Research

Catching malware outbreaks early keeps users, communities, enterprises, and governments safe. But if malware samples are scarce, can machine learning help analyze, detect, and end an outbreak?

Radio frequency (RF) technology is being used in operations to control various industrial machines. However, the lack of implemented security in RF communication protocols could lead to production sabotage, system control, and unauthorized access.

We looked into MQTT brokers and CoAP servers around the world to assess IoT protocol security. Learn how to prevent risks and secure machine-to-machine (M2M) communications over MQTT and CoAP in our research.

This research looks at the kinds of IoT projects being driven by global organizations, their key challenges and perceived threats, along with hard data outlining the frequency and type of attacks they’ve already experienced.

Securing energy and water should remain top priority in the continuing integration of the industrial internet of things in these critical sectors.

Evasive network threats pose serious risks to enterprises. Learn about malicious network flow clustering—a machine learning-powered method for addressing concerns on network threats.

To move forward, we need to look into the past to figure out what the best course of action is. Take a trip down memory lane with this infographic to see how far we've come in securing the digital world.

We delved into the rise and fall of Scan4You, the largest counter antivirus service in the underground, its operators, and the ties that bind them to other cybercriminals.

This research examines the oft-overlooked infection vectors in today’s healthcare networks: exposed medical devices and supply chain attacks.