DynBlock: dynamic data encryption with Toffoli gate for IoT Article Swipe
Muhammad Aziz Ul Haq
,
Ijaz Ali Shoukat
,
Alamgir Naushad
,
Mohsin Raza Jafri
,
Muhammad Moid Sandhu
,
Abd Ullah Khan
,
Hyundong Shin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-02437-6
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-02437-6
The emergence of 6G networks, coupled with the expansion of smart devices, necessitates robust and efficient cryptography solutions to ensure secure communication. However, the existing resource-constrained cryptography solutions that rely on static permutation, substitution methods, variable key sizes, and fixed block size are vulnerable to quantum computing-based cryptanalysis and side-channel attacks. To address these challenges, this paper proposes a lightweight dynamic block cipher (DynBlock) algorithm. DynBlock is specifically suitable for resource-limited devices, and features a dynamic block size (64-128 bits), which is adaptable to symmetric encryption key sizes. Additionally, DynBlock includes dynamic permutation and substitution layers that enhance confusion and diffusion properties, along with a novel substitution-permutation network (SPN) algorithm that eliminates conventional substitution- and permutation-boxes. DynBlock leverages Tofoli gates and XOR operations to reduce the number of computation operations required to achieve optimal throughput and energy efficiency. Security validation of DynBlock is performed considering various metrics, including an average key avalanche effect of 53.85%, average plain-text avalanche effect of 57.82%, differential cryptanalysis ([Formula: see text]), and cryptanalysis ([Formula: see text]). Performance is compared against various state-of-the-art schemes. We evaluate DynBlock with both 3 and 5 rounds to assess its security and computational efficiency. While the 5-round configuration offers stronger resistance to cryptanalytic attacks, the 3-round setup already delivers robust security, featuring high entropy and a strong avalanche effect, making it well-suited for resource-constrained environments. It is found that DynBlock significantly improves energy efficiency and throughput compared to its predecessors. Additionally, DynBlock demonstrates resistance to quantum computing-based attacks, improved side-channel attack resilience, and enhanced randomness and entropy.
Related Topics
Concepts
Toffoli gate
Computer science
Encryption
Embedded system
Computer security
Quantum gate
Quantum algorithm
Quantum mechanics
Quantum
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41598-025-02437-6
- https://www.nature.com/articles/s41598-025-02437-6.pdf
- OA Status
- gold
- Cited By
- 2
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410613100
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4410613100Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1038/s41598-025-02437-6Digital Object Identifier
- Title
-
DynBlock: dynamic data encryption with Toffoli gate for IoTWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-05-22Full publication date if available
- Authors
-
Muhammad Aziz Ul Haq, Ijaz Ali Shoukat, Alamgir Naushad, Mohsin Raza Jafri, Muhammad Moid Sandhu, Abd Ullah Khan, Hyundong ShinList of authors in order
- Landing page
-
https://doi.org/10.1038/s41598-025-02437-6Publisher landing page
- PDF URL
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https://www.nature.com/articles/s41598-025-02437-6.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.nature.com/articles/s41598-025-02437-6.pdfDirect OA link when available
- Concepts
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Toffoli gate, Computer science, Encryption, Embedded system, Computer security, Quantum gate, Quantum algorithm, Quantum mechanics, Quantum, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
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30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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