This article explains why passive defenses no longer suffice, defines data security governance as an organizational management discipline, and walks through a four‑step process—asset inventory, classification, control rules, and continuous monitoring—supported by six core security technologies.
The article examines how easily accessible, unfiltered large language models enable even novice attackers to create sophisticated, personalized phishing campaigns and rapid reconnaissance, while defenders scramble to adopt small, locally‑run AI models for detection, UEBA, and reverse‑engineering of AI‑generated malware.
The article explains how situational awareness—covering pre‑attack, during‑attack, and post‑attack stages—leverages big data, AI, threat intelligence, UEBA and visualization to turn security platforms into proactive “security brains,” while also critiquing current product implementations and market practices.
Meituan‑Dianping’s Information Security Center combats data leakage by deploying multi‑layered safeguards—device fingerprinting, CAPTCHAs, behavior‑based crawler detection, robust watermarking, honey‑pot datasets, UEBA analytics, and advanced masking, tokenization, privacy‑preserving techniques, asset mapping, and automated database scanning—to protect both application systems and its massive data‑warehouse environment.
