machine learning

A new generation of chatbots creates coherent, meaningful texts. This can help out both cybercriminals and cyberdefenders.

We’ve been using machine learning in Kaspersky Internet Security for Android for years now. Here’s why — and what we’ve achieved.

How ontologies can provide the world with greater, faster protection from cyberthreats and more.

Our method for training models to filter out spam lets you maintain privacy without losing efficiency.

With deepfakes becoming more and more common — and more and more convincing — how can you protect your business?

We examine the workings of emotion-recognition technologies, their usefulness, and the privacy concerns they inspire.

This year’s Kaspersky NEXT event centred around AI, gender equality, and social robotics.

Social engineering augmented with machine-learning algorithms can deceive even high-ranking executives.

In this episode of the Kaspersky Lab podcast, Dave and Jeff take a look at the latest Facebook snafu, AI in Dota 2, dumb criminals, and more.

To reduce the attack surface you can block many vulnerable features of software. The question is, how can you do that but not interfere with business-processes?

What surprises do machine learning have in store for us? How difficult is it to trick a machine? And will we end up with Skynet and rise of the machines? Let’s take a look.

Any piece of malware can be captured if you know it for what it is — for example, if you use a trainable behavioral model.

What’s troubling the cybersecurity community most in 2018?

Effective protection of industrial facilities requires permanent monitoring of both information systems and operational processes. We have just the tool.

Google’s new E-Screen Protector prompts users when prying eyes are on their smartphone screen. Is this technology useful?

The essence of the HuMachine concept is a fusion of big data, machine learning, and our analysts’ expertise. But what is behind these words?