Demo Data from EDBT 2026 / reviewers in the wild / expert
Shaoyu Tu
dblp:390/6601
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
1 paper |
Software-defined and programmable networks · 100% | |
| Network and information security
1 paper |
Network security · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software-defined and programmable networks
programmable data plane |
0.8 | 1 | 2024 | Envisioning a Unified Programmable Dataplane to Monitor Slow Attacks · ICNP 2024 |
Network security › intrusion detection and prevention
intrusion detection |
0.8 | 1 | 2024 | Envisioning a Unified Programmable Dataplane to Monitor Slow Attacks · ICNP 2024 |
Software-defined and programmable networks › programmable data plane
programmable switch |
0.2 | 1 | 2024 | Envisioning a Unified Programmable Dataplane to Monitor Slow Attacks · ICNP 2024 |
Software-defined and programmable networks › programmable data plane
SmartNIC offload |
0.2 | 1 | 2024 | Envisioning a Unified Programmable Dataplane to Monitor Slow Attacks · ICNP 2024 |
Methods — techniques the papers use, named apart from their topics
sketch-based data structures · 1.5flow filtering · 1.5caching · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Envisioning a Unified Programmable Dataplane to Monitor Slow AttacksabstractRecent work shows that programmable switches can effectively detect attack traffic, such as denial-of-service attacks in the midst of high-volume network traffic. However, these techniques primarily rely on sampling or sketch-based data structures, which can only be used to approximate the characteristics of dominant flows in the network. As a result, such techniques are unable to effectively detect low-volume attacks that stealthily add only a few packets to the network. Our work explores how the combination of programmable switches, Smart network interface cards, and hosts can enable fine-grained analysis of every flow in a network, even those with only a small number of packets. We focus on analyzing packets at the start of each flow, as those packets often can help indicate whether a flow is benign or suspicious. We propose a unified architecture that spans the full programmable dataplane to take advantage of the strengths of each type of device. We are developing new filter data structures to efficiently track flows on the switch, dataplane-based communication protocols to quickly coordinate between devices, and caching approaches on the SmartNIC that help minimize the traffic load reaching the host. Our preliminary prototype can handle the full pipe bandwidth of 1.4 Tbps of traffic entering the Tofino switch, forward only 20 Gbps to the SmartNIC, and minimize the traffic load to 5 Gbps reaching the host due to our efficient flow filter, packet batching, and SmartNIC-based cache. Cuidi Wei, Shaoyu Tu, Toru Hasegawa, Yuki Koizumi, K. K. Ramakrishnan, Junji Takemasa, Timothy Wood 0001 |
ICNP | 2 |