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Privacy concerns how laws and norms govern personal data, shaping cybersecurity duties for collection, storage, access, and disclosure.

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Privacy is the ability of people to control how information about them is collected, used, retained, and disclosed. In technical and legal contexts, it covers identifiable data and data that can support inferences about a person, not only information made public. Privacy rules and organizational policies commonly address purpose, transparency, access, correction, retention, and sharing.

For security practitioners, privacy depends on reducing unnecessary data and restricting legitimate access: data minimization, encryption, least-privilege controls, segregation of identifiers, retention limits, and audit logs all reduce exposure. Compromised credentials, misconfigured storage, excessive telemetry, or third-party access can reveal sensitive information; pseudonymized datasets may also be re-identified when combined with other data. During an incident, teams must establish what personal data was accessed or disclosed, contain further exposure, preserve evidence, and meet applicable notification and handling requirements.

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AI-assisted coding and AI app generation platforms have created an unprecedented surge in software development. Companies are now facing rapid growth in both the number of applications and the pace of change within those applications. Security and privacy teams are under significant pressure as the surface area they must cover is expanding quickly while their staffing levels remain largely

This week’s cyber stories show how fast the online world can turn risky. Hackers are sneaking malware into movie downloads, browser add-ons, and even software updates people trust. Tech giants and governments are racing to plug new holes while arguing over privacy and control. And researchers keep uncovering just how much of our digital life is still wide open

Cybersecurity researchers have disclosed three now-patched security vulnerabilities impacting Google's Gemini artificial intelligence (AI) assistant that, if successfully exploited, could have exposed users to major privacy risks and data theft

We used to think of privacy as a perimeter problem: about walls and locks, permissions, and policies. But in a world where artificial agents are becoming autonomous actors — interacting with data, systems, and humans without constant oversight — privacy is no longer about control. It’s about trust. And trust, by definition, is about what happens when you’re not looking

Meta Platforms on Monday announced that it's bringing advertising to WhatsApp, but emphasized that the ads are "built with privacy in mind." The ads are expected to be displayed on the Updates tab through its Stories-like Status feature, which allows ephemeral sharing of photos, videos, voice notes, and text for 24 hours. These efforts are "rolling out gradually," per the company

The Hacker News 1 year, 2 months ago

Top 10 Best Practices for Effective Data Protection

Data is the lifeblood of productivity, and protecting sensitive data is more critical than ever. With cyber threats evolving rapidly and data privacy regulations tightening, organizations must stay vigilant and proactive to safeguard their most valuable assets. But how do you build an effective data protection framework? In this article, we'll explore data protection best practices from meeting

Austrian privacy non-profit noyb (none of your business) has sent Meta's Irish headquarters a cease-and-desist letter, threatening the company with a class action lawsuit if it proceeds with its plans to train users' data for training its artificial intelligence (AI) models without an explicit opt-in

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