EDPB guidance on cross-border data transfers post Schrems II ruling highlights a number of things that have changed that organizations will need to keep in mind when thinking about how to comply.
Security incidents happen; that’s just reality. But how a company decides to handle an event says more about their values and priorities than their product. The recent Okta compromise reminds us of the damage inflicted when there is a lack of transparency between a security vendor and its customers.
Fraud detection and cybersecurity have traditionally been separate disciplines. However, increasingly sophisticated attacks, especially those targeting APIs with malicious bots, demand a more integrated defense.
Hackers are reverse engineering mobile apps and embedding malicious code to steal data for downstream attacks or to cause other direct harm to the user.
In today’s corporate environment, everyone has become a privileged user accustomed to quick access and swift responses generated in seconds across platforms, vendors, and many different systems. A rigid and rule-bound access management system is no longer sufficient for companies that want to maintain a competitive edge.
Emerging privacy enhancing technologies (PETs), such as federated learning, are the key building blocks in changing our relationship with data. They can unlock new opportunities while protecting individual privacy, maintaining control of valuable data, and simplifying compliance in an increasingly fragmented regulatory landscape.
Security teams need to be vigilant - both on what SaaS services employees are connecting to, and whether those platforms are safe and remains safe for use in the organization.
Using a people-centric approach to data privacy management can significantly reduce the costs associated with privacy compliance, and help organizations accelerate efficiency and speed to avoid regulatory penalties.
We live in an age that values authenticity: being true to who you are and what you value. It is ironic, then, that one of the more recent innovations of the past few years—Large Language Models, or Generative AI—is in the process of undermining authenticity itself.
For organisations to thrive, they need to prioritise outcomes in their IT investments, leverage trusted industry ecosystems and demonstrate an ability to adapt operating models to customer requirements.
