Securing digital certificates with perceptual hashing and JSON web tokens
*R. Obulakonda ReddyCorresponding authorrkondareddy@gmail.comDepartment of Computer Science and Engineering (Cyber Security)DundigalInstitute of Aeronautical EngineeringHyderabad, Telangana, 500043, IndiaView full profile → , D. Mahammad Rafimahammadrafi0780@gmail.comDepartment of Computer Science and Engineering (Cyber Security)DundigalInstitute of Aeronautical EngineeringHyderabad, Telangana, 500043, IndiaView full profile → , K. S. R. K. Sarmasarmaksrk@vjit.ac.inDepartment of Computer Science and Engineering (Data Science)Himayat Sagar RdVidya Jyothi Institute of TechnologyHyderabad, Telangana, 500075, IndiaView full profile → , CH. N. Santhosh Kumarsanthosh.ph10@gmail.comDepartment of Computer Science and EngineeringAnanthagiri Suryapet DistrictAnurag Engineering CollegeTelangana, Telangana, 508206, IndiaView full profile → , Muniyandy Elangovanmuniyandy.e@gmail.comAffiliation 1Department of BiosciencesSaveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai, Tamil Nadu, 602105, IndiaAffiliation 2Applied Science Research CenterApplied Science Private UniversityAmman, JordanView full profile → , N. Sreevanivanikondareddy@gmail.comDepartment of Computer Science and Engineering (Cyber Security)DundigalInstitute of Aeronautical EngineeringHyderabad, Telangana, 500043, IndiaView full profile → , Deepak Damarladeepak@deepakd.comDepartment of Computer Science and Engineering (Cyber Security)DundigalInstitute of Aeronautical EngineeringHyderabad, Telangana, 500043, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 13 Nov 2024
- Published Online:
- 17 Mar 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1929
- Pages:
- 485–496
Abstract
Keywords
Subject Classifications
References
[1] W. Sun, J. Zhou, Y. Li, M. Cheung, and J. She, “Robust High-Capacity Watermarking over Online Social Network Shared Images,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 3, pp. 1208–1221, Mar. (2021), doi: 10.1109/TCSVT.2020.2998476.
[2] Z. Zhang and B. B. Gupta, “Social media security and trustworthiness: Overview and new direction,” Future Generation Computer Systems, vol. 86, pp. 914–925, Sep. (2018), doi: 10.1016/j.future.2016.10.007.
[3] T. Hassan, A. Asaad, D. Ali, and S. Jassim, “Artificial Image Tampering Distorts Spatial Distribution of Texture Landmarks and Quality Characteristics,” arXiv preprint arXiv:2208.02710 (2022).
[4] A. Ilavendhan and N. Vignesh, “A Comprehensive Analysis of Anti-Image Manipulation Techniques: Advancements and Challenges,” 2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS). IEEE (2023).
[5] D. K. Mahto and A. K. Singh, “A survey of color image watermarking: State-of-the-art and research directions,” Computers and Electrical Engineering, vol. 93, Jul. (2021), doi: 10.1016/j.compeleceng.2021.107255.
[6] C. Kumar, A. K. Singh, and P. Kumar, “A recent survey on image watermarking techniques and its application in e-governance,” Multimedia Tools and Applications, vol. 77, no. 3, pp. 3597–3622, Feb. (2018), doi: 10.1007/s11042-017-5222-8.
[7] S. Singhania, A. N. Arju, and R. Singh, “Image Tampering Detection Using Convolutional Neural Network,” International Journal of Synthetic Emotions, vol. 10, no. 1, pp. 54–63, Sep. (2019), doi: 10.4018/ijse.2019010103.
[8] O. A. Montesinos López, A. Montesinos López, and J. Crossa, “Convolutional Neural Networks,” in Multivariate Statistical Machine Learning Methods for Genomic Prediction, Cham: Springer International Publishing, pp. 533–577 (2022). doi: 10.1007/978-3-030-89010-0_13.
[9] F. Ghasemi, A. Mehridehnavi, A. Pérez-Garrido, and H. Pérez-Sánchez, “Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks,” Drug Discovery Today, vol. 23, no. 10, Elsevier Ltd, pp. 1784–1790, Oct. 01 (2018). doi: 10.1016/j.drudis.2018.06.016.
