As COVID-19 continues to spread worldwide, not only disrupting health and life but also business continuity up and down the supply chain, economic and cyber risk have taken on pandemic proportions, as well. Many enterprises are struggling just to keep essential services functioning as they send employees home to work with new, hastily procured technologies. At the same time, they’re battling a surge in cybercrime by threat actors seeking to take advantage of the chaos.

On May 29, 2019, the governor of Nevada signed into law Senate Bill 220, a new consumer privacy law. The new privacy law amended Nevada’s existing 2017 online privacy law. Effective October 1, 2019, the new privacy gives consumers the right to opt-out of the sale of their personal information.

In today’s constantly evolving cybersecurity threat landscape, you have to do everything possible and then some to protect your critical data assets. Performing a vulnerability assessment and implementing a vulnerability management program can help your organization effectively deal with cybersecurity vulnerabilities. However, it’s important to understand the difference between vulnerability assessment and vulnerability management.

COVID-19 has us reeling from health, social, and economic shocks, but this isn’t our first global crisis. It is, however, the first in which cybercrime plays a starring role. The world has faced several pandemics in the past 100 years—several influenza pandemics including swine flu (H1N1) and Avian, or bird, flu, and HIV/AIDS—as well as economic depression and a number of recessions.

An FCPA compliance program checklist outlines the things an American company needs to check when it wants to do business in a foreign country to ensure it follows the guidelines of the U.S Foreign Corrupt Practices Act (FCPA) of 1977. The FCPA is a federal law that aims to prevent all U.S. companies and their officers, directors, employees, and agents from making corrupt payments to foreign government officials to retain or obtain business.

National Institute of Standards and Technology (NIST) Special Publication (SP) 800-37 revision 2 is a Risk Management Framework for Information Systems and Organizations: A System Lifecycle Approach for Security and Privacy. NIST SP 800-37 rev 2 was published in December of 2018 and describes the Risk Management Framework (RMF) and guidelines on how to apply RMF to information systems.

Third-party vendor data breaches are becoming an epidemic for organizations that themselves have solid information security programs. The Ponemon Institute has proven year over year in its survey that the cost of third-party data breaches increases with each survey. Many struggle with how exactly to hold third-party vendors accountable and enforce the same rigid standards and controls that they consume internally. The big question is: how do organizations prevent third-party vendor data breaches?

If the coronavirus disease (COVID-19) pandemic has caused your enterprise to make a sudden, rapid switch from an on-premises-centered business model to a diverse, dispersed network of ad-hoc home offices, you may have let security and privacy measures slide a bit.

The Payment Card Industry Data Security Standard (PCI DSS) represents an information security standard designed for organizations that store, process, or transmit credit cards and are exposed to cardholder data. The card brands themselves have advocated for the PCI standard which is administered by the Payment Card Industry Security Standards Council (PCI SSC). Given organizations are interested in compliance, many ask the question “what are the PCI DSS Security Audit Procedures”?

The Factor Analysis of Information Risk (FAIR) framework was developed by Jack Jones. FAIR is a risk management framework championed by the open group that enables organizations to analyze, measure, and understand risk. The FAIR model evaluates factors that contribute to IT risk and how they impact each other while breaking down risk by identifying and defining the risk model. FAIR is most often used to establish probabilities for the frequency and magnitude of data loss.