Ikram Ullah | Cryptography | Innovative Research Award

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Innovative Research Award

Ikram Ullah
Government Polytechnic Institute Lakki Marwat, Pakistan

Ikram Ullah
Affiliation Government Polytechnic Institute Lakki Marwat
Country Pakistan
Documents 14
Subject Area Cryptography
Event Technology Scientists Awards
ORCID 0000-0002-4431-3186

Ikram Ullah is a researcher affiliated with Government Polytechnic Institute Lakki Marwat, Pakistan, whose work is situated in cryptography and secure information processing. His recent publications address substitution-box construction, elliptic-curve methods, pseudo-random number generation, and image security, reflecting an applied research focus on developing computational techniques for secure digital data.

Abstract

Ikram Ullah’s research focuses on cryptographic methods for secure digital information, with particular attention to substitution boxes, elliptic curves, pseudo-random number generation, and image encryption. His recent publications examine statistically optimized dynamic S-boxes, Montgomery-curve-based S-box generation, and elliptic-curve methods for secure image data. These studies address cryptographic design through mathematical structures and computational techniques, with emphasis on security properties, efficiency, and practical data protection. Collectively, the publications indicate a research profile connecting theoretical cryptography with application-oriented security problems, particularly where nonlinear components, randomness, and image protection are important. The documented work also illustrates collaboration across mathematical and computing research environments.[1] [2] [3]

Keywords

Cryptography; substitution boxes; S-box generation; elliptic curves; Montgomery curves; pseudo-random number generation; SHA-512; image encryption; nonlinear cryptographic components; information security.

Introduction

Modern digital systems require cryptographic mechanisms that can protect information against unauthorized access and manipulation. Substitution boxes and pseudo-random number generators are important components of many security architectures. Recent studies involving Ikram Ullah examine elliptic-curve structures and dynamic constructions to address security, nonlinearity, randomness, and efficient protection of image data.[1] [2] [3]

Research Profile

Ikram Ullah’s documented research centers on cryptography, particularly the mathematical and computational design of secure primitives. His publications address dynamic substitution boxes, Montgomery elliptic curves, pseudo-random number generation, and image encryption. The work combines algebraic structures with computational evaluation to investigate security characteristics and practical efficiency in cryptographic security applications.[1] [2] [3]

Research Contributions

The reported contributions include construction of statistically optimal dynamic S-boxes, development of a Montgomery-curve-based S-box generator, and an elliptic-curve pseudo-random number generator using SHA-512. These studies explore nonlinear components, dynamic generation, key sensitivity, and secure image-data processing. Together, they demonstrate an application-oriented approach to cryptographic primitive design and evaluation further.[1] [2] [3]

Publications

Ullah has coauthored recent studies covering dynamic S-box construction, Montgomery-curve-based substitution-box generation, and elliptic-curve pseudo-random number generation for image security. The publications appear in Physica Scripta and Security and Privacy, and collectively address mathematical constructions and computational mechanisms intended to strengthen cryptographic processes used for protecting digital information and systems.[1] [2] [3]

Research Impact

The research addresses security challenges in image encryption and cryptographic primitive generation, areas relevant to secure digital communication and data protection. Reported studies evaluate properties such as nonlinearity, randomness, key sensitivity, computational efficiency, and security performance. Their focus provides potential relevance to cryptographic systems requiring adaptable and efficient security components.[1] [2] [3]

Award Suitability

The documented publication record provides evidence of sustained research activity in cryptography and secure information processing. His recent work directly addresses technically relevant problems involving S-boxes, elliptic curves, pseudo-random generation, and image security. These contributions provide a substantive basis for considering the Innovative Research Award within the stated research domain.[1] [2] [3]

Conclusion

Ikram Ullah’s research profile reflects a focused contribution to cryptography through studies of dynamic S-boxes, elliptic-curve constructions, pseudo-random generation, and image security. The documented publications demonstrate engagement with both mathematical foundations and practical security requirements. Continued research in these areas may further develop efficient and adaptable cryptographic mechanisms for applications.[1] [2] [3]

References

  1. Aslam, C. M. A., Ullah, I., & Ishaq, M. (2026). Construction of statistically optimal dynamic S-boxes for secure image encryption. Physica Scripta, 101(35).
    https://doi.org/10.1088/1402-4896/ae9c79
  2. Ullah, I., Arif, S., Abbas, F., & Hayat, U. (2026). Efficient and Secure Montgomery Curve Based Substitution Box Generator With Optimal Nonlinearity. Security and Privacy, 9(1), e70168.
    https://doi.org/10.1002/spy2.70168
  3. Bilal, M., Ullah, I., Zhang, X., & Hayat, U. (2026). Efficient pseudo-random number generator using elliptic curves over small primes for securing image data. Physica Scripta, 101(1), 015005.
    https://doi.org/10.1088/1402-4896/ae3034

