A survey on in-network computing: Programmable data plane and technology specific applications

S Kianpisheh, T Taleb - IEEE Communications Surveys & …, 2022 - ieeexplore.ieee.org
In comparison with cloud computing, edge computing offers processing at locations closer to
end devices and reduces the user experienced latency. The new recent paradigm of in …

Advancing sdn from openflow to p4: A survey

A Liatifis, P Sarigiannidis, V Argyriou… - ACM Computing …, 2023 - dl.acm.org
Software-defined Networking (SDN) marked the beginning of a new era in the field of
networking by decoupling the control and forwarding processes through the OpenFlow …

An exhaustive survey on p4 programmable data plane switches: Taxonomy, applications, challenges, and future trends

EF Kfoury, J Crichigno, E Bou-Harb - IEEE access, 2021 - ieeexplore.ieee.org
Traditionally, the data plane has been designed with fixed functions to forward packets using
a small set of protocols. This closed-design paradigm has limited the capability of the …

Jaqen: A {High-Performance}{Switch-Native} approach for detecting and mitigating volumetric {DDoS} attacks with programmable switches

Z Liu, H Namkung, G Nikolaidis, J Lee, C Kim… - 30th USENIX Security …, 2021 - usenix.org
The emergence of programmable switches offers a new opportunity to revisit ISP-scale
defenses for volumetric DDoS attacks. In theory, these can offer better cost vs. performance …

Realtime robust malicious traffic detection via frequency domain analysis

C Fu, Q Li, M Shen, K Xu - Proceedings of the 2021 ACM SIGSAC …, 2021 - dl.acm.org
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 …

Machine learning approaches for combating distributed denial of service attacks in modern networking environments

A Aljuhani - IEEE Access, 2021 - ieeexplore.ieee.org
A distributed denial of service (DDoS) attack represents a major threat to service providers.
More specifically, a DDoS attack aims to disrupt and deny services to legitimate users by …

[PDF][PDF] FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications.

D Barradas, N Santos, L Rodrigues, S Signorello… - NDSS, 2021 - ndss-symposium.org
An emerging trend in network security consists in the adoption of programmable switches for
performing various security tasks in large-scale, high-speed networks. However, since …

Machine-learning-enabled ddos attacks detection in p4 programmable networks

F Musumeci, AC Fidanci, F Paolucci, F Cugini… - Journal of Network and …, 2022 - Springer
Abstract Distributed Denial of Service (DDoS) attacks represent a major concern in modern
Software Defined Networking (SDN), as SDN controllers are sensitive points of failures in …

An efficient design of intelligent network data plane

G Zhou, Z Liu, C Fu, Q Li, K Xu - 32nd USENIX Security Symposium …, 2023 - usenix.org
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 …

Collaborative prediction and detection of DDoS attacks in edge computing: A deep learning-based approach with distributed SDN

H Zhou, Y Zheng, X Jia, J Shu - Computer Networks, 2023 - Elsevier
Edge computing (EC) has greatly facilitated the deployment of networked services with fast
responses and low bandwidth, by deploying computing and storage at the network edge …