The AI cybersecurity impact for IoT
Insights into how the security community is working to secure IoT devices today, and how AI will enhance those efforts over time.
Practical application of artificial intelligence that can transform cybersecurity
There is tremendous opportunity to use AI—particularly machine learning—to improve the efficacy of cybersecurity, the detection of hackers, and even prevent attacks before they occur.
Enhancing Office 365 Advanced Threat Protection with detonation-based heuristics and machine learning
Office 365 Advanced Threat Protection (ATP) uses a comprehensive and multi-layered solution to protect mailboxes, files, online storage, and applications against a wide range of threats.
A worthy upgrade: Next-gen security on Windows 10 proves resilient against ransomware outbreaks in 2017
Adopting reliable attack methods and techniques borrowed from more evolved threat types, ransomware attained new levels of reach and damage in 2017.
Application fuzzing in the era of Machine Learning and AI
Proactively testing software for bugs is not new. The earliest examples date back to the 1950s with the term “fuzzing.” Fuzzing as we now refer to it is the injection of random inputs and commands into applications. It made its debut quite literally on a dark and stormy night in 1988.
How future policy and regulations will challenge AI
I recently wrote about how radical the incorporation of artificial intelligence (AI) to cybersecurity will be. Technological revolutions are however frequently not as rapid as we think.
Rules-making in technology: Examining the past and predicting the future
Are the rules and regulations being put in place today, from the Chinese cybersecurity law to the EU’s General Data Protection Regulation (GDPR), going to be appropriate for the world 10 years from now? And if not, should this be of concern? To answer these questions, we need to learn from the past.