Signorello

@ulisboa.pt

19

Scopus Publications

477

Scholar Citations

7

Scholar h-index

7

Scholar i10-index

Scopus Publications

  • Editor-in-Chief's Message
    Sam H. Noh, Robbert van Renesse
    ACM Transactions on Computer Systems, 2026
  • Lessons Learned from Five Years of Artifact Evaluations at EuroSys
    Daniele Cono D'Elia, Thaleia Dimitra Doudali, Cristiano Giuffrida, Miguel Matos, Mathias Payer, et al.
    Proceedings of the 3rd ACM Conference on Reproducibility and Replicability ACM Rep 2025, 2025
  • Internet Architecture Evolution: Found in Translation
    Guilherme Ribeiro, Luis Pedrosa, Salvatore Signorello, Fernando M. V. Ramos
    Hotnets 2024 Proceedings of the 2024 3rd ACM Workshop on Hot Topics in Networks, 2024
    The success of the Internet is undeniable, but so are its limitations. Over the past two decades, the research community has responded with clean-slate redesigns, proposing innovative architectures focused on issues like security and information dissemination, among others. Unfortunately, these efforts have had limited impact on the commercial Internet, if any. The reason is that the Internet architecture is deeply entrenched, making a complete replacement elusive. In this paper, we argue that a successful approach to evolving the Internet requires three key ingredients. It should (1) be backwards compatible with the current Internet, (2) evolve from the existing architecture, and (3) allow new architectures to reach their full potential. Recently, the community introduced an overlay-based approach for an Extensible Internet. We believe this is a clear step in the right direction: it is backwards-compatible, does not require replacing the current Internet infrastructure, and is deployable today. However, we contend that this approach is not fully adequate as it lacks the third requirement, which we deem crucial for new architectures to gain a foothold and grow. As an alternative, we advocate for a translation-based approach and present our rationale on how it may enable effective Internet evolution by meeting the three requirements above.
  • P4Chaskey: An Efficient MAC Algorithm for PISA Switches
    Martim Francisco, Bernardo Ferreira, Fernando M. V. Ramos, Eduard Marin, Salvatore Signorello
    Proceedings International Conference on Network Protocols Icnp, 2024
    Cryptographic primitives are of paramount importance to guarantee security properties in communication networks. The associated computational complexity of cryptography standards makes it prohibitive to execute these primitives at line rate in the network core. Existing implementations of cryptographic MAC algorithms in $\\mathbf{P 4}$ for programmable switches impose a severe performance penalty due to packet recirculation, which may not be tolerable at those network speeds. In this paper, we propose the first data plane design in $\\mathbf{P 4}$ of the Chaskey algorithm, a widely used secure and lightweight cryptographic MAC algorithm, tailored for the PISA switch architecture. Our P4Chaskey is the first solution to compute MACs using 128-bit keys without packet recirculation, guaranteeing line rate Terabit speeds. As state-of-the-art solutions require recirculations for the same key size (reducing throughput performance) or offer weaker security (smaller keys), P4CHASKEY is now, to our knowledge, the most efficient MAC design for the target switch architecture.
  • Europ4 2023 chairs welcome message
    Europ4 2023 Proceedings of the 6th International Workshop on P4 in Europe, 2023
  • Poster: In-Network ML Feature Computation for Malicious Traffic Detection
    João Romeiras Amado, Francisco Chamiça Pereira, Salvatore Signorello, Miguel Correia, Fernando Ramos
    SIGCOMM 2023 Proceedings of the ACM SIGCOMM 2023 Conference, 2023
