Healthcare data masking unlocks the incredible potential of healthcare data for analytics and AI applications. The insights from healthcare data can revolutionize the industry from improving patient care to streamlining operations. However, the use of such data is fraught with risk. In the United States, Protected Health Information (PHI) is regulated by the Health Insurance Portability and Accountability Act (HIPAA), which sets stringent requirements to safeguard patient privacy.

If you are a security, compliance, and privacy professional, it’s time to focus on an often-ignored issue—client-side security. While many organizations dedicate significant resources to protecting their servers, there’s a critical question to consider: are you also safeguarding what’s happening on your users’ browsers?

Cybercrime targeting law firms has surged by 77% in the past year, raising significant concerns for the legal sector. The frequency, nature, and motivations of these attacks are evolving, putting law firms in a vulnerable position. Due to the sensitive nature of their data and high stakes, law firms are frequent targets for financially motivated cybercriminals, hacktivists, and even state-sponsored groups.

As security leaders, you’re tasked with protecting the crown jewels of our organizations, your data, while balancing innovation, compliance, and ever-evolving threats. Yet, too often, data security strategies rely on isolated tools and reactive measures, leaving critical gaps.

Cyber insurance underwriters consider a range of variables to assess the risk a company presents and, consequently, determine premiums. These variables can broadly be categorized into organizational factors, security posture, third-party interactions, and incident history.

Collaboratively authored by Anthony Cammarano, Mario Vargas, Muneeb Hasan, Alexandre Charlet, Andre Castro, Vic Levy, Ken Darker and Iwona Rajca Generative AI (GenAI) applications are revolutionizing how businesses interact with data, primarily through Retrieval-Augmented Generation (RAG) pipelines, combining language models with vast enterprise knowledge bases. These pipelines allow organizations to query extensive internal datasets in real time.

Imagine your sensitive business data falling into the wrong hands. A data breach can be devastating, leading to financial losses, legal headaches, and irreparable damage to your reputation. Cloud encryption is your key to protecting your valuable data and ensuring peace of mind in the cloud. In this article, we'll explore cloud encryption and how AlgoSec can help you implement it effectively.

This collaboration is a significant step forward in making robust data security accessible to all organizations. By leveraging the Azure Marketplace, we're empowering Azure customers to easily discover, deploy, and integrate Riscosity into their existing infrastructure. This seamless integration allows for a streamlined experience and faster time to value.

Data is essential. Businesses, researchers, and healthcare providers rely on it. However, this data often contains sensitive personal information, creating privacy risks. Data de-identification helps mitigate these risks by removing or altering identifiers. This makes it harder to link data back to specific individuals. This process is vital for protecting sensitive information and allowing safe data use. Privacy is a growing concern. Regulations like HIPAA set strict rules.