The challenge of telling humans and bots apart is almost as old as the web itself. From online ticket vendors to dating apps, to ecommerce and finance — there are many legitimate reasons why you'd want to know if it's a person or a machine knocking on the front door of your website. Unfortunately, the tools for the web have traditionally been clunky and sometimes involved a bad user experience.
Many applications rely on user data to deliver useful features. For instance, browser telemetry can identify network errors or buggy websites by collecting and aggregating data from individuals. However, browsing history can be sensitive, and sharing this information opens the door to privacy risks. Interestingly, these applications are often not interested in individual data points (e.g.
In today’s digital age, cybersecurity is an ever-present concern for businesses and individuals alike. The use of threat intelligence has become a cornerstone in the fight against cyber threats, offering invaluable insights for preventing attacks. However, this comes with its own set of challenges, particularly in terms of maintaining data privacy standards. This guide explores the delicate balance between leveraging threat intelligence for security and upholding user data privacy rights.
Data privacy has emerged as a paramount concern, transcending borders and industries. The introduction of the General Data Protection Regulation (GDPR) by the European Union marked a significant milestone in the global data privacy landscape. However, the conversation around data privacy extends far beyond GDPR, encompassing various regulations worldwide.
More than 130 global jurisdictions have enacted data privacy laws. While each contains rules and requirements distinct to their regions, they share a common priority: identity security. That’s because if an attacker compromises a single identity in an organization where sensitive data is collected, stored and handled, it’s all downhill from there.