Digital Signs Security System using AES-Blowfish-RSA Hybrid Cryptography Approach


  • Christnatalis HS Universitas Prima Indonesia
  • Amir Mahmud Husein Universitas Prima Indonesia




Hybrid Cryptography; RSA-AES-Blowfish; Digital Signatures; Data Security; Kohonen SOM


Increasing application of digital signatures in legitimate authentication of administrative documents in both public and private environments is one of the points of concern, especially the issue of security and integrity of ownership of signatures. Digital signature is a mathematical scheme, which a unit to identify and prove the authenticity of the owner of the message or document. The study aims to analyze security patterns and identification of digital signatures on documents using the RSA-AES-Blowfish hybrid cryptographic method approach for securing digital signatures, while the Kohonen SOM method is applied to identify ownership recognition of signature images. The analysis framework used in this study is each signature will be stored in the form of a digital image file that has been encrypted using hybrid method of AES-Blowfish with the SHA 256 hash function. Process of forming private keys and public keys in the signature image using the RSA algorithm. Authentic verification of the use of digital signatures on the document has 2 (two) stages, the first stage is signature will be valid used on the document if the result of hashing the selected signature image is the same based on the private key and public key entered by the user, while the second stage identification is done using the Kohonen SOM method to validate the similarity of the chosen signature with the ownership of the signature.

GS Cited Analysis


Download data is not yet available.


Husein, A M., Bayu, A W, Tommy, Andi, M E, and Siregar, R., 2018, Performance analysis of AES-Blowfish hybrid algorithm forsecurity of patient medical record data, IOP Conf. Series: Journal of Physics: Conf. Series 1007 (2018) 012018, doi:10.1088/1742-6596/1007/1/012018.

Husein, A M, Harahap, M., 2017, Pengenalan Multi Wajah Berdasarkan Klasifikasi Kohonen SOM Dioptimalkan dengan Algoritma Discriminant Analysis PCA, QUERY: Jurnal Sistem Informasi, Volume: 01, Number: 02, pp 33-39, ISSN 2579-5341.

Husein, A M., Harahap, M., 2017, Penerapan Metode Distance Transform Pada Kernel Discriminant Analysis Untuk Pengenalan Pola Tulisan Tangan Angka Berbasis Principal Component Analysis. Sinkron, Vol 2, No 2, pp 31-36, e-ISSN:2541-2019, p-ISSN:2541- 044X.

Randika, K S., 2014, Online and Offline Signature Verification: A Combined Approach, International Conference on Information and Communication Technologies, doi: 10.1016/j.procs.2015.02.089.

Mukherjee, A., Priya, K., Pandit, M., & Bhattacharya, D., 2017, Use of Auto Associative Network for signature recognition, International Journal of Current Engineering and Technology, E-ISSN:2277–4106.

Harahap, M., Husein, A M., Darma, A., 2017, Identifikasi Tanda Tangan Dengan Kohonen SOM berbasis Principal Component Analysis. Seminar Nasional APTIKOM (SEMNASTIKOM), pp 333-337.

Kedia, S., Monga, Er., G, 2017, Static Signature Matching Using LDA and Artificial Neural Networks, International Journal of Advance Research, Ideas and Innovation in Technology, 245-248, Volume3, Issue3, ISSN: 2454-132X.

Ghosh, S N et al., 2015, Performance Analysis of AES, DES, RSA And AES-DES-RSA Hybrid Algorithm for Data Security, International Journal of Innovative and Emerging Research in Engineering Volume 2, Issue 5, 83-88.
Bhuvaneshwari M, Tenmozhi S. 2016, A VLSI architecture for security based stenographic processor with AES algorithm. International Journal of Electrical and Computer Engineering; pp 1–6.

Suratma, P G., Azis, A., 2017. Tanda Tangan Digital Menggunakan QR Code Dengan Metode Advanced Encryption Standard. Techno, Volume 18 No. 1, pp 059-068, ISSN 1410 – 8607.

Fauzan, A M., Paulus, E., 2018, A Framework to Ensure Data Integrity and Safety, Journal of Computing and Applied Informatics (JoCAI) Vol. 02, No. 1, pp 1-11, ISSN: 2580-6769.

Shaikh, A. P., Kaul, V., 2014, Enhanced Security Algorithm using Hybrid Encryption and ECC, IOSR Journal of Computer Engineering (IOSR-JCE), Volume 16, Issue 3; PP 80-85.

Kadam, K G., Khairnar, V., 2015, Hybrid RSA-AES Encryption for Web Services, International Journal of Technical Research and Applications”, Special Issue 31(September, 2015), PP. 51-56.

Behl, R., Sehgal, G., Kumar, M., Gupta, P., Garg, S., 2015, Experimental comparison between Hybrid RSA-AES and RSA algorithms in IP security, IJMTER, 588-594.

Kumar B., Boaddh., and Mahawar, L., 2016, A hybrid security approach based on AES and RSA for cloud data, International Journal of Advanced Technology and Engineering Exploration”, Vol 3(17), 43-49.

Mohammed, H. R., Al-Taee, E. J. A. R., 2015, Signature Identification and Recognition using Elman Neural Network, European Journal of Scientific Research, ISSN 1450-216X/1450-202X Vol. 131 No 2.

Daqrouq, K., Sweidan, H., Balamesh, A. & Ajour, M. N., 2017, Off-Line Handwritten Signature Recognition by Wavelet Entropy and Neural Network, Entropy 2017, 19, 252; doi:10.3390/e19060252.

Por, L. Y., Beh, D., Ang, T. F., Ong, S. Y., 2013, “An Enhanced Mechanism for Image Steganography Using Sequential Colour Cycle Algorithm”, The International Arab Journal of Information Technology, Vol. 10, 51-60


Crossmark Updates

How to Cite

HS, C., & Husein, A. M. (2019). Digital Signs Security System using AES-Blowfish-RSA Hybrid Cryptography Approach. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 4(1), 185-190.

Most read articles by the same author(s)

1 2 > >>