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Cybercriminals targeting the legal sector

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.

Don't Choose Between DSPM and DLP: Here's Why You Need Both

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.

Protect Your Data within your Generative AI workflow with Protegrity on AWS Bedrock

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.

What Is Cloud Encryption? Your Key to Data Security

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.

Riscosity and Microsoft Azure: A Powerful Partnership for Data Security

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 De-identification: Definition, Methods & Why it is Important

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.
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The Key Steps to Ensuring DORA Compliance

As we approach 2025, financial institutions across the EU face the challenge of complying with the Digital Operational Resilience Act (DORA), which is set to take effect on the 17th of January. DORA is focused on strengthening cybersecurity and operational resilience across financial ecosystems, with the consequences for non-compliance ranging from regulatory fines to reputational damage and an increased risk of cyberattacks.

People Problem or Data Problem? Risks and Mitigation of Insider Threats

An insider is any person with authorized access to systems or data that gives them the ability to take potentially harmful actions. Insiders range from business partners or third party contractors to full- and part-time employees–essentially all valid users with access to resources that you'd rather keep out of the wrong hands. People are just people, but when they mishandle data, they fall into the category of being an insider threat–intentional or not.

Challenges with Data Security Posture Management (DSPM)

While Data Security Posture Management (DSPM) is a powerful approach for discovering, monitoring, and managing sensitive data across complex systems, it is not without its challenges. These hurdles often stem from the complexity of modern data environments, evolving threats, and operational constraints. Below are the primary challenges associated with DSPM.