Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …

As a recent innovation, network functions virtualization (NFV)—with its core concept of
replacing hardware middleboxes with software network functions (NFs) implemented in …

Increasingly, smart Network Interface Cards (sNICs) are being used in data centers to
offload networking functions (NFs) from host processors thereby making these processors …

Many efforts have been devoted to the development of efficient Network Intrusion Detection
System (NIDS) using machine learning approaches in Software-defined Network (SDN) …

Restricting data plane processing to packet headers precludes analysis of payloads to
improve routing and security decisions. DeepMatch delivers line-rate regular expression …

Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …

Middlebox services that inspect packet payloads have become commonplace. Today,
anyone can sign up for cloudbased Web application firewall with a single click. These …

Internal users are the main causes of anomalous and suspicious behaviors in a
communication network. Even when traditional security middleboxes are present, internal …

Multi-string pattern matching is a crucial building block for many network security
applications and thus of great importance. Since every byte of a packet has to be inspected …

The increasing amount of network throughput and security threat makes intrusion detection
a major research problem. In the literature, intrusion detection has been approached by …