    We present Peregrine, a malicious traffic detector that offloads part of its computation to a programmable switch. The idea is to partition detection, by moving the ML feature computation module from a middlebox server to a switch data plane. The key innovation unlocked---computing the ML input features over all traffic---results in a significant improvement in detection performance: in our evaluation, up to 5.7x over the state of the art.
  • Generic change detection (almost entirely) in the dataplane
    Gonçalo Matos, Salvatore Signorello, Fernando M. V. Ramos
    Ancs 2021 Proceedings of the 2021 Symposium on Architectures for Networking and Communications Systems, 2021
    Identifying traffic changes accurately sits at the core of many network tasks, from congestion analysis to intrusion detection. Modern systems leverage sketch-based structures that achieve favourable memory-accuracy tradeoffs by maintaining compact summaries of traffic data. Mainly used to detect heavy-hitters (usually the major source of network congestion), some can be adapted to detect traffic changes, but they fail on generality. As their core data structures track elephant flows, they miss to identify mice traffic that may be the main cause of change (e.g., microbursts or low-volume attacks). We present k-meleon, an in-network online change detection system that identifies heavy-changes - instead of changes amongst heavy-hitters only, a subtle but crucial difference. Our main contribution is a variant of the k-ary sketch (a well-known heavy-change detector) that runs on the data plane of a switch. The challenge was the batch-based design of the original. To address it, k-meleon features a new stream-based design that matches the pipeline computation model and fits its tough constraints. A preliminary evaluation shows that k-meleon achieves the same level of accuracy for online detection as the offline k-ary, detecting changes for any type of flow: be it an elephant, or a mouse.
  • Towards generic traffic change detection in the data plane
    Gonçalo Matos, Salvatore Signorello, Fernando M. V. Ramos
    Conext Sw 2021 Proceedings of the 2021 Conext Student Workshop 2021 Part of Conext 2021 the 17th International Conference on Emerging Networking Experiments and Technologies, 2021
    Identifying traffic changes accurately sits at the core of many network tasks, from congestion analysis to intrusion detection. Modern telemetry systems perform traffic change detection but restrict their detection to heavy-hitters, failing to identify relevant traffic changes, including microbursts or low-volume attacks. We present k-meleon, an in-switch online change detection system that identifies heavy-changes - instead of changes amongst heavy-hitters only, a subtle but crucial difference. k-meleon is a variant of the k-ary sketch (a well-known heavy-change detector) that leverages programmable switches for detection. To overcome the batch-based design of the original k-ary, k-meleon features a new stream-based design that matches the switch's pipelined computation model and fits its tight constraints. The preliminary evaluation of the current prototype shows the potential of k-meleon in achieving the same level of accuracy for online detection as the offline k-ary.
  • FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications
    Diogo Barradas, Nuno Santos, Luis Rodrigues, Salvatore Signorello, Fernando M. V. Ramos, et al.
    28th Annual Network and Distributed System Security Symposium Ndss 2021, 2021
