Article Review #1
Cyberbullying and Psychological Stress among Female Employees
In this article, researches discuss how various psychological stressors pertaining to the deviant online behavior known as “cyber-bullying” adversely affect the mental health and ultimately the job performance of specifically female employees, as well as address the fact that females are statistically more susceptible to become victims of cyber-bullying over their male counterparts. This article pertains to various principles of social science such as social psychology in that the article discusses how negative interactions online in a professional work environment can lead to increased stress, depression, destroyed perception of organizational justice, and low job satisfaction and performance, among other factors. The study’s research suggests a multitude of hypotheses such as “perceived interactional justice is associated with job satisfaction” meaning that an employee who feels safe and secure will perform to or above standards, whilst an employee who does not trust her safety to the organization will have adverse psychological effects, as well as decreased job performance. The research methods used in this study include using a pre-existing questionnaire and modifying it to meet the needs of various aspects of the study to include psychological stress, organizational commitment, and job satisfaction. The types of data used included self-administered surveys that were disseminated amongst female employees and analyzed by various means to include software such as SPSS, and generated demographic analysis tables by means of the “Statistical Package for the Social Sciences (SPSS). Various concepts from our classroom studies pertain to this specific article to include psychology and human factors. The female victims of this phenomena were targeted specifically due to their gender and by those with means of anonymity and no fear of retaliation or adverse job impacts. Furthermore, low self-control, as well as aggression could be used to describe the offending parties as they are engaging in risk taking and negative, potentially criminal acts of deviant behavior in cyber-space and potentially putting their job at risk if identified. This topic of study relates to the challenges of marginalized groups, in this case, women in professional working environments, as it addresses the fact that women are statistically more likely to be cyber-bullied and deal with negative psychological stressors due to the abuse being suffered by the aggressor. This study helps bring to light the fact that marginalized groups are more likely to fall victim to cyber-crimes, in this case cyber-bullying, and that these crimes do in fact have negative consequences and are not “victimless.”
References:
Doghan, M., & Arshad, S. (n.d.). View of cyberbullying and psychological stress among female employees. https://cybercrimejournal.com/menuscript/index.php/cybercrimejournal/article/view/161/61
Testing human ability to detect ‘deepfake’ images of human faces.
In this article, researchers discuss speak upon how deepfake images of human faces has caused an increase into distrust of various media sources, most specifically sources of news. This plays into the social sciences of psychology, sociology, and criminology. These social sciences tie into the fact that it further extends the reach of cyber criminals in that it allows the creation of “new vectors of crime.” Furthermore, the scope of this technology means that just as we deal with phishing scams and robocalls today on a societal scale, we may also be dealing with deep or “shallow-fake” scams in the future. This technology will be able to tap into human psychology and sociology to allow for more victims to fall prey due to the nature of the scams in which a trusted person’s face, voice, and mannerisms can be replicated to fool a victim into a false reality, in turn causing them to provide various confidential information such as banking details, and encrypted passwords. Some of the studies conducted by researchers on this matter include showing study participants a mixture of both real and deepfake images. This study used a mixed dataset of “images generated by the StyleGAN1 algorithm [99], which was trained on the Flickr-Faces-High-Quality (FFHQ) dataset [100], (B) images generated by that same algorithm but as trained on the CelebA-HQ dataset [101], and (C) images generated by the PGGAN algorithm [102] as trained on the CelebA-HQ dataset.” As for the results and hypotheses found in this study, due to the small sample size and design of this study, the results tended to be inconclusive. Another study conducted regarding this research topic was to have participants report on how trustworthy they found various images, both real as well as deepfake. The data found from this study showed that participants found deepfake images to be significantly more trustworthy than their real counterparts. The hypothesis gathered from this study was that the difference was due to “deepfake faces looking more like average faces, which some research indicates tend to be more trustworthy.” Some of the concepts discussed in class that pertain to this study and the issue of deepfake technology is that victimization will be on a broad scale, moving from targeting elderly and the technologically inept, to targeting a larger group due to the more sophisticated tactics that cybercriminals will be utilizing. Furthermore, Machiavellianism may play a factor into these types of crimes as cybercriminals can use this end to “justify the means” in the form of scams involving making a victim believe that their loved ones are in danger with the use of deepfake videos and/or voices. Additionally, the three stages of fraud will come into play here just as they have regarding other well-known scams such as phishing emails, and robocalls in that victims will realize they have been duped and either try to rectify the damage or choose to not report the crime out of embarrassment. Marginalized groups in this study include those that have public status such as celebrities and politicians initially as they have already been targeted by these deepfake scams. However, this will soon expand to the public as the technology becomes more accessible and easier to use. This study has made multiple contributions to society as it outlines the fact that most normal and “non-trained” individuals cannot distinguish between real and deepfake images, and that these technologies will spread and become more dangerous, breeding further distrust in society and sources of legitimate news.
