Social networks have been a hot topic for many years, allowing its billions of users to connect and share all of their daily life occurrences. While social networking sites can connect the world in a manner in which wasn’t previously available, the treasure-trove of information available on a vast majority of the population can be utilized as a weapon. In Samar Muslah Albladi and George R.S. Weir’s article, “Predicting individuals’ vulnerability to social engineering in social networks,” a study is presented to further understand the relationship between social media networks and users’ vulnerability to social engineering attacks.
The results of the study provided a rare glimpse into the correlation between an individual’s social networking usage and their vulnerability to cybercrime. For Facebook, it was found that users’ involvement level has a significant impact on their susceptibility to social engineering. Furthermore, the number of Facebook friends a participant had increased their likelihood to be socially engineered; for example, these users were more likely to accept a friend request from a stranger. “Around 48% of the participants in this study stated that they know less than 10% of their Facebook network personally” (Albladi, Weir, 2020). While it may seem obvious that those who are less tech-savvy would be more acceptable to social engineering, the correlation between the date a user joined Facebook and their vulnerability, found that the longer the user had been on Facebook, the less likely they were to become a victim of cybercrime.
While it was discovered that the motivation for a person to use social networks did not influence their social engineering vulnerability, this motivation directly affects user behavior such as their involvement on the websites, their trust with the platforms, as well as any previous experiences with cybercrime (Albladi, Weir, 2020). As we live in a world in which we and our technology are interconnected, the population on social networking sites is quite similar to the rising security concerns of the Internet of Things (IoT). The more connected we get, the ability to share and steal valuable data rises as well. By performing studies on how social engineering works, as well as identify vulnerable users, we can further understand and defend against the cybercrime of tomorrow.
The authors of this article had a clear purpose to their research and experiment in that they wanted to shed light on the dark world of social engineering while focusing on social media; this purpose was accomplished by providing results that were carefully obtained and enforced with supporting facts and data. While the article excels in the presentation of the research-derived results of the study, it should be known that using a scenario-based experiment instead of a real-world scenario limits the authenticity of the end-result of the survey. Furthermore, the fact that the study was only focused on those in the academic community also lessens the impact of the entire experiment. The authors did an excellent job appealing to readers by utilizing popular terms, conditions, and questions that are abundant in both social media and social engineering. Through the information in this study, the factors in which increase our vulnerability to social engineering attacks can be reduced, both in our professional and personal lives.
The conceptual model the research of this article provided showcases the user-related factors that predict users’ vulnerability to social engineering attacks by using a scenario-based experiment (Albladi, Weir, 2020). Through the use of an online-questionnaire using the Qualtrics online survey tool, subjects were asked numerous questions regarding the participants’ demographics, a scenario-based experiment, as well as several queries to assess the individuals’ risk, competence, trust, and motivation. The study found that those who are more active on social media were potentially more vulnerable to social engineering attacks, especially those with reduced experience on the technology and associated cybercrime. Furthermore, having a large number of Facebook friends suggest that the user is more prone to accepting requests from strangers. With the abovementioned results, a participant’s vulnerability to social engineering attacks can be found.
Hadnagy, C., & Wozniak, S. (2018). Social Engineering; The Science of Human Hacking (2nd ed.). Newark: John Wiley & Sons, Incorporated.
Albladi, S.M., Weir, G.R.S. (2020). Predicting individuals’ vulnerability to social engineering in social networks. Cybersecurity 3, Article 7. Retrieved March 26, 2020, from https://doi.org/10.1186/s42400-020-00047-5.