Article Review #1: Bugs in Our Pockets: Understanding Smartphone Security Vulnerabilities Joseph Sierra Old Dominion University CYSE 201S 11 February 2024 Introduction In this article review I will go over the research that was done about the vulnerability’s smartphones could potentially bring to an organization, the research questions that were presented, how this relates to the social science principles, and the data analysis that the researchers have gathered. Relevance to social sciences This topic relates to social sciences through cyber security as its to try and understand human behavior, the decisions that are made through the awareness and behaviors of the workers and hackers, and how an organization responds to the technological risks that come from many different sources including smartphones. Due to the world of cybersecurity always evolving in how security gets breached and how to prevent a breach it goes to show to importance and the impact that training can have for an organization. Research Questions The research questions that were brought up in the article were targeted towards the importance having good knowledge and security for the weak points and risk a smartphone could bring to organizations. For example, is if whether CSS can be a safe and effective to detect crime, the motivations for exploiting the smartphones, what mitigative strategies were effective, and the user awareness and knowledge for using the smartphones (Abelson et al., 2024). Research Methods The research methods that were used in the article were from the work of many others who have did research on this topic since its relevance is increasing as technology advances. Some of the works come from US National Academics of science, Engineering, and Medicine which goes over the technical approaches to access unencrypted content, the 2019 Carnegie Endowment for International Peace which shows a set of principles and guides on encryption policies, and on Paul Rosenzweig’s early analysis on the policy and technological issues that were raised by CSS (Rosenzweig P., 2020). Types of Data and Analysis Some examples of the types of data that are included are perceptual hashing, unencrypted data, service provider data, and user data (Abelson et al., 2024). The analysis that is used is the statistical information regarding vulnerability for data and the analysis on the security practices that different user groups have to protect against organized crime/hackers. Relation to Marginalized Groups Marginalized groups can also face adversity as they could be related to someone who is part of an organization they want to hack or CSS systems can even be reversed engineered and can be used on clients which are very hard to prevent once it has been done (Abelson et al., 2024). The information can be used to harass them, blackmail, or even frame individuals to make them become informers (Abelson et al., 2024). Overall Contributions to Society The research done in this article gives good information on the value of knowing the vulnerabilities not only smartphones could bring but other technology/programs like the CSS system. It shows the importance of having a secure practice for your technological use. This also shows the impact that it could have on organizations, small groups, or individuals if they do not have good cybersecurity measures. Conclusion In this article review it shows many crucial factors on how vulnerable smartphones can be, the risk that some programs can bring even though they may have some pros, the importance of having training on cybersecurity, and the impacts that could occur if the vulnerabilities are exploited which all of these are valuable to the advance technological state we are in. Sources Abelson, H., Anderson, R., Bellovin, S. M., Benaloh, J., Blaze, M., Callas, J., Diffie, W., Landau, S., Neumann, P. G., Rivest, R. L., Schiller, J. I., Schneier, B., Teague, V., & Troncoso, C. (2024). Bugs in our pockets: the risks of client-side scanning. Journal of Cybersecurity, 10(1). https://doi.org/10.1093/cybsec/tyad020 National Academies of Sciences, Engineering, and Medicine. Decrypting the Encryption Debate: A Framework for Decision Makers. Washington, DC: National Academy Press, 2018. https://doi.org/10.17226/25010 Carnegie Endowment for International Peace. Moving the encryption policy conversation forward. 2019. https://carnegieendowment.org/2019/09/10/moving-encryption-policy- conversation-forward-pub-79573 Rosenzweig P. The law and policy of client-side scanning. Lawfare. 2020. https://www.lawfareblog.com/law-and-policy-client-side-scanning (Rosenzweig P., 2020)
Article Review #1: Understanding the Role of Artificial Intelligence in Cybercrime Joseph Sierra Old Dominion University CYSE 201S 11 February 2024 Introduction This review goes over the article "Understanding the Role of Artificial Intelligence in Cybercrime". My review analysis will go over the multiple sides of research done, how this relates to the social sciences principles, the research questions, research methods, the data analysis that was done, how this impacts marginalized groups, and the overall societal contributions that understanding AI in cybercrime will bring. Relevance to Social Sciences Principles The article focused on how artificial intelligence (AI) in cybercrime relates with the social sciences principles because of human behavior, how society handles technological advancements, and the risk of using AI on illegal acts taken by criminals. It goes into insights from sociology, criminology, and psychology to understand why cybercriminals are motivated to take such actions, society impacts that AI attacks have done, and the morality of surrounding AI development and deployment. Research Questions or Hypotheses The article wants to investigate the use, capabilities, and the negative impacts of AI like creating fake images and videos to commit someone to criminal activities (Parti, n.d.). The research questions go into how cybercriminals utilize AI techniques in South Korea on cyber victims, the results of AI attacks in bypassing what was thought to be a good measure of security, and the potential consequences and impact it can bring to individuals, organizations, and society as a whole (Stavola & Choi, 2023). Research Methods The research method that was used was from multiple sources like Victimization by Deepfake in the Metaverse: Building A Practical Management Framework which is one of the two papers that won the 2023 International White Hat Conference and the paper Harnessing Large Language Models to Simulate Realistic Human Responses to Social Engineering Attacks: A Case Study (Parti, n.d.). Types of Data and Analysis The types of data that was used and analyzed in this article includes algorithms, tools, and the tactics in cybercrime, with the understanding of cybercriminal behaviors and motivations to do such acts (Asfour & Murillo, 2023). Analysis that was used to get this information is statistical examination of attack patterns and trends. Relation to Marginalized Groups The use of AI in cybercrime can have a bad impact on the marginalized groups, such as individuals from low-income backgrounds or minority populations. This is because of the low- risk that is taken by the criminals, if they were to commit these acts on an organization with funds it is more likely for them to get caught and punished. Overall Contributions to Society The article offers good insights into the evolving technological advancements made by AI- enabled cybercrime. By taking in AI's adoption, capabilities, and implications it could bring to the table in cybercrime, the study informs about the cybersecurity strategies that can be taken, regulatory frameworks that can be used, and how law enforcement should respond to the acts that are taken. Also, getting a good grasp of the negative impact and the vulnerabilities of marginalized groups, the article wants for better and more secure cybersecurity approaches that prioritizes the safety of everyone. Conclusion "Understanding the Role of Artificial Intelligence in Cybercrime" gives good insights into the always evolving AI-driven cyber threats. Taking in the multiple ways of the negative impacts AI could have, the article shows why we need to understand how cybercriminals get motivated to do such acts, tactics, and the negative impacts they will create, and to create strategies to prevent cyber crime being done, detecting the issue before it becomes a problem, and how we should respond including the law (Asfour & Murillo, 2023). Sources Parti, K. (n.d.). Understanding the use of artificial intelligence in cybercrime. Virtual Commons - Bridgewater State University. https://vc.bridgew.edu/ijcic/vol6/iss2/1/ Choi, K., Back, S., & Toro-Alvarez, M.M. (2022). Digital forensics & cyber investigation. Cognella. Stavola, J., & Choi, K. (2023). Victimization by deepfake in Metaverse: Building a practical management framework. International Journal of Cybersecurity Intelligence and Cybercrime, 6(2), 3-20. Asfour, M., & Murillo, J. C. (2023). Harnessing large language models to simulate realistic human responses to social engineering attacks: A case study. International Journal of Cybersecurity Intelligence and Cybercrime, 6(2), 21-49.