Sergi D Bray, Shane D Johnson, Bennett Kleinberg, Testing human ability to detect ‘deepfake’ images of human faces, Journal of Cybersecurity, Volume 9, Issue 1, 2023, tyad011, https://doi.org/10.1093/cybsec/tyad011
Article Review #2
“The Future of Cybercrime Prevention Strategies: Human Factors and A Holistic Approach to Cyber Intelligence”
Introduction
The topic at hand from the article I have chosen discusses various new and emerging technologies and trends that impact how we communicate in an online environment, as well as how these new technologies affect our likelihood of falling prey to cybercriminals. The article I have chosen further delves into this research topic by addressing how the “Internet of Things” plays a part in the rise of cybercrime, and further, how human factors are still one of the best ways to mitigate this issue.
Social Factors and Research Methods
Regarding social factors as they pertain to cybercrime in various elements of cyberspace such as social media, the sharing of intimate images, and emerging “blockchain systems”, the authors of the article chose a research approach in which they focus on various methods of research. When researching cybercrime in social media, the authors addressed “social demographic factors, victimization experiences, opportunity factors, and social context factors are associated with the public’s fear of crime on social networking sites” (Back, S., & LaPrade, J. 2019).
Secondly, when reviewing the sharing of intimate images, the authors approached this by conducting perception analysis’ and concluded that participants were more likely to share content with a romantic partner, with non-intimate content being preferred. Furthermore, they discovered that participants associated the sharing of intimate images with no consent was motivated by various factors such as revenge, or cyberbullying.
Lastly, the authors of the article researched blockchain technologies by investigating their strengths and weaknesses in regard to how they are theorized to make online environments more safe and secure. The authors summarized that understanding these strengths and weaknesses allowed for better security against cybercrime and other threats.
Class Concepts and the challenges of marginalized groups
This article pertains to various concepts discussed in class to include social factors related to social media. Examples of this being that various social media sites such as Facebook, Snapchat, Instagram and so on often contain wide age gaps based on the platform in question. For example, Snapchat has a wide age gap in which 65 percent of users are between the ages of 18-29, whilst only 2 percent of users are 65 and over. Furthermore, other forms of demographic shifts are seen on social media communities in which it is shown that a larger majority of Hispanic and Black Americans were reported to use Instagram. Conversely, only 35 percent of White Americans reported using this platform. To bring these concepts to fruition, the marginalized group that is being affected by the negative aspects of social media usage and cyberbullying tend to be younger in age. These younger users are more likely to take risks that leave them vulnerable to cyberbullying and other forms of cybercrime such as “revenge porn.” Furthermore, girls were more likely to be at risk of cyberbullying than their male counterparts.
Overall Societal Contributions
The overall societal contribution of this article lies in the author’s take that cyber intelligence and security require a holistic approach to tackle issues such as cybercrime. Whilst the author’s note the importance of various physical means of security such as encryption, they state that the most effective means of combatting cybercrime lies in a human centric approach. This means that we must fight cyber threats effectively through various human factors such as cyber security training, promoting good cyber hygiene, and as the study suggests, “building socially constructed norms for online users will improve human vulnerabilities to cybercrime” (Back, S., & LaPrade, J. 2019).
Conclusion
In conclusion, the selected article sheds light on the intricate relationship between emerging technologies, social factors, and the ever-evolving landscape of cybercrime. It emphasizes the significance of understanding how these factors come together in our online environments, and how they can leave us vulnerable to cyber threats. The authors utilize a multifaceted research approach, exploring social demographics, victimization experiences, and social contexts, to dissect the complex dynamics of cybercrime in the digital age.
The article’s exploration of social media platforms and their age demographics illustrates how different groups are exposed to distinct cyber risks. Marginalized groups, especially younger individuals, are more susceptible to cyberbullying and other cybercrimes. It is essential to recognize these disparities and the challenges they present in creating a safer digital environment.
One of the central takeaways from the article is the importance of a holistic approach to cyber intelligence and security. While technological safeguards like encryption are crucial, the most effective defense against cybercrime lies in human-centric strategies. This entails investing in cyber security training, promoting good online hygiene, and fostering socially constructed norms that improve users’ resilience to cyber threats.
References:
Back, S., & LaPrade, J. (2019). The future of cybercrime prevention strategies: Human factors and a holistic approach to cyber intelligence. International Journal of Cybersecurity Intelligence & Cybercrime, 2(2), 1-4. https://www.doi.org/10.52306/02020119KDHZ8339