Qualiteg - LLM Security - Qualiteg Journal (Page 2)

LLM-Audit

LLM-Audit PII Detection Technology, Part 2: Staged PII Masking in LLM Applications

Hello, this is the Qualiteg Product Development team! In our previous technical deep dive, we started from the inherent ambiguity of Japanese—where you cannot tell whether "三沢" (Misawa) is a person's name or a place name—and introduced a five-stage approach to PII detection, from

LLM-Audit

LLM-Audit PII Detection Technology, Part 1: High-Accuracy PII Detection Attuned to the Depth of the Japanese Language

Hello from the Qualiteg Research Team! Today we take a close look at PII (Personally Identifiable Information) detection technology. Global Tools and Japanese-Specialized Tools, Side by Side Protecting personal information is a challenge shared worldwide. With regulations tightening around the globe—GDPR, CCPA, and Japan's amended Act on

LLM-Audit

Defending Corporate Information in the LLM Era: The New Challenge of PII Security

Introduction Why PII Security Matters Now We live in an era in which large language models (LLMs) have permeated every corner of business. Generative AI tools such as ChatGPT, Claude, and Gemini are no longer experimental technology—they have become indispensable infrastructure for daily work. Behind this convenience, however, corporate

LLM Security

LLM-Audit: The Front Lines of LLM Attacks and Defenses

Introduction With the rapid evolution of artificial intelligence, large language models (LLMs) have become indispensable tools for many companies and organizations. Their range of applications—natural language processing, code generation, data analysis, and more—expands daily, driving innovation across a wide range of fields, from streamlining business processes to supporting

LLM Security

[LLM Security] How to Detect Hallucinations

Hello, this is the Qualiteg Research Team. Today, we walk through the following paper on hallucination detection in RAG systems and share our thoughts on LLMs built specifically to detect hallucinations. "Lynx: An Open Source Hallucination Evaluation Model" https://arxiv.org/pdf/2407.08488 Overview The paper describes

LLM Security

[LLM Security] Llama Guard: A First Step Toward AI Safety

Hello, this is the Qualiteg Research Department. Today we will explain Llama Guard, which was announced at the end of last year (December 2023). In recent years, AI technology has advanced remarkably and its range of applications continues to grow. At the same time, however, concerns about the safety of

LLM Security

[LLM Security] Zero-Resource Black-Box Hallucination Detection

Hello from the Qualiteg Research Team. In this article, we walk through the following paper, which proposes a method for detecting hallucinations in a "zero-resource" setting, i.e., without relying on external information such as a database. SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models https: