Secure Cyber Physical Systems: Machine Learning and Cryptography

Topic Information

Dear Colleagues,

We invite you to contribute to our Topic on “Secure Cyber Physical Systems: Machine Learning and Cryptography”. This Topic will bring together cutting-edge research and advancements in leveraging cryptographic techniques and machine learning approaches to ensure the security and privacy of cyber–physical systems (CPSs). With CPS playing a vital role in industries such as healthcare, manufacturing, transportation, and energy, addressing their unique security challenges is crucial for safeguarding critical infrastructure and data.

In this Topic, original research articles, reviews, and case studies are welcome. Research areas may include (but are not limited to) the following:

1. Security vulnerabilities and threat modeling in CPS;
2. Applications of cryptographic algorithms for secure CPS communication and data integrity;
3. Machine learning approaches for intrusion and anomaly detection in CPS;
4. Privacy-preserving machine learning techniques for CPS security;
5. Emerging trends in blockchain and distributed ledger technologies for CPS;
6. Advances in post-quantum cryptography for secure CPS;
7. Case studies on machine learning and cryptography applications in CPS sectors (e.g., autonomous vehicles, medical devices, industrial IoT);
8. Artificial general intelligence approaches/reinforcement learning for CPS cybersecurity.

We look forward to receiving your contributions, which will advance the field and create secure, resilient, and intelligent CPS systems.

Dr. Heena Rathore
Dr. Henry Griffith
Dr. Yuchen Jiang
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Electronics electronics	2.6	6.1	2012	16.4 Days	CHF 2400	Submit
Future Internet futureinternet	3.6	8.3	2009	16.1 Days	CHF 1800	Submit
Information information	2.9	6.5	2010	20.9 Days	CHF 1800	Submit
Sensors sensors	3.5	8.2	2001	17.8 Days	CHF 2600	Submit

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Published Papers (1 paper)

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All Electronics Future Internet Information Sensors

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18 pages, 1217 KB  

Open AccessArticle

Antagonistic Differential Game of Critical Infrastructure Migration Management to Post-Quantum Cryptography Under HNDL Conditions

by Feruza Malikova, Valery Lakhno, Zhuldyz Alimseitova, Myroslav Lakhno, Kuljan Togzhanova and Gulzhanat Beketova

Information 2026, 17(5), 485; https://doi.org/10.3390/info17050485 (registering DOI) - 15 May 2026

Abstract

Advances in quantum computing have created a serious threat to modern asymmetric cryptosystems protecting heterogeneous critical information infrastructures (CIIs). During this transition period, the primary threat is the “Harvest Now, Decrypt Later” (HNDL) temporal strategy of attackers, which requires the forced migration of [...] Read more.

Advances in quantum computing have created a serious threat to modern asymmetric cryptosystems protecting heterogeneous critical information infrastructures (CIIs). During this transition period, the primary threat is the “Harvest Now, Decrypt Later” (HNDL) temporal strategy of attackers, which requires the forced migration of CIIs to post-quantum cryptography (PQC) algorithms. However, such migration is associated with nonlinear “technological friction.” This will manifest as a drop in the performance of legacy systems, such as SCADA. In the context of deep cross-industry integration, this can trigger avalanche-like cascading CII failures. This article presents a model of a zero-sum differential game between a CII defender and an attacker (APT group). Using Pontryagin’s maximum principle and the Forward–Backward Sweep Method (FBSM) iterative algorithm, a saddle point was found that determines the equilibrium trajectories of limited resource allocation over a given planning horizon for the CII transition to PQC. The results of the computational experiment demonstrated that isolated sectoral migration is ineffective. It is shown that optimal control requires cross-sector synchronization to prevent cascading degradation of the CII. The proposed mathematical framework provides a practical toolkit for strategic IT budget planning and national security risk management in anticipation of quantum supremacy (Q-Day). Full article

(This article belongs to the Topic Secure Cyber Physical Systems: Machine Learning and Cryptography)

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