The old defenses against cyberattacks–firewalls, antivirus programs and operating system patches–worked well when the security perimeter was the office. Now that remote work is here to stay and more devices are connected to company networks, protecting networks is more complicated. Read on to learn how defense in depth, an integration of individual tools, can help you better protect your technological assets.
With an increasing number of devices connected to networks, as well as increasingly sophisticated cyber attacks, the threat landscape is incredibly broad. In 2003, the US government and various industries collaborated and created Cybersecurity Awareness Month. Each October, the spotlight falls again on keeping your system secure and being secure online. Read on to learn about becoming not just aware, but prepared, all year long.
With the recent wildfires in Maui, disaster preparedness is (or should be) once again top of mind. Aside from the physical recovery of businesses, integrity of their data (the lifeblood of the business) is at stake. Even if you think you’re prepared, you may not be. Read on to learn more about where to start in your disaster recovery planning.
While cloud computing is now a common way to provision computing resources and outsource IT functions, security can be a (perceived) obstacle to adoption. Cloud security can be a shared responsibility, however, between the customer and provider. Read on to learn more about what to expect from a current or prospective provider, and what you can do yourself to stay secure.
Artificial Intelligence seems to be the hot topic nowadays, in the business world and the world at large. Many of us use the technology, whether we know it or not. Visitors to a website see that chat window pop up, and it seems like a real person is on the other end. Because of AI, it is often a chatbot simulating personal interaction.
Artificial Intelligence (AI) has been used in some form for several years. Typical applications of AI include advanced-analytics and machine learning algorithms used to perform numerical and optimization tasks like predictive modeling. Generative AI, in contrast, has matured quickly due to enormous financial investment.