Murray State University’s Master of Science (M.S.) in Cybersecurity Management online program curriculum includes a deep dive into the foundation of protecting networks and data through its Information Security Risk Management course. The core course focuses on developing risk assessments based on compliance frameworks to prevent cyberattacks and other unauthorized breaches of digital assets.
As cybercriminals adopt advanced technologies such as artificial intelligence, successful attacks set a record in 2023, according to the Identity Theft Resource Center (ITRC). It recorded more than 3,000 personal data breaches, affecting more than 350 million individuals — a 78% increase over 2022. The favorite targets were healthcare, financial services and transportation organizations.
The ITRC reported a significant uptick in the number of supply chain attacks in 2023. The strategy exploits weaknesses in organizations’ supply chains, often through vendors with inadequate defense protocols, to penetrate their cybersecurity measures. Artificial intelligence (AI) integration boosts supply chain attack precision and stealth by enhancing target identification, enabling adaptive malware and generating realistic phishing content.
Automating these processes makes the attack more sophisticated, elusive and dangerous. “The combination of more data from more compromises, along with revolutionary technology, means we must consider significant changes to how we protect personal information and respond when it is compromised,” the ITRC warns.
What Is Cyber Risk Management?
Cyber risk management is a multi-stage process on which an effective, resilient digital defense system rests. The stages include identifying vulnerabilities in an organization’s IT infrastructure, assessing them according to severity and developing protocols to mitigate damage in the event of a successful breach.
Data analytics plays a crucial role in cyber risk analysis by providing real-time insights and enhancing threat detection capabilities. That capacity enables organizations to analyze vast amounts of data to identify unusual patterns and anomalies in data flows that may be early warnings of probes to find defensive weaknesses. Predictive analytics allow cyber defense teams to anticipate and proactively address emerging threats, while descriptive and diagnostic analytics help understand past security events and their root causes.
Cybersecurity management professionals must know about risk management and data analytics to effectively prevent cyberthreats. “In today’s digital world, the work of protecting company data is never-ending. As technology evolves, so do the new threats, meaning security work is never over,” according to Sentinel One.
What Are Cybersecurity Risk Frameworks?
The cybersecurity consultant Safe recommends building risk assessments and the resulting defenses on best-practices frameworks. Among the 10 most effective frameworks identified by the global cybersecurity vendor, the National Institute of Standards and Technology Cybersecurity Framework (NIST CSF) is the most widely used.
Its popularity derives from its flexibility, comprehensive approach and adaptability across industries. For instance, its cybersecurity language bridges the gap between business and technical teams to ensure defense processes align with overall organizational goals. Its risk-based approach enables organizations to allocate resources effectively, and its alignment with other standards streamlines compliance efforts. Additionally, NIST CSF is recognized globally as a benchmark for cybersecurity best practices, making it attractive for businesses seeking to build trust with partners and customers.
How Are Quantitative and Qualitative Methodologies Used in Risk Assessment?
On the one hand, quantitative uses data and statistical analysis to assign monetary values to potential losses in the event of a successful attack. The Factor Analysis of Information Risk (FAIR) model is a widely used quantitative framework that calculates risk exposure based on threat frequency, vulnerability severity and asset value.
Qualitative methods rely on expert judgment and descriptive scales to identify and prioritize risks. These assessments often categorize risk impact as low, medium or high, offering a broader understanding of cybersecurity issues across different business perspectives.
Both provide benefits to cybersecurity. The hybrid approach mentioned by Proto Labs enhances risk identification, analysis and prioritization. “Organizations may also choose to combine both approaches to manage their cyber risks more effectively in an increasingly complex threat landscape,” it recommends.
What Are the Elements of a Risk Mitigation Plan?
The comprehensive M.S. in Cybersecurity Management program also explores the critical need for a mitigation plan based on risk assessment results. An effective mitigation plan, according to Pure Storage, closes identified vulnerabilities through education, continuous evaluation and maintaining hardware and software. “By taking proactive steps, including testing and updating these measures, businesses can minimize the impact of ransomware attacks and safeguard their operations, data, and reputation,” it says.
For example, if a risk analysis found that the organization ran outdated software and unpatched systems, the mitigation plan would direct a rigorous patch-management system. Similarly, if the cybersecurity team detected insufficient employee training on phishing email detection — a primary vector for ransomware distribution — the plan would specify comprehensive employee cybersecurity awareness training and testing.
Professionals with cybersecurity knowledge — including the ins and outs of cybersecurity management — are poised to excel in the increasingly digitized world. Murray State’s program provides graduates with the necessary technical and leadership skills to protect information and organizations against cyberthreats of all types.
Learn more about Murray State University’s online M.S. in Cybersecurity Management program.
