed and evaluated machine-learning models that interpret user taps by using the centroids and/or the heatmaps as their input and studied the contribution of the heatmaps to model performance. The results show that adding the heatmap into the input feature set led to 21.4% relative reduction of character error rates on average, compared to using the centroid alone. Furthermore, we conducted a live user study with the centroid-based and heatmap-based decoders built into Pixel 6 Pro devices and observed lower error rate, faster typing speed, and higher self-reported satisfaction score based on the heatmap-based decoder than the centroid-based decoder. These findings underline the promise of utilizing touch heatmaps for improving typing experience in mobile keyboards.

关键词： mobile text entry touch interface key decoding machine learning

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Research on privacy and secure storage protection of personalized medical data based on hybrid encryption

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EURASIP JOURNAL ON INFORMATION SECURITY 2024年第1期2024卷 1-1页

作者： Lv, Jialu North Sichuan Med Coll Nanchong 637000 Peoples R China

Personalized medical data privacy and secure storage protection face serious challenges, especially in terms of data security and storage efficiency. Traditional encryption and storage solutions cannot meet the needs of modern medical data protection, which has led to an urgent need for new data protection strategies. Research personalized medical data privacy and secure storage protection based on hybrid encryption, in order to improve the security and efficiency of data storage. A hybrid encryption mechanism was proposed, which uses user attributes as keys for data encryption. The results show that the storage consumption of user attribute keys increases with the number of user attributes, but the consumption of hybrid encryption privacy storage technology is much smaller than that of traditional schemes. In the test, when the number of users increased to 30, the processing time first reached 1200 ms. During the increase in data volume, both test data and real data showed a brief decrease in attack frequency, but after the data volume reached 730-780, the attack frequency increased. It is worth noting that the performance of test data is better than that of real data. Personalized medical data privacy and secure storage protection based on hybrid encryption can not only effectively improve data security and reduce the risk of attack, but also greatly outperform traditional solutions in storage consumption and processing time. It has important practical significance for modern medical data storage protection.

关键词： Hybrid encryption Medical data Private data storage key decoding Data plain text

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