Understanding Artificial Intelligence in Cybersecurity

Social Sciences

            This article based on understanding artificial intelligence in cybersecurity largely relates to the social sciences, mainly psychology and criminology. This article goes in depth about how artificial intelligence influences criminal motives and behaviors and different vulnerabilities to cybercrimes. They do this by using theories such as the Routine Activities Theory and Big Five Personality Traits Model. The research done in this article explains multiple preventative measures that we can take as individuals or even organizations that were informed by interdisciplinary perspectives. In total, it highlights the importance of evidence-based policy making and interdisciplinary collaboration while discussing and trying to find ways to stop evolving cyber threats, which only grow stronger and more effective with each passing day.

Hypothesis

            Throughout this article, multiple research questions and hypothesis come up. One of the main questions being, what are the underlying motivations driving offenders to commit interpersonal cybercrimes involving deepfakes online? The article goes on to say that offenders usually make and abuse these deepfakes and post them online for financial gain or sexual pleasure reasons. The main age group that is known for doing these cybercriminal deepfakes and people in their younger twenties, and this is due to them having better understanding of newer technologies and the easy access online platforms offer. Theres multiple other research questions and hypotheses that come up that largely must deal with deepfakes and plenty of other things. These things range from motives of potential offenders to vulnerabilities of potential victims and how good their security measures are against these offenders.

Research Methods

            This article is made by a very well-established organization, and due to this, they have multiple research methods that they use. This includes quantitative and qualitative research methods. Qualitative research methods were used majorly in study one and were used to gain testimonies and statements around deep-fake cybercrimes online. Qualitative research methods are used to find patterns or themes within statements from people and include questioning different people to get answers based on your research questions. The next research method, quantitative, was mainly used in the second study by categorizing individual personality traits using the Big Five Personality Traits Model that was talked about earlier when we discussed social sciences. Researchers use these personality traits to understand individuals’ relationship with being influenced by social engineering attacks.

Types of Data and Analysis

            The types of data and analysis done was both depending on the study that was done. The first study had a lot to do with deepfakes and how people were affected and victimized by it. The data for this study was gotten through interviews and testimonies through experts in the field, and the researchers came to an analysis by looking for the common theme in what the experts were saying about this research question. The second study was based on social engineering attacks and the information for this study was gathered through gaining information about people’s personalities based on how they responded to fake messages that were send to them. The analysis was done by sorting people into their different respective personality types that the researchers discovered, and they say which personality type was more likely to fall for scams sent to them.

Article Relating to Class

            This article based on AI relates to concepts in our class in many ways. First, this article heavily relates to what we always talk about not just in class, but cybersecurity in general, which is risk management. By analyzing how people respond to things and how easy it is for people to get influenced by messages, were able to see how people respond to cybercrime based on their personality traits, which the article highlights the importance of human intelligence into risk management, which is something we talk about all the time, that no matter how many warning we give, there is always the human factor. Some other concepts that are in the article that relate to our class are ethical considerations when being online, and following policies and regulations posted by organizations or individuals.

AI Relating to Marginalized Groups

            There are many ways in which the topic of this article relates to challenges and concerns for marginalized groups. The first being that they are much more vulnerable to exploitation, because they are much more willing to take risks based on the position society has put them. This may cause them to be more vulnerable to exploitation and may make them a much bigger target by these groups. Another challenge is for marginalized and groups at a disadvantage is that they don’t get as big of a representation as people would from a higher-class group in society. Their voices are not as loud so their message based on what these AI deepfakes and scams are doing in their community may not be heard as much as in higher class societies, so not as much may be done to help them, which is a major challenge.

Societal Contributions of this Study

            This study and article contribute to our everyday society in many ways. This includes making all of us more aware of emerging cyber threats such as these cyber engineering attacks and deepfakes that can do much harm to individuals and groups. This article improves societies cybersecurity awareness as I just discussed, gives us improved insights for policymakers and regulators, and also helps us society as a whole advance research and innovations in the field.

Conclusion

In summary, these studies discussed in these articles shed a much needed in depth light on these topics based on how AI in changing and redefining cybercrimes. They help us gain a new understanding of new cyber engineering and deepfakes that we may not have known or known much about before. By learning about who is the most vulnerable and how we can better protect ourselves, this study along with others like it can make a huge difference in keeping the digital world safer then without.

References

Understanding the use of artificial intelligence in Cybercrime. (n.d.). https://vc.bridgew.edu/cgi/viewcontent.cgi?article=1170&context=ijcic