Automated incident response in Office 365 ATP now generally available
Powerful automation capabilities help improve the effectiveness and efficiency of investigating and responding to Office 365 alerts.
CISO series: Better cybersecurity requires a diverse and inclusive approach to AI and machine learning
A collaborative, inclusive approach to creating AI and machine learning models can help increase your resilience to cyberattacks.
New machine learning model sifts through the good to unearth the bad in evasive malware
Most machine learning models are trained on a mix of malicious and clean features. Attackers routinely try to throw these models off balance by stuffing clean features into malware. Monotonic models are resistant against adversarial attacks because they are trained differently: they only look for malicious features.
The evolution of Microsoft Threat Protection, February update
Learn about the latest enhancements to Microsoft Threat Protection, the premier solution for securing the modern workplace across identities, endpoints, user data, apps, and infrastructure.
Securing the future of AI and machine learning at Microsoft
The “Securing the Future of Artificial Intelligence and Machine Learning at Microsoft” paper outlines net-new security engineering challenges in the AI and machine learning space.
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.