Ali Broumandnia | Cybersecurity | Innovative Research Award

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Innovative Research Award

Ali Broumandnia
Islamic Azad University, Iran

Ali Broumandnia
Affiliation Islamic Azad University
Country Iran
Scopus ID 23003455800
Documents 61
Citations 615
h-index 12
Subject Area Cybersecurity
Event Technology Scientists Awards
ORCID 0000-0001-5145-2013

Ali Broumandnia is a researcher affiliated with Islamic Azad University whose scholarly work addresses cybersecurity through digital image encryption, chaotic maps, modular arithmetic, and secure multimedia processing. His publications examine scale-invariant encryption approaches designed to address image-size constraints while strengthening cryptographic properties, providing a focused contribution to contemporary information-security research. [1] [2]

Abstract

Ali Broumandnia’s research is situated within cybersecurity, with particular emphasis on digital image encryption using chaotic and modular mathematical techniques. His scholarly work addresses limitations associated with image-size dependency and conventional cryptographic approaches by investigating scale-invariant encryption frameworks. Research involving three-dimensional modular chaotic maps explores permutation, substitution, diffusion, key-space characteristics, and statistical security measures for digital imagery. Related work extends these concepts to color images and prime-modular constructions, demonstrating a consistent research direction toward adaptable and computationally considered image-security mechanisms. The publication record supplied for this recognition profile indicates sustained engagement with encryption research and its applications to secure digital multimedia communication. [1] [2] [3]

Keywords

  • Cybersecurity
  • Digital Image Encryption
  • Chaotic Maps
  • Modular Arithmetic
  • Scale-Invariant Encryption
  • Cryptography
  • Secure Multimedia

Introduction

Digital images require protection against unauthorized access, manipulation, and disclosure as multimedia communication expands across networked environments. Broumandnia’s research approaches this challenge through cryptographic methods based on chaotic maps and modular operations. His studies investigate scale-invariant image encryption, seeking approaches applicable across differing image dimensions while maintaining measurable security characteristics and computational practicality. [1] [2]

Research Profile

Broumandnia’s documented research profile centers on cybersecurity and image cryptography, particularly the application of three-dimensional modular chaotic maps to digital image protection. His work encompasses grayscale and color-image encryption, scale-invariant processing, permutation and diffusion mechanisms, and prime-modular techniques. These themes demonstrate a coherent specialization connecting mathematical transformations with practical multimedia security requirements. [1] [2] [3]

Research Contributions

The research contributions represented by these publications include development and evaluation of scale-invariant encryption strategies using three-dimensional modular chaotic maps. The studies consider permutation, substitution, diffusion, key-space expansion, statistical properties, and image-size flexibility. Color-image encryption extends the methodology to multidimensional visual data, while prime-modular techniques further explore cryptographic robustness and implementation characteristics. [1] [2] [3]

Publications

Selected publications associated with Broumandnia’s research include studies on scale-invariant digital color image encryption, scale-invariant digital image encryption using three-dimensional modular chaotic maps, and digital image encryption using chaotic maps with prime modular constructions. Collectively, these works reflect a continuing investigation of cryptographic architectures intended to improve flexibility, security parameters, and image-processing performance. [1] [2] [3]

Research Impact

The supplied academic metrics list 61 documents, 615 citations, and an h-index of 12, indicating a documented body of scholarly output and citation activity. Within the cited research, scale-invariant encryption addresses practical image-dimension considerations, while color-image and prime-modular studies broaden the technical scope of secure multimedia processing. [1] [2] [3]

Award Suitability

The documented research aligns with an Innovative Research Award through its sustained focus on image-security methodologies involving chaotic maps, modular arithmetic, scale invariance, and multidimensional processing. The supplied publication evidence demonstrates technically focused work addressing established challenges in digital image encryption, while the reported scholarly metrics provide additional context for evaluating the researcher’s academic profile and research activity. [1] [2] [3]

Conclusion

Ali Broumandnia’s documented scholarship presents a focused research direction in cybersecurity and digital image encryption. His publications investigate three-dimensional chaotic-map architectures, scale-invariant processing, color-image protection, and prime-modular techniques. Together with the supplied publication metrics, these works provide a structured basis for recognizing a research profile centered on cryptographic approaches for secure digital multimedia. [1] [2] [3]