    However, besides the specific tasks tackled by the previous work, there is currently a lack of support for a new range of security applications that resort to machine learning (ML) to classify flows in real time [92, 27]. This brand of applications has become more relevant as a result of a global trend towards encrypting all Internet traffic [20, 58], which has rendered deep-packet inspection (DPI) increasingly ineffective. As an alternative to DPI, the use of ML-based techniques has proved useful to classify flows with high accuracy for a wide range of scenarios, such as multimedia covert channel detection [7], website fingerprinting [40], botnet traffic identification [53], malware tracking [2], IoT device behavioral analysis [59, 79], or detection of DRM-protected streaming [26, 68, 66].
  • Poster: Speeding up Network Intrusion Detection
    Joao Romeiras Amado, Salvatore Signorello, Miguel Correia, Fernando Ramos
    Proceedings International Conference on Network Protocols Icnp, 2020
    Modern network data planes have enabled new measurement approaches, including efficient sketch-based techniques with provable trade-offs between memory and accuracy, directly in the data plane, at line rate. We thus ask the question: can one leverage this richer measurement plane to improve network intrusion detection? Our answer is SPID, a push-based, feature-rich network monitoring approach to assist learning-based attack detection. SPID switches run a diverse set of measurement primitives and proactively push measurements to the monitoring system when relevant changes occur. Network measurements are then fed as input features to a classifier based on unsupervised learning to detect ongoing attacks, as they occur. In consequence, SPID aims to reduce attack detection time, when comparing to existing solutions present in large scale networks.
  • Random linear network coding on programmable switches
    Diogo Goncalves, Salvatore Signorello, Fernando M.V. Ramos, Muriel Medard
    2019 ACM IEEE Symposium on Architectures for Networking and Communications Systems Ancs 2019, 2019
  • Named Data Networking with Programmable Switches
    Rui Miguel, Salvatore Signorello, Fernando M. V. Ramos
    Proceedings International Conference on Network Protocols Icnp, 2018
  • Advanced interest flooding attacks in named-data networking
    Salvatore Signorello, Samuel Marchal, Jerome Francois, Olivier Festor, Radu State
    2017 IEEE 16th International Symposium on Network Computing and Applications NCA 2017, 2017
  • Understanding the social impact of ICN: between myth and reality
    G. Piro, S. Signorello, M. R. Palattella, L. A. Grieco, G. Boggia, et al.
    AI and Society, 2017
  • NDN.p4: Programming information-centric data-planes
    Salvatore Signorello, Radu State, Jerome Francois, Olivier Festor
    IEEE Netsoft 2016 2016 IEEE Netsoft Conference and Workshops Software Defined Infrastructure for Networks Clouds Iot and Services, 2016
  • Security challenges in future NDN-enabled VANETs
    Salvatore Signorello, Maria Rita Palattella, Luigi Alfredo Grieco
    Proceedings 15th IEEE International Conference on Trust Security and Privacy in Computing and Communications 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications IEEE Trustcom Bigdatase Ispa 2016, 2016
  • Exploring IoT Protocols through the Information-Centric Networking’s Lens
    Salvatore Signorello, Radu State, Olivier Festor
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2015
  • Digital forgetting in information-centric networks-the CONVERGENCE perspective
    Fernando Almeida, Helder Castro, Maria T. Andrade, Giuseppe Tropea, Nicola Blefari Melazzi, et al.
    New Review of Hypermedia and Multimedia, 2014
  • Enabling remote access to a wireless sensor network by exploiting IPv6 capabilities
    A. Leonardi, S. Palazzo, F. Scoto, S. Signorello
    Iwcmc 2011 7th International Wireless Communications and Mobile Computing Conference, 2011

