Abstract
This study introduces a novel authentication methodology; it is based on pattern recognition of fingers size and pressure when users touch smartphone screen. By analyzing diagrams of these touches and applying data mining for the first time as an authentication technique, this paper presents three new approaches. First, an exact-range evaluation approach has been verified that size is more recognition consistency than pressure. Second, a pattern-range is a new technique reliance on size frequency position. At last, using a size-range has been facilitated the login. The association rules have been modified to work on finger touchscreen data files. To login, 94.1111% of 18 authorized users are succeeded and 98.9% of 20 unauthorized users are failed. Android device and Android studio are used. Size and pressure are normalized to 1; a training set is applied; the password is not considered.
Highlights
Authentication requirements are becoming a headache in the smart devices technology; this problem becomes more complicated because of the technology exponential development [1,2]
This paper is about studying the potential of a new technique over touch screen that it is able to detect finger size or pressure pattern endeavor to cast the password
First experiment is to compare between finger size and pressure properties in order to find out their suitability with pattern recognition
Summary
Authentication requirements are becoming a headache in the smart devices technology; this problem becomes more complicated because of the technology exponential development [1,2]. Focusing on smartphone, using password is inefficient due to the touchscreen limitation comparing to finger sizes, especially fat fingers [3]. Users are mostly leaning towards using 4-digit pin and reducing password length making smartphones more vulnerable than other devices [4]. Users prefer a semi-blind touchscreen with intuitive use in order to not interrupt their main tasks [5]. Many users are unwilling to use fingerprint authentication due to the high cost of additional hardware and compromising fingerprint by saving its information in the smartphone memory [7]. This paper proposes a new direction that considers fingers’ touchscreen information such as size and pressure as a gold mining iJIM ‒ Vol 14, No 19, 2020
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