Anomaly Detection

The proliferation of Internet of Things (IoT) devices has revolutionized connectivity and accessibility, yet this surge also exposes critical vulnerabilities to zero-day attacks that evade traditional security measures. As IoT continues to integrate into everyday life, safeguarding network

The constant evolution of cyber threats requires innovative approaches to safeguard information networks. Intrusion Detection Systems (IDS) play a pivotal role in securing networks by monitoring and analyzing network traffic to identify suspicious activity. With the growing reliance on network

In the complex world of banking, fraud prevention remains an ever-evolving challenge for financial institutions. Traditional fraud detection methods, often relying on static, rule-based systems, struggle to keep pace with increasingly sophisticated fraud tactics. In this landscape, machine learning

In the rapidly evolving landscape of software systems, ensuring that these systems remain reliable and issue-free is paramount. Traditional deep learning methods, although effective in many domains, have encountered significant challenges when interpreting the semantic details embedded within log

Anomaly detection has become a vital tool in modern business, enabling organizations to pinpoint irregularities within vast datasets. This capability is indispensable for various applications, ranging from fraud prevention to operational optimization. The advent of big data and dynamic graph

Phil Venables, the Chief Information Security Officer (CISO) of Google Cloud, is at the forefront of safeguarding AI technologies against emerging threats. Honored on the 2024 Forbes CIO Next list, Venables has emerged as a critical advisor for various companies leveraging Google’s cloud services, e