RECENT SCHOLAR PUBLICATIONS

  • Lessons Learned from Five Years of Artifact Evaluations at EuroSys
    DC D'Elia, TD Doudali, C Giuffrida, M Matos, M Payer, S Pirelli, ...
    Proceedings of the 3rd ACM Conference on Reproducibility and Replicability … , 2025
    2025
    Citations: 1
  • Internet architecture evolution: Found in translation
    G Ribeiro, L Pedrosa, S Signorello, FMV Ramos
    Proceedings of the 23rd ACM Workshop on Hot Topics in Networks, 300-307 , 2024
    2024
    Citations: 4
  • P4Chaskey: An Efficient MAC Algorithm for PISA Switches
    M Francisco, B Ferreira, FMV Ramos, E Marin, S Signorello
    EuroP4’24 - Proceedings of the 7th European P4 Workshop (ICNP'24) , 2024
    2024
    Citations: 5
  • Peregrine: Ml-based malicious traffic detection for terabit networks
    JR Amado, F Pereira, D Pissarra, S Signorello, M Correia, F Ramos
    arXiv preprint arXiv:2403.18788 , 2024
    2024
    Citations: 6
  • Poster: In-network ML feature computation for malicious traffic detection
    J Romeiras Amado, FC Pereira, S Signorello, M Correia, F Ramos
    Proceedings of the ACM SIGCOMM 2023 Conference, 1105-1107 , 2023
    2023
    Citations: 3
  • Generic change detection (almost entirely) in the dataplane
    G Matos, S Signorello, FMV Ramos
    Proceedings of the Symposium on Architectures for Networking and … , 2021
    2021
    Citations: 5
  • Towards generic traffic change detection in the data plane
    G Matos, S Signorello, FMV Ramos
    CoNEXT-SW '21: Proceedings of the CoNEXT Student Workshop, 9-10 , 2021
    2021
  • The Nuts and Bolts of Building FlowLens
    D Barradas, N Santos, L Rodrigues, S Signorello, FMV Ramos, A Madeira
    2021
    Citations: 1
  • FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications
    D Barradas, N Santos, L Rodrigues, S Signorello, FMV Ramos, A Madeira
    2021 27th Network and Distributed System Security Symposium (NDSS) , 2021
    2021
    Citations: 246
  • Poster: Speeding Up Network Intrusion Detection
    JR Amado, S Signorello, M Correia, F Ramos
    2020 28th IEEE International Conference on Network Protocols (ICNP) , 2020
    2020
    Citations: 1
  • Random linear network coding on programmable switches
    D Gonçalves, S Signorello, FMV Ramos, M Médard
    2019 ACM/IEEE Symposium on Architectures for Networking and Communications … , 2019
    2019
    Citations: 29
  • Named data networking with programmable switches
    R Miguel, S Signorello, FMV Ramos
    2018 IEEE 26th International Conference on Network Protocols (ICNP), 400-405 , 2018
    2018
    Citations: 40
  • A multifold approach to address the security issues of stateful forwarding mechanisms in Information-Centric Networks
    S Signorello
    Université de Lorraine , 2018
    2018
    Citations: 2
  • Advanced interest flooding attacks in named-data networking
    S Signorello, S Marchal, J François, O Festor, R State
    2017 IEEE 16th International Symposium on Network Computing and Applications … , 2017
    2017
    Citations: 29
  • Understanding the social impact of ICN: between myth and reality
    G Piro, S Signorello, MR Palattella, LA Grieco, G Boggia, T Engel
    AI & SOCIETY 32 (3), 401-419 , 2017
    2017
    Citations: 10
  • Security challenges in future NDN-enabled VANETs
    S Signorello, MR Palattella, LA Grieco
    2016 IEEE Trustcom/BigDataSE/ISPA, 1771-1775 , 2016
    2016
    Citations: 26
  • NDN. p4: Programming Information-Centric Data-Planes
    S Signorello, R State, J Francois, O Festor
    International Workshop on Open-Source Software Networking (OSSN), IEEE … , 2016
    2016
    Citations: 63
  • Exploring IoT Protocols Through the Information-Centric Networking’s Lens
    S Signorello, R State, O Festor
    Intelligent Mechanisms for Network Configuration and Security, 56-60 , 2015
    2015
    Citations: 2
  • Digital forgetting in information-centric networks—the CONVERGENCE perspective
    F Almeida, H Castro, MT Andrade, G Tropea, NB Melazzi, S Signorello, ...
    New review of hypermedia and multimedia 20 (2), 169-187 , 2014
    2014
    Citations: 2
  • Enabling remote access to a wireless sensor network by exploiting IPv6 capabilities
    A Leonardi, S Palazzo, F Scoto, S Signorello
    2011 7th International Wireless Communications and Mobile Computing … , 2011
