Cybersecurity and the Social Sciences

Journal Entries

The NICE Workforce Framework contains two categories that match my professional goals which are “Protect and Defend” and “Investigate.” The two cybersecurity roles that interest me most are Cyber Defense Incident Responder and Cyber Crime Investigator. The ability to work directly with threats by defending networks while performing threat analysis and digital forensic work attracts me deeply to this field. The analytical and hands-on nature of these responsibilities makes cybersecurity the most exciting field for me.

The “Oversight and Governance” category does not match my professional interests. My interest in security protocols technical execution exceeds my understanding of the administrative and strategic planning aspects which are essential for risk management and policy creation.

Empiricism in cybersecurity practice results in evidence-based security methods which eliminate theoretical assumptions. Security professionals can obtain precise threat landscape knowledge through organized data collection and analysis of network traffic and intrusion attempts and vulnerability scan results. The collected empirical data enables researchers to detect new attack methods and live malware versions which target computer systems. The system produces numerical data which evaluates security system operational effectiveness through performance measurements against real-world threats that firewalls and intrusion detection systems encounter. The data-driven method functions as a core instrument to develop security strategies and identify defense sectors that require maximum resource investment. Organizations can use predictive analytics and machine learning to process this data for future attack prediction and system security improvement. Incident data serves as a tool for organizations to maintain continuous improvement because it delivers critical information which helps them enhance their security position.

The researchers can use PrivacyRights.org data to study data breaches by identifying patterns and trends. The “Data Breach Chronology” enables them to track which organizations experience the most attacks as well as the methods hackers employ to penetrate systems and the types of data that get compromised (Social Security numbers, medical records, passwords).

The data contains critical information which enables experts to forecast upcoming data breach occurrences. The analysis of attack vectors and their corresponding industry targets becomes possible through statistical modeling and predictive analytics which reveal patterns between different variables. The healthcare sector faces an increasing number of ransomware attacks which suggest a possible future direction for the industry. The developed forecasting system enables organizations to create enhanced security protocols and distribute resources more effectively and design specific security plans for upcoming threats. Security research and policy development that depends on data needs the publicly available data as its fundamental foundation.