Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Malasi, J. -J. M.; Moudoud, H.; Missaoui, R.
CausalGraph: When Causal Reasoning Meets Large Language Models for Intrusion Detection Systems Proceedings Article
In: Dig Tech Pap IEEE Int Conf Consum Electron, Institute of Electrical and Electronics Engineers Inc., 2026, ISBN: 0747668X (ISSN); 979-833155343-2 (ISBN), (Journal Abbreviation: Dig Tech Pap IEEE Int Conf Consum Electron).
Abstract | Links | BibTeX | Tags: Alarm systems, Budget control, causal reasoning, Chains, Computer crime, Concept Drift, Concept drifts, Conformal Risk Control, Counterfactuals, Generative AI, Human computer interaction, Intrusion Detection, Intrusion Detection Systems, Intrusion-Detection, Knowledge based systems, Language model, LLM, LLMs, Network intrusion, Network security, Risks controls, Sampling
@inproceedings{malasiCausalGraphWhenCausal2026,
title = {CausalGraph: When Causal Reasoning Meets Large Language Models for Intrusion Detection Systems},
author = {J. -J. M. Malasi and H. Moudoud and R. Missaoui},
url = {https://www.scopus.com/pages/publications/105037367854?origin=resultslist},
doi = {10.1109/ICCE67443.2026.11449614},
isbn = {0747668X (ISSN); 979-833155343-2 (ISBN)},
year = {2026},
date = {2026-01-01},
booktitle = {Dig Tech Pap IEEE Int Conf Consum Electron},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Modern intrusion detection systems often achieve impressive benchmark accuracy yet fail in real-world deployment, where network behavior and attacker tactics continuously evolve. Under concept drift, decision boundaries learned offline can diverge from operational reality, triggering false-alarm cascades and creating detection blind spots that erode analyst trust. In this paper, we propose CausalGraph-IDS, a causal and language-model-assisted intrusion detection framework that moves beyond purely correlational scoring by explicitly verifying multi-stage attack chains. Additionally, we propose CHAIN-CRC, a unified algorithm that (i) learns a constrained attack-chain causal graph guided by knowledge-based priors derived from widely used adversary behavior taxonomies, (ii) computes robustness scores by testing whether alarms persist under feasible counterfactual security interventions, and (iii) applies conformal risk control to enforce operator-defined false-positive budgets with finite-sample guarantees.Generative models are integrated in strictly assistive roles through three modules: prior induction to distill causal constraints from unstructured threat reports, counterfactual generation to propose realistic and operationally feasible interventions, and causal logic justification to produce human-readable explanations grounded in the learned attack chain. Experiments on two widely used network intrusion detection benchmarks show that CausalGraph-IDS provides robust, explainable, and risk-governed detection, maintaining strong recall at low false-positive rates while delivering actionable causal insights for mitigation. © 2026 IEEE.},
note = {Journal Abbreviation: Dig Tech Pap IEEE Int Conf Consum Electron},
keywords = {Alarm systems, Budget control, causal reasoning, Chains, Computer crime, Concept Drift, Concept drifts, Conformal Risk Control, Counterfactuals, Generative AI, Human computer interaction, Intrusion Detection, Intrusion Detection Systems, Intrusion-Detection, Knowledge based systems, Language model, LLM, LLMs, Network intrusion, Network security, Risks controls, Sampling},
pubstate = {published},
tppubtype = {inproceedings}
}
Modern intrusion detection systems often achieve impressive benchmark accuracy yet fail in real-world deployment, where network behavior and attacker tactics continuously evolve. Under concept drift, decision boundaries learned offline can diverge from operational reality, triggering false-alarm cascades and creating detection blind spots that erode analyst trust. In this paper, we propose CausalGraph-IDS, a causal and language-model-assisted intrusion detection framework that moves beyond purely correlational scoring by explicitly verifying multi-stage attack chains. Additionally, we propose CHAIN-CRC, a unified algorithm that (i) learns a constrained attack-chain causal graph guided by knowledge-based priors derived from widely used adversary behavior taxonomies, (ii) computes robustness scores by testing whether alarms persist under feasible counterfactual security interventions, and (iii) applies conformal risk control to enforce operator-defined false-positive budgets with finite-sample guarantees.Generative models are integrated in strictly assistive roles through three modules: prior induction to distill causal constraints from unstructured threat reports, counterfactual generation to propose realistic and operationally feasible interventions, and causal logic justification to produce human-readable explanations grounded in the learned attack chain. Experiments on two widely used network intrusion detection benchmarks show that CausalGraph-IDS provides robust, explainable, and risk-governed detection, maintaining strong recall at low false-positive rates while delivering actionable causal insights for mitigation. © 2026 IEEE.
2.
Passerini, K.; Gagnon, S.; Cakici, K.
Opportunities in the digital economy: a new value chain and services for mobile telecom operators Proceedings Article
In: 10th Americas Conference on Information Systems, AMCIS 2004, pp. 2530–2535, Association for Information Systems, 2004.