    2011
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications
    D Barradas, N Santos, L Rodrigues, S Signorello, FMV Ramos, A Madeira
    2021 27th Network and Distributed System Security Symposium (NDSS) , 2021
    2021
    Citations: 246
  • NDN. p4: Programming Information-Centric Data-Planes
    S Signorello, R State, J Francois, O Festor
    International Workshop on Open-Source Software Networking (OSSN), IEEE … , 2016
    2016
    Citations: 63
  • Named data networking with programmable switches
    R Miguel, S Signorello, FMV Ramos
    2018 IEEE 26th International Conference on Network Protocols (ICNP), 400-405 , 2018
    2018
    Citations: 40
  • Random linear network coding on programmable switches
    D Gonçalves, S Signorello, FMV Ramos, M Médard
    2019 ACM/IEEE Symposium on Architectures for Networking and Communications … , 2019
    2019
    Citations: 29
  • Advanced interest flooding attacks in named-data networking
    S Signorello, S Marchal, J François, O Festor, R State
    2017 IEEE 16th International Symposium on Network Computing and Applications … , 2017
    2017
    Citations: 29
  • Security challenges in future NDN-enabled VANETs
    S Signorello, MR Palattella, LA Grieco
    2016 IEEE Trustcom/BigDataSE/ISPA, 1771-1775 , 2016
    2016
    Citations: 26
  • Understanding the social impact of ICN: between myth and reality
    G Piro, S Signorello, MR Palattella, LA Grieco, G Boggia, T Engel
    AI & SOCIETY 32 (3), 401-419 , 2017
    2017
    Citations: 10
  • Peregrine: Ml-based malicious traffic detection for terabit networks
    JR Amado, F Pereira, D Pissarra, S Signorello, M Correia, F Ramos
    arXiv preprint arXiv:2403.18788 , 2024
    2024
    Citations: 6
  • P4Chaskey: An Efficient MAC Algorithm for PISA Switches
    M Francisco, B Ferreira, FMV Ramos, E Marin, S Signorello
    EuroP4’24 - Proceedings of the 7th European P4 Workshop (ICNP'24) , 2024
    2024
    Citations: 5
  • Generic change detection (almost entirely) in the dataplane
    G Matos, S Signorello, FMV Ramos
    Proceedings of the Symposium on Architectures for Networking and … , 2021
    2021
    Citations: 5
  • Internet architecture evolution: Found in translation
    G Ribeiro, L Pedrosa, S Signorello, FMV Ramos
    Proceedings of the 23rd ACM Workshop on Hot Topics in Networks, 300-307 , 2024
    2024
    Citations: 4
  • Poster: In-network ML feature computation for malicious traffic detection
    J Romeiras Amado, FC Pereira, S Signorello, M Correia, F Ramos
    Proceedings of the ACM SIGCOMM 2023 Conference, 1105-1107 , 2023
    2023
    Citations: 3
  • A multifold approach to address the security issues of stateful forwarding mechanisms in Information-Centric Networks
    S Signorello
    Université de Lorraine , 2018
    2018
    Citations: 2
  • Exploring IoT Protocols Through the Information-Centric Networking’s Lens
    S Signorello, R State, O Festor
    Intelligent Mechanisms for Network Configuration and Security, 56-60 , 2015
    2015
    Citations: 2
  • Digital forgetting in information-centric networks—the CONVERGENCE perspective
    F Almeida, H Castro, MT Andrade, G Tropea, NB Melazzi, S Signorello, ...
    New review of hypermedia and multimedia 20 (2), 169-187 , 2014
    2014
    Citations: 2
  • Enabling remote access to a wireless sensor network by exploiting IPv6 capabilities
    A Leonardi, S Palazzo, F Scoto, S Signorello
    2011 7th International Wireless Communications and Mobile Computing … , 2011
    2011
    Citations: 2
  • Lessons Learned from Five Years of Artifact Evaluations at EuroSys
    DC D'Elia, TD Doudali, C Giuffrida, M Matos, M Payer, S Pirelli, ...
    Proceedings of the 3rd ACM Conference on Reproducibility and Replicability … , 2025
    2025
    Citations: 1
  • The Nuts and Bolts of Building FlowLens
    D Barradas, N Santos, L Rodrigues, S Signorello, FMV Ramos, A Madeira
    2021
    Citations: 1
  • Poster: Speeding Up Network Intrusion Detection
    JR Amado, S Signorello, M Correia, F Ramos
    2020 28th IEEE International Conference on Network Protocols (ICNP) , 2020
    2020
    Citations: 1
  • Towards generic traffic change detection in the data plane
    G Matos, S Signorello, FMV Ramos
    CoNEXT-SW '21: Proceedings of the CoNEXT Student Workshop, 9-10 , 2021
    2021