Abstract
Steganography and Cryptography both provide data security, and when used together, it will result to more robust protection. However, one of the studies found that 95% of data breach incidents relate to human error, such as failing to keep information safe and using weak passwords. This data breach is the challenge when using Cryptography as it needs a key for encryption and decryption that must be kept and remembered. This study utilized multilayer protection using Face Authentication (FA) with Advanced Encryption Standard (AES) 128-bit and Least Significant Bit (LSB) to secure a text file that contains confidential information. With this, users do not need to remember and manually keep their passwords because the face authentication would automatically generate a password for them. This includes a face anti-spoofing technique to identify real and fake faces and overcome spoofing attacks. LSB was used to hide the secret text. The FA performance was measured using the False Acceptance Rate (FAR) and False Rejection Rate (FRR) to determine its accuracy. The FRR and FAR results of 0.089% and 0.014% respectively show that the system can successfully detect an image’s authenticity. The AES 128-bit ciphertext takes 12 septillion years to be successfully analyzed using the brute-force attack. Furthermore, the imperceptibility of LSB stego-image obtained 0.48 and 51 dB, respectively, using Mean Square Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). In addition to these, the Message Digest 5 (MD5) was used to convert the generated password into a more complex and stronger cipher key.
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References
Rashmi, N., Jyothi, K.: Steganography combined with cryptography. In: 2018 2nd Conference on Inventive Systems and Control, ICISC 2018, pp. 81–84 (2018)
Sarinas, S.: Facebook-Cambridge analytica scandal: company says 87 million affected (2018). https://www.cnbc.com/2018/04/04/facebook-updates-the-number-of-users-impacted-by-cambridge-analytica-leak-to-87-million-.html. Accessed 19 Nov 2019
UpGuard Team, Block buster: how a private intelligence platform leaked 48 million personal data records (2018). https://www.upguard.com/breaches/s3-localblox. Accessed 19 Nov 2019
Revell, T., Waterfield, P.: Huge new Facebook data leak exposed intimate details of 3m users|New Scientist (2018). https://www.newscientist.com/article/2168713-huge-new-facebook-data-leak-exposed-intimate-details-of-3m-users/. Accessed 19 Nov 2019
Smith, D.: iCloud has deeper problems than the 4Chan nude photos leak - business insider (2014). https://www.businessinsider.com/icloud-has-deeper-problems-than-the-4chan-nude-photos-leak-2014-9. Accessed 19 Nov 2019
Ward, M.: Exposed Amazon cloud storage clients get tip-off alerts - BBC News (2018). https://www.bbc.com/news/technology-42839462. Accessed 19 Nov 2019
Kerner, S.M.: Misconfigured Cloud Storage Instance Exposes Data on 123M Americans (2017). https://www.eweek.com/security/cloud-data-leak-exposes-information-on-123-million-americans. Accessed 19 Nov 2019
Ronda, R.A.: Comelec website hacked|Philstar.com, The Philippine Star (2016). https://www.philstar.com/headlines/2016/03/28/1567196/comelec-website-hacked. Accessed 19 Nov 2019
Joshi, K., Yadav, R.: A new LSB-S image steganography method blend with Cryptography for secret communication. In: Proceedings of 2015 3rd International Conference on Image Information Processing, ICIIP 2015, pp. 86–90 (2016). https://doi.org/10.1109/ICIIP.2015.7414745.