Abstract | Links | BibTeX | Tags: Business models, Chains, Digital economy, Mobile telecom, Mobile telecommunication operator, Mobile telecommunication systems, Mobile telecommunications, Technological factors, Telecom operators, Telecommunication industry, Telecommunication services, Telecommunications industry, Telecommunications operators, Value chains
@inproceedings{passerini_opportunities_2004,
title = {Opportunities in the digital economy: a new value chain and services for mobile telecom operators},
author = {K. Passerini and S. Gagnon and K. Cakici},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139064053&partnerID=40&md5=d410151fd810adf44b16f35e3a36106c},
year = {2004},
date = {2004-01-01},
booktitle = {10th Americas Conference on Information Systems, AMCIS 2004},
pages = {2530–2535},
publisher = {Association for Information Systems},
abstract = {The advent of the digital economy has brought about radical changes in traditional business channels and operations in several industries. This paper reviews opportunities and challenges that the digital economy has opened in the telecommunication industry in general, and more specifically for mobile telecom operators. It explores the key strategies and technological factors that are guiding the reshaping of the business models for mobile telecom operators, and discusses ongoing changes in the traditional mobile value chain. In addition to presenting a conceptual overview of emerging business models, the paper describes a methodological approach for determining the range of services, customers and product options that will be successful in the new mobile-business environment. The strength of this approach lies in its ability to closely meet the needs of the digital economy’s more sophisticated customers, and therefore increase the potential success of the new business models. © 2004, Association for Information Systems. All rights reserved.},
keywords = {Business models, Chains, Digital economy, Mobile telecom, Mobile telecommunication operator, Mobile telecommunication systems, Mobile telecommunications, Technological factors, Telecom operators, Telecommunication industry, Telecommunication services, Telecommunications industry, Telecommunications operators, Value chains},
pubstate = {published},
tppubtype = {inproceedings}
}
The advent of the digital economy has brought about radical changes in traditional business channels and operations in several industries. This paper reviews opportunities and challenges that the digital economy has opened in the telecommunication industry in general, and more specifically for mobile telecom operators. It explores the key strategies and technological factors that are guiding the reshaping of the business models for mobile telecom operators, and discusses ongoing changes in the traditional mobile value chain. In addition to presenting a conceptual overview of emerging business models, the paper describes a methodological approach for determining the range of services, customers and product options that will be successful in the new mobile-business environment. The strength of this approach lies in its ability to closely meet the needs of the digital economy’s more sophisticated customers, and therefore increase the potential success of the new business models. © 2004, Association for Information Systems. All rights reserved.
3.
Passerini, K.; Gagnon, S.; Cakici, K.
Opportunities in the digital economy: a new value chain and services for mobile telecom operators Proceedings Article
In: 10th Americas Conference on Information Systems, AMCIS 2004, pp. 2530–2535, Association for Information Systems, 2004.
Abstract | Links | BibTeX | Tags: Business models, Chains, Digital economy, Mobile telecom, Mobile telecommunication operator, Mobile telecommunication systems, Mobile telecommunications, Technological factors, Telecom operators, Telecommunication industry, Telecommunication services, Telecommunications industry, Telecommunications operators, Value chains
@inproceedings{passeriniOpportunitiesDigitalEconomy2004,
title = {Opportunities in the digital economy: a new value chain and services for mobile telecom operators},
author = {K. Passerini and S. Gagnon and K. Cakici},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139064053&partnerID=40&md5=d410151fd810adf44b16f35e3a36106c},
year = {2004},
date = {2004-01-01},
booktitle = {10th Americas Conference on Information Systems, AMCIS 2004},
pages = {2530–2535},
publisher = {Association for Information Systems},
abstract = {The advent of the digital economy has brought about radical changes in traditional business channels and operations in several industries. This paper reviews opportunities and challenges that the digital economy has opened in the telecommunication industry in general, and more specifically for mobile telecom operators. It explores the key strategies and technological factors that are guiding the reshaping of the business models for mobile telecom operators, and discusses ongoing changes in the traditional mobile value chain. In addition to presenting a conceptual overview of emerging business models, the paper describes a methodological approach for determining the range of services, customers and product options that will be successful in the new mobile-business environment. The strength of this approach lies in its ability to closely meet the needs of the digital economy’s more sophisticated customers, and therefore increase the potential success of the new business models. © 2004, Association for Information Systems. All rights reserved.},
keywords = {Business models, Chains, Digital economy, Mobile telecom, Mobile telecommunication operator, Mobile telecommunication systems, Mobile telecommunications, Technological factors, Telecom operators, Telecommunication industry, Telecommunication services, Telecommunications industry, Telecommunications operators, Value chains},
pubstate = {published},
tppubtype = {inproceedings}
}
The advent of the digital economy has brought about radical changes in traditional business channels and operations in several industries. This paper reviews opportunities and challenges that the digital economy has opened in the telecommunication industry in general, and more specifically for mobile telecom operators. It explores the key strategies and technological factors that are guiding the reshaping of the business models for mobile telecom operators, and discusses ongoing changes in the traditional mobile value chain. In addition to presenting a conceptual overview of emerging business models, the paper describes a methodological approach for determining the range of services, customers and product options that will be successful in the new mobile-business environment. The strength of this approach lies in its ability to closely meet the needs of the digital economy’s more sophisticated customers, and therefore increase the potential success of the new business models. © 2004, Association for Information Systems. All rights reserved.