Breaking Botnets: A Quantitative Analysis of Individual, Technical, and Strategic Defense Factors
Introduction
The article Breaking Botnets looks at how botnets can be stopped using different types of defenses. Botnets are just groups of infected devices controlled by an attacker to launch an attack. The study connects to the social sciences by kind of showing how human behavior, and company choices, and technical tools all play a role in fighting against cybercrime. This review will explain the research focus and methods, even its contributions while also connecting it back to social sciences.
Relation to Social Sciences
I realized that this article is tied to social sciences, especially behavioral studies. It shows that fighting cybercrime specifically is not just about the technology but also about people and institutions. Like, decisions made by people and by organizations both influence how effective defenses against botnets are. The research points out that solutions to this type of crime must also consider social behavior as much as it does the technical measures.
Research Question and Variables
The main question is which individual, technical, and strategic actions help reduce botnet activity? It was said that with better defenses, better cooperation and with more responsible user activity and behavior then that will lower the success and lifespan of botnets. The independent variables here would be the person behind the computer, firewalls, and updated machines, along with defenses like collaboration and information sharing across countries, and other actions like password changing. The dependent variable here is the effectiveness of the disruption of botnets which can be measured by outcomes. For example, if the botnet size was reduced, or shorter lifespan of the botnet and even fewer infections.
Data Analysis
The author used quantitative methods to analyze botnet activity and defenses. You can
tell that the study relies on real data from monitoring systems, defense logs, and publicly
available databases for cyber incidents. There are statistical models including correlation analysis and regression, are used to find answers or test their hypotheses and provide evidence for finding which strategies are best.
Connection to Class
The article’s findings connect to theories discussed in class like the recent General
deterrence theory, that suggests that preventive actions discourage criminals actions. In this case, the stronger the defense and coordinated strategies act as deterrents against botnets. The study also has ideas links with neutralization theory, where inaction or weak defenses might be rationalized by organizations until major harm happens. By showing that strategies reduce risk, the article goes over the importance of behavioral responses alongside technical fixes.
Challenges

Even though the article does not focus on marginalized populations, its findings show inequalities in cybersecurity resources. Bigger organizations and governments might have the capacity to invest in sophisticated technical defenses and participate in sharing strategies. Though, under resourced places and developing countries may be more vulnerable to botnet attacks. This is a concern because of the unequal access to protection and the burden cybercrime places on marginalized groups. The study indirectly calls for greater support for less resources people for better security.
Contributions to society
The study makes important contributions by moving beyond speculation to evidence-
based recommendations. By finding which factors most effectively disrupt botnets, the article provides actionable insights for policymakers, organizations, and cybersecurity professionals. It underscores the need for global cooperation, strong technical defenses, and consistent individual security practices. These findings not only guide cybersecurity strategy but also contribute to safer online environments for society at large. Ultimately, the article emphasizes that combating cybercrime requires a combined effort of technical innovation, individual responsibility, and
collective governance.
Conclusion
Breaking Botnets Fills the gap between technical cybersecurity research and social
science. This article shows how human and institutional behavior directly impacts the
effectiveness of digital defenses. Its quantitative approach really shows which defense strategies work best against botnets, while its implications extend to issues of equity and governance and social responsibility. The study contributes important evidence for understanding and addressing one of the most pressing challenges in cybersecurity.

Article Review #2 Investigating the Intersection of AI and Cybercrime: Risks, Tools & Techniques
Introduction
This article “Investigating the Intersection of AI and Cybercrime: Risks, Tools & Techniques” by Shetty et al. (2024), from the International Journal of Cybersecurity Intelligence & Cybercrime, is really about how artificial intelligence affects both cybercriminals and cybersecurity experts. The authors explain how hackers use AI to make smarter attacks and how security teams use AI to also stop them. The topic is important because it shows how new technology changes the way people commit and prevent cybercrime.
Relation to Social Science
This article relates to social science because it focuses on human behavior and motivation behind cybercrime. It looks at why people use technology for harmful reasons, such as money, power, or curiosity. It also shows how society reacts to new technology and the ethical choices that come with it.
Research Questions and Variables
So, the main research question was, How does AI influence cybercrime and cybersecurity? The authors believed that AI helps both sides, making cyberattacks stronger but also improving defenses. The independent variable is the use of AI technology, and the dependent variable is the number and success of cybercrime incidents.
Methods Used
The researchers used both qualitative and quantitative methods. They studied real cyberattack cases, analyzed data from 2022 to 2024, and interviewed cybersecurity professionals. This helped them understand both the numbers and personal opinions about AI in cybersecurity.
Data and Analysis
The article used data from reports, surveys, and security databases. The authors found that AI type attacks have increased, and even though AI helps detect attacks faster, it also
allows hackers to create more advanced threats.
Connection to Class Concepts
The article connects to topics from class like vulnerability management and the human side of cybersecurity. It shows that technology alone can’t fix cybersecurity issues, understanding human actions and ethics is just as important.
Marginalized Groups
Smaller companies and lower income users are more at risk because they usually can’t afford strong security tools. This shows how the “digital divide” makes some groups more vulnerable to AI type cybercrime.
Conclusion
Overall, this article helps readers understand that AI is changing cybersecurity in both good and negative ways. It shows the importance of using AI responsibly and combining technology with ethics and social understanding. the author suggests that experts, policymakers, and educators must work together to build a safer and fairer digital world.
Reference
Shetty, S., Rahman, A., & Lin, T. (2024). Investigating the intersection of AI and cybercrime: Risks, tools & techniques. International Journal of Cybersecurity Intelligence & Cybercrime, https://vc.bridgew.edu/ijcic/vol7/iss2/3/