GÖRÜNTÜ DOSYALARININ ŞİFRELENEREK GÜVENLİ ŞEKİLDE SAKLANMASI

With the increase in internet usage and technological developments, people take hundreds of photos every day. Photos increasing day by day take up a lot of space in the phone memory. Storing these photos in flash memory, computers and phones is not very reliable due to situations such as loss and corruption. This situation has created the need for new storage areas other than the phone. Cloud storage systems are used as an alternative at this point. Cloud storage areas contain security measures against system access and attacks, but they do not directly work on the images uploaded to the system. Cloud accounts are sometimes hijacked by malicious people and photos of people can be stolen. In order to prevent this situation, a system that uses encryption algorithms on the image before storage has been proposed. Various symmetric encryption algorithms under CodeIgniter (PHP Framework) have been compared in the system and the application results are presented. Instead of using their own extensions of the image files to be encrypted, it is ensured that the images are stored with a different file extension in the Amazon Web Service environment or local environment after they are encrypted. When malicious people who want to capture images encounter a file with a different extension, they will not be able to directly determine that it is an image file. With thesystem proposed in this study, it is aimed to provide a safer storage opportunity regardless of the environment in which the images are stored

Authenticated public key elliptic curve based on deep convolutional neural network for cybersecurity image encryption application

The demand for cybersecurity is growing to safeguard information flow and enhance data privacy. This essay suggests a novel authenticated public key elliptic curve based on a deep convolutional neural network (APK-EC-DCNN) for cybersecurity image encryption application. The public key elliptic curve discrete logarithmic problem (EC-DLP) is used for elliptic curve Diffie–Hellman key exchange (EC-DHKE) in order to generate a shared session key, which is used as the chaotic system’s beginning conditions and control parameters. In addition, the authenticity and confidentiality can be archived based on ECC to share the (Formula presented.) parameters between two parties by using the EC-DHKE algorithm. Moreover, the 3D Quantum Chaotic Logistic Map (3D QCLM) has an extremely chaotic behavior of the bifurcation diagram and high Lyapunov exponent, which can be used in high-level security. In addition, in order to achieve the authentication property, the secure hash function uses the output sequence of the DCNN and the output sequence of the 3D QCLM in the proposed authenticated expansion diffusion matrix (AEDM). Finally, partial frequency domain encryption (PFDE) technique is achieved by using the discrete wavelet transform in order to satisfy the robustness and fast encryption process. Simulation results and security analysis demonstrate that the proposed encryption algorithm achieved the performance of the state-of-the-art techniques in terms of quality, security, and robustness against noise- and signal-processing attacks