When cyber attackers infiltrate your systems, they rely on stealth to remain unnoticed. According to IBM’s Cost of a Data Breach Report 2024, it takes an average of 292 days to identify and contain breaches involving stolen credentials, 261 for phishing attacks, and 257 days for social engineering attacks.
According to Gartner Extended Detection and Response (XDR) is a concept which provides a SaaS-based, vendor-specific security threat detection and incident response system that integrates multiple security products into a cohesive security operations system, providing a more holistic approach to cybersecurity.
At this point it is old news, but this year NIS2 will finally move from being a theory to impacting everyday life of organizations, as Member States must transpose the Directive into applicable, national law by 17 October 2024. The European Directive requires Member States to adopt laws that will improve the cyberresilience of organizations within the EU and impacts organizations that are defined as “operators of essential services”. Under NIS 1, EU member states could still choose what this meant, but to ensure more consistent application, NIS2 has set out its own definition. Rather than making a distinction between operators of essential services and digital service providers, NIS2 defines a new list of the following sectors:
Why is post-quantum cryptography (PQC) important? Well, it's all about safeguarding your sensitive data in the face of future quantum computing advancements. As traditional encryption methods might become vulnerable – and quite frankly redundant -, post-quantum cryptography steps in to make sure your data remains secure.
The era of rapid AI development, also known as the AI Spring, is pressuring companies to shorten their Time-to-Market drastically. In order to stay competitive, they rush to release AI-based products, often sacrificing thorough development and testing. This rush results in underdeveloped AI systems that lack robustness and reliability. New machine learning (ML) algorithms, which are crucial to these developments, may enter production without adequate large-scale review, increasing the risk of ineffective or potentially hazardous implementations. The lack of software development resources increases these risks and challenges even further. Today’s high demand for AI expertise significantly outweighs the supply of skilled professionals and the high costs of computational resources, like GPUs, reduces the general access to AI models. The situation gets even trickier because of data quality, where training data does not meet the expectation and need for high-quality and relevance, resulting in weak AI outputs.
The increasing number of endpoints is becoming more evident within organizations, extending beyond the conventional landscape of end-user computing devices like laptops and workstations. The rise in remote work culture has significantly amplified the demand to safeguard and supervise an array of endpoints, as well as the interactions among them across our broad digital ecosystems. Given that these endpoints persist as prominent gateways for cyberthreats, establishing robust endpoint security strategies has become an indispensable business requirement. However, it prompts an important question: Is Endpoint Detection the sole reliable tool within our cybersecurity tool kit?
