Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs

Jan Antic; Joao Pita Costa; Ales Cernivec; Matija Cankar; Tomaz Martincic; Aljaz Potocnik; Hrvoje Ratkajec; Gorka Benguria Elguezabal; Nelly Leligou; Alexandra Lakka; Ismael Torres Boigues; Eliseo Villanueva Morte

doi:10.1109/DRCN57075.2023.10108105

Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs

Jan Antic, Joao Pita Costa, Ales Cernivec, Matija Cankar, Tomaz Martincic, Aljaz Potocnik, Hrvoje Ratkajec, Gorka Benguria Elguezabal, Nelly Leligou, Alexandra Lakka, Ismael Torres Boigues, Eliseo Villanueva Morte

High Performance Analytics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

In the era of digital transformation the increasing vulnerability of infrastructure and applications is often tied to the lack of technical capability and the improved intelligence of the attackers. In this paper, we discuss the complementarity between static security monitoring of rule matching and an application of self-supervised machine-learning to cybersecurity. Moreover, we analyse the context and challenges of supply chain resilience and smart logistics. Furthermore, we put this interplay between the two complementary methods in the context of a self-learning and self-healing approach.

Original language	English
Title of host publication	2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665475983
DOIs	https://doi.org/10.1109/DRCN57075.2023.10108105
Publication status	Published - 2023
Event	19th International Conference on the Design of Reliable Communication Networks, DRCN 2023 - Vilanova i la Geltru, Spain Duration: 17 Apr 2023 → 20 Apr 2023

Publication series

Name	2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023

Conference

Conference	19th International Conference on the Design of Reliable Communication Networks, DRCN 2023
Country/Territory	Spain
City	Vilanova i la Geltru
Period	17/04/23 → 20/04/23

Keywords

anomaly detection
deep learning
masked language modelling
natural language processing
runtime
security monitoring
self healing
self learning
smart logistics
supply chain resilience

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/DRCN57075.2023.10108105

Cite this

Antic, J., Costa, J. P., Cernivec, A., Cankar, M., Martincic, T., Potocnik, A., Ratkajec, H., Elguezabal, G. B., Leligou, N., Lakka, A., Boigues, I. T., & Morte, E. V. (2023). Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs. In 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023 (2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DRCN57075.2023.10108105

Antic, Jan ; Costa, Joao Pita ; Cernivec, Ales et al. / Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs. 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023).

@inproceedings{8c97d7a265f1430c8930da2286ea76b9,

title = "Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs",

abstract = "In the era of digital transformation the increasing vulnerability of infrastructure and applications is often tied to the lack of technical capability and the improved intelligence of the attackers. In this paper, we discuss the complementarity between static security monitoring of rule matching and an application of self-supervised machine-learning to cybersecurity. Moreover, we analyse the context and challenges of supply chain resilience and smart logistics. Furthermore, we put this interplay between the two complementary methods in the context of a self-learning and self-healing approach.",

keywords = "anomaly detection, deep learning, masked language modelling, natural language processing, runtime, security monitoring, self healing, self learning, smart logistics, supply chain resilience",

author = "Jan Antic and Costa, {Joao Pita} and Ales Cernivec and Matija Cankar and Tomaz Martincic and Aljaz Potocnik and Hrvoje Ratkajec and Elguezabal, {Gorka Benguria} and Nelly Leligou and Alexandra Lakka and Boigues, {Ismael Torres} and Morte, {Eliseo Villanueva}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023 ; Conference date: 17-04-2023 Through 20-04-2023",

year = "2023",

doi = "10.1109/DRCN57075.2023.10108105",

language = "English",

series = "2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023",

address = "United States",

}

Antic, J, Costa, JP, Cernivec, A, Cankar, M, Martincic, T, Potocnik, A, Ratkajec, H, Elguezabal, GB, Leligou, N, Lakka, A, Boigues, IT & Morte, EV 2023, Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs. in 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023. 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023, Institute of Electrical and Electronics Engineers Inc., 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023, Vilanova i la Geltru, Spain, 17/04/23. https://doi.org/10.1109/DRCN57075.2023.10108105

Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs. / Antic, Jan; Costa, Joao Pita; Cernivec, Ales et al.
2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs

AU - Antic, Jan

AU - Costa, Joao Pita

AU - Cernivec, Ales

AU - Cankar, Matija

AU - Martincic, Tomaz

AU - Potocnik, Aljaz

AU - Ratkajec, Hrvoje

AU - Elguezabal, Gorka Benguria

AU - Leligou, Nelly

AU - Lakka, Alexandra

AU - Boigues, Ismael Torres

AU - Morte, Eliseo Villanueva

PY - 2023

Y1 - 2023

N2 - In the era of digital transformation the increasing vulnerability of infrastructure and applications is often tied to the lack of technical capability and the improved intelligence of the attackers. In this paper, we discuss the complementarity between static security monitoring of rule matching and an application of self-supervised machine-learning to cybersecurity. Moreover, we analyse the context and challenges of supply chain resilience and smart logistics. Furthermore, we put this interplay between the two complementary methods in the context of a self-learning and self-healing approach.

AB - In the era of digital transformation the increasing vulnerability of infrastructure and applications is often tied to the lack of technical capability and the improved intelligence of the attackers. In this paper, we discuss the complementarity between static security monitoring of rule matching and an application of self-supervised machine-learning to cybersecurity. Moreover, we analyse the context and challenges of supply chain resilience and smart logistics. Furthermore, we put this interplay between the two complementary methods in the context of a self-learning and self-healing approach.

KW - anomaly detection

KW - deep learning

KW - masked language modelling

KW - natural language processing

KW - runtime

KW - security monitoring

KW - self healing

KW - self learning

KW - smart logistics

KW - supply chain resilience

UR - http://www.scopus.com/inward/record.url?scp=85159134927&partnerID=8YFLogxK

U2 - 10.1109/DRCN57075.2023.10108105

DO - 10.1109/DRCN57075.2023.10108105

M3 - Conference contribution

AN - SCOPUS:85159134927

T3 - 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023

BT - 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023

Y2 - 17 April 2023 through 20 April 2023

ER -

Antic J, Costa JP, Cernivec A, Cankar M, Martincic T, Potocnik A et al. Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs. In 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023). doi: 10.1109/DRCN57075.2023.10108105

Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this