In-network machine learning using programmable network devices: A survey
Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …
classification and anomaly detection to network configuration. However, machine learning …
Offloading machine learning to programmable data planes: A systematic survey
The demand for machine learning (ML) has increased significantly in recent decades,
enabling several applications, such as speech recognition, computer vision, and …
enabling several applications, such as speech recognition, computer vision, and …
An efficient design of intelligent network data plane
Deploying machine learning models directly on the network data plane enables intelligent
traffic analysis at line-speed using data-driven models rather than predefined protocols …
traffic analysis at line-speed using data-driven models rather than predefined protocols …
{HorusEye}: A Realtime {IoT} Malicious Traffic Detection Framework using Programmable Switches
The ever-growing volume of IoT traffic brings challenges to IoT anomaly detection systems.
Existing anomaly detection systems perform all traffic detection on the control plane, which …
Existing anomaly detection systems perform all traffic detection on the control plane, which …
Flowrest: Practical flow-level inference in programmable switches with random forests
User-plane machine learning facilitates low-latency, high-throughput inference at line rate.
Yet, user planes are highly constrained environments, and restrictions are especially …
Yet, user planes are highly constrained environments, and restrictions are especially …
DDoS family: A novel perspective for massive types of DDoS attacks
Abstract Distributed Denial of Service (DDoS) defense is a profound research problem. In
recent years, adversaries tend to complicate their attack strategies by crafting vast DDoS …
recent years, adversaries tend to complicate their attack strategies by crafting vast DDoS …
Towards continuous threat defense: In-network traffic analysis for IoT gateways
The widespread use of IoT devices has unveiled overlooked security risks. With the advent
of ultrareliable low-latency communications (URLLCs) in 5G, fast threat defense is critical to …
of ultrareliable low-latency communications (URLLCs) in 5G, fast threat defense is critical to …
pforest: In-network inference with random forests
C Busse-Grawitz, R Meier, A Dietmüller… - arxiv preprint arxiv …, 2019 - arxiv.org
When classifying network traffic, a key challenge is deciding when to perform the
classification, ie, after how many packets. Too early, and the decision basis is too thin to …
classification, ie, after how many packets. Too early, and the decision basis is too thin to …
RIDS: Towards advanced ids via rnn model and programmable switches co-designed approaches
Existing Deep Learning (DL)-based network Intrusion Detection System (IDS) is able to
characterize sequence semantics of traffic and discover malicious behaviors. Yet DL models …
characterize sequence semantics of traffic and discover malicious behaviors. Yet DL models …
Leveraging prefix structure to detect volumetric ddos attack signatures with programmable switches
C Misa, R Durairajan, A Gupta… - … IEEE Symposium on …, 2024 - ieeexplore.ieee.org
As increasingly complex and dynamic volumetric DDoS attacks continue to wreak havoc on
edge networks, two recent developments promise to bolster DDoS defense at the edge …
edge networks, two recent developments promise to bolster DDoS defense at the edge …