Measuring the level of cyber-security awareness for cybercrime in Saudi Arabia

Abstract

The revolution in the Information Technology (IT) field has led to a significant increase in the number of people connected to and utilizing the Internet. However, it has also introduced severe security risks: valuable information such as passwords, financial accounts, and other confidential data are considered attractive targets for attackers. Cyber-attacks against this infrastructure can not only lead to data leakage but can also have significant financial implications and even lead to loss of life. Consequently, to defend against such attacks, and considering that humans have a key role in these technologies, it is important to increase cyber-security awareness. This paper focuses on measuring the current level of cyber-security awareness in Saudi Arabia, in terms of cyber-security practices, level of awareness, and incident reporting, by means of an online questionnaire with 1230 participants. The questionnaire results showed that 31.7% used public Wi-Fi to access the Internet, 51% used their personal information to create their passwords, 32.5% did not have any idea about phishing attacks, 21.7% had been victim of cybercrimes while only 29.2% of them reported the crime, which reflects their levels of awareness. The paper concludes by offering recommendations based on analysis of the results to promote the level of awareness.

Implementasi Data Mining dengan Algoritma Naïve Bayes untuk Profiling Korban Penipuan Online di Indonesia

“…Tahapan pertama dalam penelitian ini dimulai dengan melakukan pra-penelitian, yaitu dengan mengamati fenomena penipuan secara daring menggunakan IM di Indonesia. Peneliti membuat sebuah dugaan mengenai karakteristik korban kejahatan online berdasarkan penelitian yang dilakukan oleh Alzubaidi di Arab Studi [17] tentang karakteristik dari korban kejahatan online yaitu sociodemografi korban, perangkat (gawai) yang dimiliki korban, dan aplikasi yang dimiliki korban.…”

“…Data mining juga bisa digunakan untuk membuat knowledge based system untuk memprediksi pola cybercrime dan juga pembuatan profiling [16]. Pembuatan profiling ini berguna sebagai cara untuk meningkatkan kewaspadaan pengguna internet terhadap cybercrime [17], [18]. Penelitian ini bertujuan untuk membuat profiling dengan menggunakan Algortima Naïve Bayes berdasarkan data sosiodemografi korban penipuan online melalui IM yang berdampak pada penipuan materi (uang) ataupun pencurian akun IM.…”

Advantageous comparison: using Twitter responses to understand similarities between cybercriminals (“Yahoo Boys”) and politicians (“Yahoo men”)

“…The perpetrators of “Yahoo Yahoo” are consequently called “Yahoo Boys” ( Ojedokun and Eraye, 2012 ; Melvin and Ayotunde, 2010 ). Equally, the term Yahoo Boys signifies that the cybercrimntlhich suggests that gender forces and socialization in society have a differential impact on the actions of men and women online ( Lazarus, 2019b ; Alzubaidi, 2021 ; Holt, Navarro & Clevenger, 2020 ; Ricciardelli & Adorjan, 2019 ; Zsila et al., 2019 ).…”

Mobile Applications for Cybercrime Prevention: A Comprehensive Systematic Review

“…In the labor field, many continue to opt for teleworking, online sales have increased notoriously, in the same way computer crimes in all its forms have also been increasing. A computer crime is a crime committed through the use of electronic tools and methods, against people or organizations [1,6]. It should also be noted that computer crimes have a tendency to become a long-term factor in the political and economic process, due to the lack of great success in counteracting them [4].…”

“…Being clear about the types of cybercrime and possible techniques to counteract them, would be of great help if these in turn are disseminated to users, so that they can avoid becoming victims of cybercriminals. In 2017 cybercrime costs amounted to approximately $600 billion in the United States, by 2019 they increased by 118% in the first half of the year leading to huge losses and financial implications, and by 2020 the statistics increased from 71% in mobile malware and 689% in PowerShell malware [1].…”