1. DATA HIDING IN IMAGE-BASED AUTHENTICATION USING
COMBINATION OF
ZERO-KNOWLEDGE PROTOCOL AND STEGANOGRAPHY
NAME: NURUL NADZIRAH BT ADNAN
MATRIC NUMBER: BTBL 17047005
SUPERVISOR NAME: PROF. MADYA DR.ZARINA BT
MOHAMAD
PROGRAM: BACHELOR OF COMPUTER SCIENCE (NETWORK
SECURITY) WITH HONOUR
ABSTRACT / RESEARCH BACKGROUND
One other most important aspects in information security nowadays is to understand when creating or improving the website’s login procedure or
known as user authentication. Users are usually identified with a user ID, and authentication is accomplished when the user provides a credential, for
example a password, that matches with that user ID. The concept that is normally use to secure or authenticate the system is the simple text-based
passwords. But, it is not secure enough and a burden on the user to remember. There is an alternative solution to these which is Graphical User
Authentication (GUA) or imaged-based authentication. This is because humans are good at recognizing images rather than remembering password.
This type of approach help user to create and memorize passwords easily. So, the combination of zero-knowledge protocol and steganography been
implemented with the GUA to make a better approach. The implemented algorithm has higher resistance toward shoulder surfing attack compare to
existed algorithm or method. From this alternative algorithm, proved that Graphical User Authentication with combination of zero-knowledge and
steganography is much better that the text-based authentication in term of usability and security.
PROBLEM STATEMENT
The problem arises because passwords are expected to comply with two
fundamentally conflicting requirements:
Passwords should be easy to remember, and the user authentication
protocol should be executable quickly and easily by humans [5, 6].
Passwords should be secure for example, they should look random
and should be hard to guess, they should be changed frequently, and
should be different on different accounts of the same user; they
should not be written down or stored in plain text [5].
OBJECTIVE
To propose the combination of the zero-knowledge protocol and
steganography techniques in the graphical password to provide the
authentication and confidentiality of the data [8].
To design an improved version of GUAS method with combination
steganography and zero-knowledge protocol that able to achieve
balance between the aspect of security, usability and reliability [9].
To implement an authentication approach based on graphical password
using zero-knowledge and steganography. (To test the secure graphical
password compared to text-based.)
CONCLUSION
Most of the existing authentication system has certain drawbacks for that
reason of text-based passwords. Meanwhile, GUA are most preferable
authentication system where users have to choose the images to
authenticate themselves. As authentication techniques generate passwords
it also need to resist the shoulder attack. The implemented of
steganography and zero-knowledge in GUA make much better solution in
user authentication in term of security.
FUTURE WORKS
So researchers of modern days have gone through different alternative
methods and concluded that graphical passwords are most preferable
authentication system.
By implementing encryption algorithms and hashing for storing and
retrieving pictures and data, one can achieve another level of security.
RESULTS
REFERENCES
1. Johnson, N., & Katzenbeisser, S. (2000). A survey of steganographic techniques. Information Hiding, September, 43–78.
2. Thampy, S. M., & Johny, A. (2015). Review on Graphical Password Authentication System.I-Manager’s Journal on Information Technology, 4(1), 33–38.
3. Professor, A. (2018). International Journal of Innovative Research in Computer and Communication Engineering Implementation of Graphical
Authentication System for Shoulder Surfing Attacks. 1082–1090.
4. Rupavathy, N., Carmel Mary Belinda, M. J., & Nivedhitha, G. (2018). A shoulder surfing resistance using graphical authentication system. International
Journal of Engineering and Technology(UAE), 7(1.7 Special Issue 7), 169–174.
5. Singh, K. J., & Chanu, U. S. (2013). Graphical Password or Graphical User Authentication as Effective Password Provider. 2(9), 2765–2769.
6. Vashishtha, L. K., Dutta, T., & Sur, A. (2013). Least significant bit matching steganalysis based on feature analysis. 2013 National Conference on
Communications, NCC 2013.