Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

This week, during LandForces 2024 archTIS announced the launch of archTIS Trusted Data Integration, a new lightweight, fast, and agile solution for integrating, securing, and governing sensitive and classified structured data from multiple sources at scale and speed.

These days, we use Gmail for everything from customer service to telehealth. Over time, your Gmail account might become a treasure trove of sensitive PII, PCI, PHI, and passwords that hackers can leverage. In fact, as of this year, just under half of all data breaches involve email. So, what can you do to protect your inbox? Enter: email encryption.

Prioritizing cloud security looks different for every business. However, many businesses migrating to the cloud rely on conventional data security methods, including built-in tools from cloud providers and ad hoc measures. Unfortunately, these traditional approaches often fall short, leaving critical gaps in protection and hindering true cloud-powered innovation. Ensuring secure cloud services are multifaceted, let’s dive deeper into the impacts, strategies, and solutions.

Businesses migrating to the cloud face a complex landscape requiring advanced cloud data protection measures. Conventional security approaches often fail to provide the needed flexibility and comprehensiveness for modern cloud environments. To truly harness the cloud’s power, businesses need three essential capabilities: unified control, federated protection, and comprehensive data protection mechanisms.

In today's rapidly evolving digital landscape, software supply chain security has emerged as a critical concern for organizations worldwide. Among the countless security threats, ‘secret leaks’ stand out as a predominant issue, posing significant risks to the integrity and confidentiality of software systems. This blog post delves into the intricacies of secret leaks, exploring why they are a pervasive problem and what steps can be taken to mitigate this threat.

Data is the backbone of all businesses as everything moves online. Effective data analysis helps businesses to predict future trends, identify any gaps, and understand customer behavior, bringing them ahead of their competitors. Other than being indispensable, data is also a sensitive asset because if found in the wrong hands, it can bring disastrous consequences for any organization.

Personally Identifiable Information (PII) refers to any data that can identify an individual. In today’s digital world, protecting PII is crucial. As data breaches become more common, businesses must protect their sensitive information. PII masking plays a vital role in data security. It involves altering or hiding specific data elements to prevent unauthorized access. This practice is essential for companies that handle large volumes of customer data.

As Generative AI (GenAI) and Large Language Models (LLMs) become integral to modern apps, we face a critical challenge of protecting sensitive user data from inadvertent exposure. In this article, we’ll explore the importance of content filtering in LLM-powered apps, and provide strategies for its implementation. Looking for step-by-step tutorials on prompt sanitization for OpenAI, Langchain, Anthropic, and more? Skip down to the “Tutorials & further learning” section below.

The way we store data has undergone a dramatic shift. From good ol’ floppy disks to today’s cloud storage solutions, advancements in storage have slashed costs and allowed organizations to hold exponentially more data. And we are all taking advantage of this. In fact, data is proliferating at a staggering 25% annually. This presents a double-edged sword. On the one hand, this vast data lake holds immense potential for valuable insights.