Security Technology

Digital Assistants (DA) are AI-driven software, sometimes embedded into dedicated hardware and integrated with multiple systems, that understand natural language and use them to perform various tasks

Quantum machine learning (QML) is at the nexus of two very hyped topics: artificial intelligence and quantum computing. Ignoring the AI hype, let's explore how realistic quantum machine learning is.

Our research highlights the problems faced by organizations with regard to API vulnerabilities and offers actionable solutions and practical steps to secure API systems.

In the previous parts of this series, we have learned about cryptography, what makes quantum computers unique, and how quantum computers break this cryptography. In the fourth and final part of our study on post-quantum cryptography, we will look at quantum-resistant algorithms that could replace our existing cryptography.  

This article discusses the importance of properly identifying and protecting AI model files and their associated assets, such as labels, from malicious or even unintended tampering.

Although a legitimate approach, sidecar containers can add even more complexity to Kubernetes (K8s) clusters, not only making it harder to manage but also to detect compromises. This article demonstrates that attackers can leverage the sidecar injection technique after compromising a K8s cluster to remain stealthy and avoid detection, and how to protect K8s clusters from this malicious activity.

In this article, we confront contemporary cryptography with a (so far) hypothetical quantum computer to show how asymmetric algorithms may potentially be broken if quantum computing technology becomes viable. First, we take a step into some basic mathematical objects.

In this entry, the second in our series on post-quantum cryptography, we delve into the history of quantum computing, its foundation in quantum mechanics, and the kind of complex problems quantum computers will be able to solve.

Distributed energy generation (DEG) is a term used to describe the shift from centralized energy generation, such as power companies, to a source — typically a renewable energy source — closer to the user.