Penerapan Metode Technology Threat Avoidance Theory Terhadap Tingkat Kesadaran Data Privasi Pengguna Media Sosial

• Published in: Journal of Information System Research (JOSH) Vol. 4; no. 3; pp. 1026 - 1032
• Main Authors: Rifai, Achmad, Meliyani, Ade, Chyntia, Putri, Sakti, Ichtiar Akbar
• Format: Journal Article
• Language: English
• Published: 30.04.2023
• ISSN: 2686-228X; 2686-228X
• DOI: 10.47065/josh.v4i3.3081

Theft of credential data by entering a username and password on the login page until the account is open. The authentication process in applications and the web is used to identify ownership of user data, this is because there is a vulnerability to attacks in the use of unsafe usernames and passwords. There are several security issues, one of the most common being passwords. Most systems use passwords to verify user identity. However, these passwords come with major security issues as users tend to use ones that are easy to guess, use the same password across multiple accounts, write it down and store it on their devices. Hackers have many options using which to steal passwords or hack user accounts such as credential stuffing, phishing, password.spraying, bruce force, prior data breach / reused passwords, password reset, keystroke logging and local discovery. To overcome security attacks, Multi-Factor Authentication (MFA) techniques provide higher security guarantees. Public awareness to protect identity information is fundamental, identity theft can go through various channels and ways and this needs to be emphasized. Self-efficacy (security awareness), behavioral intention, avoidance motivation and avoidance behavior are factors that influence the object. This factor analysis aims to determine the level of awareness and behavior patterns of social media users. Factor analysis used the MANOVA method as data analysis and the TTAT model. Based on the results of the MANOVA tests of between – subjects effects, the factor of favorance motivation (r = 0.499 and Sig. 0.000) and behavioral intention (r = 0.427 and Sig. 0.000). There is a link between these factors, so users must avoid data theft through security measures using multi-factor authentication (MFA).