Real-time and intelligent private data protection for the Android platform

Hung, Shih-Hao; Hsiao, Shuen-Wen; Teng, Yu-Chi; Chien, Roger

doi:10.1016/j.pmcj.2015.08.006

Cited by 9 publications

(3 citation statements)

References 2 publications

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“…As AR for COVID-19 is ready to be used in homes or various long-term educational and healthcare environments, commercially available AR platforms can assess, enhance, and implement these advanced AR systems much more accessible. Furthermore, as the quantity of smartphones grows, so do their features and capabilities [54][55][56]. This pattern is expected to continue consumption while also making AR technology easier to develop and access.…”

Section: Discussionmentioning

confidence: 99%

A New Augmented Reality System for Calculating Social Distancing between Children at School

et al. 2023

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Social distancing is one of the most important ways to prevent many diseases, especially the respiratory system, where the latest internationally spread is coronavirus disease, and it will not be the last. The spreading of this pandemic has become a major threat to human life, especially to the elderly and people suffering from chronic diseases. During the Corona pandemic, medical authorities were keen to control the spread through social distancing and monitoring it in markets, universities, and schools. This monitoring was mostly used to estimate the distance with the naked eye and interfere with estimating the distance on the observer only. In this study, a computer application was designed to monitor social distancing in closed areas, especially in schools and kindergartens, using a fast, effective and unobtrusive technique for children. In addition to this system, we use augmented reality to help to determine the location of violation of social distancing. This system was tested, and the results were accurate exceeding 98.5%.

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Section: Discussionmentioning

confidence: 99%

A New Augmented Reality System for Calculating Social Distancing between Children at School

et al. 2023

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“…In samples of the virus, the malicious virus samples is still very high in proportion, which was up to 52%, more 23 per cent than last year. In the virus infection of users, rogue behavior of the virus infection users accounted for the highest proportion, amounting to 46%; as for the virus infection users in privacy theft, the proportion increased significantly, which is up to 24%, than last year rose about 85%; the proportion of the virus infection users of SMS hijacking decreased significantly, accounted for only 3%, which dropped 81% compared the last year (Hung et al, 2015). Figure 3 shows the investigation of virus infection.…”

Section: Figure 1 2014 Android Devices Infected Trendsmentioning

confidence: 97%

The Design and Development of the Vulnerability Detection System of Android Platform

2016

Revista de la Facultad de Ingeniería

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With the share of Android market increasing continuously, the Android mobile terminal provides convenience for the users. At the same time, it is encountering more and more secure challenges and threats, which has a serious threat to the safe use of users. Although Android has already a good security mechanism to ensure the safe use of the users, in the interest of huge commercial interests, a large number of attackers attack Android users in a variety of ways because of vulnerabilities of system and software. Even though the system module and access control system has been designed by Android, the attacker can still fight with the vulnerabilities of system or third party bugs, which has good for making illegal use some of its application beyond the permission function. It not only has a greater security threat, but also has certain concealment. The present study analyzes and innovates previous researches, put forward a new communication hole detection method based on controlling flow detection and Android permission sensitive dictionary matching, and on this basis, completed the high degree of automation, high detection efficiency design and development of test software.

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“…Cui et al [7] performed bytecode modification and taint analysis on applications during application installation to obtain data leakage paths between components. Hung et al [8] analyzed the interactions between a user and an app based on TaintDroid [9] , using the dynamic taint propagation to track suspicious data streams, and indicated the risk of user privacy leakage. Jia et al [10] proposed a static analysis tool that could effectively identify and characterize vulnerable open port usage in Android applications and could perform a vulnerability analysis on a dataset with over 100K Android applications.…”

Section: Related Workmentioning

confidence: 99%