[10] H. A. Ahmed and J. W. Jang, “Document certificate authentication system using digitally signed QR code tag,” in ACM International Conference Proceeding Series, Association for Computing Machinery, Jan. (2018). doi: 10.1145/3164541.3164586.
[11] S. Xie, S. Zhong, R. Chen, and H.-Z. Tan, “Two-stage textured-patterns embedded QR codes for printed matter authentication,” Research Square (2021).
[12] “JSON Web Token (JWT) Profile for OAuth 2.0 Client Authentication and Authorization Grants,” Accessed: Aug. 25 (2024). [Online]. Available: https://doi.org/10.17487/RFC7523.
[13] P. Sharma, L. Raja, and S. Panwar, “Technological Use in Predicting Customer Churn for Long Term Sustainability and Viability Using Machine Learning Models,” Multidisciplinary Approaches for Sustainable Development, CRC Press, pp. 224–228 (2024).
[14] H. Farid, “An Overview of Perceptual Hashing,” Journal of Online Trust and Safety, vol. 1, no. 1, Oct. (2021), doi: 10.54501/jots.v1i1.24.
[15] T. Gillespie, “Content moderation, AI, and the question of scale,” Big Data and Society, vol. 7, no. 2, SAGE Publications Ltd, Jul. 01 (2020), doi: 10.1177/2053951720943234.
[16] M. Al-Zubaidie, Z. Zhang, and J. Zhang, “Efficient and secure ECDSA algorithm and its applications: A survey,” arXiv preprint arXiv:1902.10313 (2019).
[17] S. Ali and M. Cenk, “Faster residue multiplication modulo 521-bit mersenne prime and an application to ECC,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 8, pp. 2477–2490, Aug. (2018), doi: 10.1109/TCSI.2018.2791285.
[18] A. Kumar, P. Dadheech, V. Singh, R. C. Poonia, and L. Raja, “An improved quantum key distribution protocol for verification,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 22, no. 4, pp. 491–498 (2019).
[19] M. Hübner, M. Gokhale, and R. Cumplido, “2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig15): Cancun, Mexico, December 8–10, 2014,” IEEE (2015).
[20] H. Cohen, A. Miyaji, and T. Ono, “Efficient elliptic curve exponentiation using mixed coordinates,” Advances in Cryptology—ASIACRYPT’98: International Conference on the Theory and Application of Cryptology and Information Security, Beijing, China, October 18–22, 1998, Springer Berlin Heidelberg (1998).
[21] S. M. N. Khan, J. M. Ghazali, L. Q. Zakaria, S. N. Ahmad, and K. A. Elias, “Various Image Classification Using Certain Exchangeable Image File Format (EXIF) Metadata of Images,” Malaysian Journal of Information and Communication Technology (MyJICT), pp. 1–12 (2018).
[22] B. Toevs, “Processing of metadata on multimedia using exiftool: a programming approach in python,” in Proceedings - 2015 Annual Global Online Conference on Information and Computer Technology, GOCICT 2015, Institute of Electrical and Electronics Engineers Inc., pp. 26–30, Aug. (2016). doi: 10.1109/GOCICT.2015.14.
[23] M. Olvecky and M. Host’ovecky, “Digital image forensics using EXIF data of digital evidence,” ICETA 2021 - 19th IEEE International Conference on Emerging eLearning Technologies and Applications, Proceedings, pp. 282–286 (2021), doi: 10.1109/ICETA54173.2021.9726649.
[24] K. R. Prasad, “Big Data Sentiment Analysis Using Distributed Computing Approach,” in Bapi, R., Rao, K., Prasad, M. (eds), First International Conference on Artificial Intelligence and Cognitive Computing, Advances in Intelligent Systems and Computing, vol 815, Springer, Singapore, pp. 1–8 (2019). https://doi.org/10.1007/978-981-13-1580-0_66.
[25] K. Naveen Kumar, C. Krishna Mohan, and L. Reddy Cenkeramaddi, “The Impact of Adversarial Attacks on Federated Learning: A Survey,” Accepted in IEEE Transactions on Pattern Analysis and Machine Intelligence (2023), DOI: 10.1109/TPAMI.2023.3322785.
[26] C. N. Santhosh Kumar, A. Kiran, V. Kumar, S. Somnath, and S. Suneel, “Social media spammer identification using deep learning,” in MATEC Web of Conferences, vol. 392, p. 01164, EDP Sciences (2024).




