TY  - CONF
Y1  - 2018///
SN  - 9781450354141
PB  - Association for Computing Machinery
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048486620&doi=10.1145%2f3185089.3185093&partnerID=40&md5=0a4777a62816bd8cced77f731bdbbd79
A1  - Tachmammedov, S.
A1  - Hooi, Y.K.
A1  - Kalid, K.S.
EP  - 188
AV  - none
N1  - cited By 4; Conference of 7th International Conference on Software and Computer Applications, ICSCA 2018 ; Conference Date: 8 February 2018 Through 10 February 2018; Conference Code:136540
N2  - A potential application of smartphone is as a tool to prevent attendance cheating. This paper proposes an automated multi-factor analytics using common smartphone features to identify cheating. The first factor is using Quick Response (QR) code as a unique token for validation. The second factor checks for the phone's unique International Mobile Equipment Identity (IMEI) number. The third factor checks attendance time using server time. The fourth factor is geo-location of the student. Algorithm analyzes geolocation statistical variance after passing the first two factors. The algorithm is implemented as a proof of concept in a typical university lecture and lab attendance taking. The proposed algorithm has shown promising efficiency and feasibility of implementation. User survey has indicated reasonable acceptance and potential issues. © 2018 Association for Computing Machinery.
KW  - Application programs; Data handling; Global positioning system; Smartphones; Telephone sets
KW  -  Cheat-proofing; Mobile equipments; Multi factors; Proof of concept; QR codes; Quick response code; Statistical variance; User surveys
KW  -  Administrative data processing
TI  - Automated multi-factor analytics for cheat-proofing attendance-taking
ID  - scholars10511
SP  - 183
ER  -