Network security is paramount in today's digital landscape, where cyberthreats continue to
evolve and pose significant risks. We propose a DPDK-based scanner based on a study on …

Recent work on in-network machine learning (ML) anticipates offline models to operate well
in modern networking environments. However, upon deployment, these models struggle to …

Network operators require real-time traffic monitoring insights to provide high performance
and security to their customers. It has been shown that artificial intelligence and machine …

In response to concerns about protocol ossification and privacy, post-TCP transport
protocols such as QUIC and Web-RTC include end-to-end encryption and authentication at …

We introduce an approach to designing FPGA-accelerated middleboxes that simplifies
development, debugging, and performance tuning by decoupling the tasks of hardware …

Machine learning techniques are a common solution used to solve a variety of network
management tasks. Often, a network administrator chooses the model to deploy based on …

Machine learning has shown tremendous potential for improving the capabilities of network
traffic analysis applications, often outperforming simpler rule-based heuristics. However, ML …

Apsara vSwitch (AVS) is a per-host deployed forwarding component for instance network
connectivity in the Alibaba Cloud. To meet the growing performance demands, we …

Virtual Private Networks (VPNs) are increasingly being used to protect online users' privacy
and security. However, there is an ongoing arms race between censors that aim to detect …

Cryptojacking is a cybersecurity threat in which cybercriminals use unauthorized computing
resources for cryptocurrency mining. This kind of illegal activity is showing an intensifying …