Sharma, V., Madhusudan: Two new approaches for image steganography using cryptography. In: Proceedings of 2015 3rd International Conference on Image Information Processing, ICIIP 2015, pp. 202–207 (2016). https://doi.org/10.1109/ICIIP.2015.7414766
Bukhari, S., Arif, M.S., Anjum, M.R., Dilbar, S.: Enhancing security of images by Steganography and Cryptography techniques. In: 2016 6th International Conference on Innovative Computing Technology, INTECH 2016, pp. 531–534 (2017). https://doi.org/10.1109/INTECH.2016.7845050
Evans, M., He, Y., Maglaras, L., Yevseyeva, I., Janicke, H.: Evaluating information security core human error causes (IS-CHEC) technique in public sector and comparison with the private sector. Int. J. Med. Inform. 127, 109–119 (2019). https://doi.org/10.1016/j.ijmedinf.2019.04.019
Avast: Avast Press|83% of Americans are Using Weak Passwords (2019). https://press.avast.com/83-of-americans-are-using-weak-passwords. Accessed 24 Jan 2020
SC Media: Most users still use weak passwords, NCSC report finds (2019). https://www.scmagazineuk.com/users-use-weak-passwords-ncsc-report-finds/article/1582663. Accessed 24 Jan 2020
Masupha, L., Zuva, T., Ngwira, S., Esan, O.: Face recognition techniques, their advantages, disadvantages and performance evaluation. In: International Conference on Computing, Communication and Security (ICCCS) (2016)
Diana Judith, I., Mary, G.J.J., Susanna, M.M.: Three factor biometric authentication for spiraling of security. In: 1st International Conference on International Conference on Emerging Trends in Engineering, Technology and Science ICETETS 2016, pp. 7–9 (2016). https://doi.org/10.1109/ICETETS.2016.7603017
Zuo, H., Shen, Y., Li, S., Shen, H.: Two-way real-time authentication system based on dynamic password and multi-biometric. In: Proceedings of 2012 International Conference on Computer Science and Service System, CSSS 2012, pp. 1254–1257 (2012). https://doi.org/10.1109/CSSS.2012.318
Costea, N.E., Moisi, E.V.: Fingerprint authentication for budget application. In: 2019 15th International Conference on Engineering of Modern Electric Systems (EMES), pp. 105–108 (2019). https://doi.org/10.1109/EMES.2019.8795100.
Forouzan, B.A.: Introduction to Cryptography and Network Security. Tata McGraw-Hill Publishing Company Limited, New York (2008)
do Prado, K.S.: Face recognition: understanding LBPH algorithm - towards data science (2017). https://towardsdatascience.com/face-recognition-how-lbph-works-90ec258c3d6b. Accessed 5 Mar 2020
Kyrkou, C.: Object detection using local binary patterns (2017). https://medium.com/@ckyrkou/object-detection-using-local-binary-patterns-50b165658368. Accessed 4 May 2020
Chingovska, I., Anjos, A.: The Replay-Attack Database — DDP (2012). https://www.idiap.ch/dataset/replayattack. Accessed 25 Nov 2020
Chingovska, I., Anjos, A., Marcel, S.: On the effectiveness of local binary patterns in face anti-spoofing. In: International Conference of the Biometrics Special Interest Group (BIOSIG), BIOSIG 2012 (2012)
Azad, T.B.: Securing Citrix Presentation Server in the Enterprise (2008). https://doi.org/10.1016/b978-1-59749-281-2.x0001-7
Barragan-Jason, G., Cauchoix, M., Barbeau, E.J.: The neural speed of familiar face recognition. Neuropsychologia 75, 390–401 (2015). https://doi.org/10.1016/j.neuropsychologia.2015.06.017
ScramBox, What do future advances in technology mean for AES-256 security? (2016). https://scrambox.com/article/what-do-future-advances-in-technology-mean-for-aes-256-security/. Accessed 28 Nov 2020
Xie, M.: Council post: Moore’s Law at Warp Speed: The Global Security Risks of a Post-Quantum World (2018). https://www.forbes.com/sites/forbestechcouncil/2018/03/13/moores-law-at-warp-speed-the-global-security-risks-of-a-post-quantum-world/?sh=6f73ebb455a3. Accessed 28 Nov 2020
Odat, A.M., Otair, M.A.: Image steganography using modified least significant bit. Indian J. Sci. Technol. 9(39), 1–5 (2016). https://doi.org/10.17485/ijst/2016/v9i39/86878.
Al-Dmour, H., Al-Ani, A.: A steganography embedding method based on edge identification and XOR coding. Expert Syst. Appl. 46, 293–306 (2016). https://doi.org/10.1016/j.eswa.2015.10.024
Akhtar, N., Johri, P., Khan, S.: Enhancing the security and quality of LSB based image steganography. In: International Conference and Computational Intelligence and Communication Networks, CICN 2013, pp. 385–390. IEEE (2013). https://doi.org/10.1109/CICN.2013.85.
Subhedar, M.S., Mankar, V.H.: Performance evaluation of image steganography based on cover selection and contourlet transform. In: Proceedings of 2013 International Conference on Cloud and Ubiquitous Computing and Emerging Technologies, CUBE 2013, pp. 172–177 (2013). https://doi.org/10.1109/CUBE.2013.39
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Tagoc, J., Sison, A.M., Medina, R.P. (2022). Multilayer Security for Facial Authentication to Secure Text Files. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 296. Springer, Cham. https://doi.org/10.1007/978-3-030-82199-9_51
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