Enhancing Anomaly-Based Intrusion Detection Systems with Process Mining

Anomaly-based Intrusion Detection Systems IDSs ensure protection against malicious attacks on networked systems. While deep learning-based IDSs achieve effective performance, their limited trustworthiness due to black-box architectures remains a critical constraint. Despite existing explainable...

Hybrid IDS Using Signature-Based and Anomaly-Based Detection

Intrusion detection systems IDS are essential for protecting computer systems and networks against a wide range of cyber threats that continue to evolve over time. IDS are commonly categorized into two main types, each with its own strengths and limitations, such as difficulty in detecting...

The Myths of Ransomware Attacks and How To Mitigate Risk

Today's modern companies are built on data, which now resides across countless cloud apps. Therefore preventing data loss is essential to your success. This is especially critical for mitigating against rising ransomware attacks — a threat that 57% of security leaders expect to be compromised by...

How Imperva Data Security Fabric Reduces Splunk Ingestion Costs and Accelerates Incident Management

They say the devil is in the details. This is especially true for security professionals that use Splunk as their organization’s primary security analytics engine. Splunk analytics gives security teams a real-time view of machine data from networks, data centers, or IT environments. Organizations...

A Framework for Secure and Scalable Network Traffic Analysis: Netcap

The Netcap NETwork CAPture framework efficiently converts a stream of network packets into highly accessible type-safe structured data that represent specific protocols or custom abstractions. These audit records can be stored on disk or exchanged over the network, and are well suited as a data...