References

  1. Momeni Asl, A., Broumandnia, A., & Mirabedini, S. J. (2021). Scale invariant digital color image encryption using a 3D modular chaotic map. IEEE Access, 9, 102433–102449.
    https://ieeexplore.ieee.org/document/9481114
  2. Broumandnia, A. (2020). Scale invariant digital image encryption using 3D modular chaotic map. Multimedia Tools and Applications, 79, 11327–11355.
    https://link.springer.com/article/10.1007/s11042-019-08337-y
  3. Ghazanfaripour, H., & Broumandnia, A. (2020). Designing a digital image encryption scheme using chaotic maps with prime modular. Optics and Laser Technology, 131, 106339.
    https://www.scopus.com/pages/publications/85086361488

Prof. Dr. Jianquan Ouyang | Cyber Security | Research Excellence Award

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Prof. Dr. Jianquan Ouyang | Cyber Security | Research Excellence Award

Xiangtan University | China

Prof. Dr. Jianquan Ouyang is an emerging researcher in the fields of artificial intelligence, machine learning, and data-driven computational modeling, with a strong emphasis on natural language processing, diffusion models, and federated learning. Affiliated with Xiangtan University, he has authored 66 scholarly publications, receiving 258 citations and achieving an h-index of 8, reflecting consistent research impact. His recent work explores advanced techniques such as nested named entity recognition, transformer-based architectures, and physics-constrained generative models, demonstrating interdisciplinary integration across AI and scientific computing. Dr. Ouyang has collaborated with a broad network of over 90 co-authors, contributing to diverse applications including biomedical imaging, atmospheric simulation, and healthcare monitoring systems. His research advances scalable, fair, and interpretable AI systems, with societal relevance in improving medical diagnostics, environmental modeling, and intelligent data processing frameworks.

Citation Metrics (Scopus)

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258

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Top 5 Featured Publications

Muhammad Nadeem Ali | Intrution Detection | Research Excellence Award

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Mr. Muhammad Nadeem Ali | Intrution Detection | Research Excellence Award

Hongik University | South Korea

Mr. Muhammad Nadeem Ali is an emerging researcher in computer science and information engineering, with a focus on cybersecurity, intrusion detection systems, explainable artificial intelligence (XAI), optimization algorithms, and smart urban mobility solutions. He has authored 26 peer-reviewed publications, receiving 132 citations with an h-index of 6, reflecting steady scholarly impact. His recent work emphasizes interpretable AI models, such as bio-inspired optimization for secure and transparent cyber systems, alongside surveys on sustainable smart transportation. Affiliated with Hongik University, South Korea, he has collaborated with 49 international co-authors, demonstrating strong global research engagement. His research contributes to enhanced digital security, intelligent systems, and socially sustainable urban technologies.

Citation Metrics (Scopus)

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Tapasi Bhattacharjee | Security | Editorial Board Member

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Dr. Tapasi Bhattacharjee | Security | Editorial Board Member

Professor | Techno International New Town | India

Dr. Tapasi Bhattacharjee is a researcher at Techno India Group, Kolkata, with core expertise in sustainable operations management, production–inventory optimization, and circular economy–driven decision models. With 13 publications, h-index of 4 and 63 citations, her work focuses on developing analytical and optimization frameworks that address real-world challenges such as managing perishable goods, emission-sensitive production environments, and resource-efficient inventory systems. Her recent research, including studies on price–time–circularity-responsive systems, demonstrates strong capability in integrating environmental sustainability with advanced quantitative techniques. Collaborating with 18 co-authors across interdisciplinary domains, she contributes to the design of greener and more resilient supply chains, offering insights valuable to industry, policymakers, and academia. Overall, her scholarly contributions support global efforts toward low-carbon manufacturing, sustainable resource use, and data-driven industrial innovation.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Bhattacharjee, T., Maity, S. P., & Islam, S. R. (2017). Hierarchical secret image sharing scheme in compressed sensing. Signal Processing: Image Communication, 61, 21–32.
Cited by: 36

2. Bhattacharjee, T., & Maity, S. P. (2017). An image-in-image communication scheme using secret sharing and M-ary spread spectrum watermarking. Microsystem Technologies, 23(9), 4263–4276.
Cited by: 13

3. Bhattacharjee, T., & Rout, R. K. (2017). Affine Boolean classification in secret image sharing for progressive quality access control. Journal of Information Security and Applications, 33, 16–29.
Cited by: 13

4. Bhattacharjee, T., Singh, J. P., & Nag, A. (2012). A novel (2, n) secret image sharing scheme. Procedia Technology, 4, 619–623.
Cited by: 9

5. Bhattacharjee, T., & Maity, H. K. (2022). On FPGA implementation in medical secret image sharing with data hiding. Multimedia Tools and Applications.
Cited by: 6

Dr. Tapasi Bhattacharjee’s research advances secure image sharing, data protection, and intelligent watermarking techniques that strengthen digital trust in an increasingly visual and interconnected world. Her innovations support safer medical imaging, confidential communication, and resilient information systems for society and industry.