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	2.9	7.0	2012	14.8 Days	CHF 2400	Submit
Future Internet futureinternet	4.6	10.0	2009	15 Days	CHF 1800	Submit
Information information	4.3	8.2	2010	18.7 Days	CHF 1800	Submit
Sensors sensors	4.0	9.4	2001	17.8 Days	CHF 2600	Submit

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Published Papers (3 papers)

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All Electronics Future Internet Information Sensors

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42 pages, 544 KB  

Open AccessArticle

AFAPS: An Efficient ECC-Based Authentication Framework for Autonomous Airdrop Parachute Systems

by Burak Civelek and Yasin Genc

Electronics 2026, 15(15), 3273; https://doi.org/10.3390/electronics15153273 - 24 Jul 2026

Viewed by 269

Abstract

Airdrops with autonomous ram-air type parachutes are increasingly important in today’s unconventional warfare conjuncture and humanitarian aid operations. However, there are fundamental issues to be considered by operators or decision makers as to its utilization in the theatre. It is inevitable that new [...] Read more.

Airdrops with autonomous ram-air type parachutes are increasingly important in today’s unconventional warfare conjuncture and humanitarian aid operations. However, there are fundamental issues to be considered by operators or decision makers as to its utilization in the theatre. It is inevitable that new threats will arise with the increase in technology. Therefore, cyber defense elements for air supply should be secured for guided parachute systems that have the ability to glide through long distances. Some of these implied cyber-attacks could target sensitive information (identity, location, etc.) carried by guided parachutes, which are basically unmanned aerial vehicles, and deviate the system by taking over the routing control. The capture of flight information could lead to the disclosure of such covert operations, or at least lead to unexpected complications such as unauthorized airspace violations. Due to various adverse situations that may occur, ensuring the cybersecurity of the parachute payload system both in flight and on the ground has always been an important research topic. In this study, the concept of information replenishment with autonomous parachute systems is introduced to the literature and the cybersecurity of the system is detailed. Specifically, an efficient, lightweight, and pairing-free Elliptic Curve Cryptography (ECC)-based authentication scheme is proposed to secure the system. Considering the resource-constrained nature of autonomous parachute platforms, the proposed scheme is designed to ensure robust security with minimal computational and communication overheads. Furthermore, a security evaluation of the proposed scheme is performed. Although ECC-based authentication protocols have been widely investigated for UAV and IoT systems, this study is, to the best of our knowledge, the first to adapt a lightweight authentication framework to the cybersecurity requirements of autonomous ram-air parachute systems. Full article

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

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46 pages, 9020 KB  

Open AccessArticle

Generative Adversarial Network and Chaotic Map-Based Multi-Layer Medical Image Encryption

by Kaan Doğan Erdoğan and Nurettin Doğan

Sensors 2026, 26(14), 4359; https://doi.org/10.3390/s26144359 - 9 Jul 2026

Viewed by 628

Abstract

One of the major challenges in securing medical image communication systems is the secure and efficient management of cryptographic key material. In this paper, we propose a multi-layer image encryption algorithm that addresses image security while reducing per-image key-storage and transmission overhead under [...] Read more.

One of the major challenges in securing medical image communication systems is the secure and efficient management of cryptographic key material. In this paper, we propose a multi-layer image encryption algorithm that addresses image security while reducing per-image key-storage and transmission overhead under a pre-shared protected-generator model. The proposed algorithm integrates a Generative Adversarial Network, a Piecewise Linear Chaotic Map, DNA complement operations, and bit-level zigzag permutation. A distinguishing feature of the proposed algorithm is that the key image is generated from an image-specific 100-dimensional noise vector, which serves exclusively as the input to the trained generator, while the chaotic parameters and diffusion materials are derived from the generated key image. In this approach, under the assumption of a pre-shared protected generator, transmitting only the image-specific 100-dimensional noise vector that bears no structural relationship to the key image reduces per-image key storage and transmission overhead. Comprehensive numerical evaluations were performed on eleven images, comprising both standard test images and medical images, to assess the security and robustness of the proposed algorithm. The experimental results demonstrate entropy values exceeding 7.996 bits, along with NPCR and UACI values of 99.60% and 33.46%, respectively. Adjacent pixel correlations are reduced to near-zero levels across all tested images. The proposed algorithm exhibits strong robustness against common attacks, including up to 75% cropping and 50% salt-and-pepper noise. The proposed algorithm achieves competitive performance compared with several existing encryption methods. Successful decryption requires the correct image-specific noise vector and the original trained generator. Full article

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

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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 - 15 May 2026

Viewed by 401

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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