Application of Stochastic Diffusion for Hiding High Fidelity Encrypted Images

Cryptography coupled with information hiding has received increased attention in recent years and has become a major research theme because of the importance of protecting encrypted information in any Electronic Data Interchange system in a way that is both discrete and covert. One of the essential limitations in any cryptography system is that the encrypted data provides an indication on its importance which arouses suspicion and makes it vulnerable to attack. Information hiding of Steganography provides a potential solution to this issue by making the data imperceptible, the security of the hidden information being a threat only if its existence is detected through Steganalysis. This paper focuses on a study methods for hiding encrypted information, specifically, methods that encrypt data before embedding in host data where the ‘data’ is in the form of a full colour digital image. Such methods provide a greater level of data security especially when the information is to be submitted over the Internet, for example, since a potential attacker needs to first detect, then extract and then decrypt the embedded data in order to recover the original information. After providing an extensive survey of the current methods available, we present a new method of encrypting and then hiding full colour images in three full colour host images with out loss of fidelity following data extraction and decryption. The application of this technique, which is based on a technique called ‘Stochastic Diffusion’ are wide ranging and include covert image information interchange, digital image authentication, video authentication, copyright protection and digital rights management of image data in general

A Fingerprint Image Encryption Scheme Based on Hyperchaotic Rössler Map

Currently, biometric identifiers have been used to identify or authenticate users in a biometric system to increase the security in access control systems. Nevertheless, there are several attacks on the biometric system to steal and recover the user’s biometric trait. One of the most powerful attacks is extracting the fingerprint pattern when it is transmitted over communication lines between modules. In this paper, we present a novel fingerprint image encryption scheme based on hyperchaotic Rössler map to provide high security and secrecy in user’s biometric trait, avoid identity theft, and increase the robustness of the biometric system. A complete security analysis is presented to justify the secrecy of the biometric trait by using our proposed scheme at statistical level with 100% of NPCR, low correlation, and uniform histograms. Therefore, it can be used in secure biometric access control systems

Implementasi Metode Chaotic Encryption Dan Discrete Fourier Transform Untuk Menyembunyikan Data Biometrik Sidik Jari Ke Dalam Sinyal Audio

Keamanan adalah salah satu isu terpenting pada era ini, terutama untuk keamanan data biometrik sidik jari. Pada umumnya, sistem yang menggunakan data biometrik sidik jari menyimpan atau mengirim data tersebut dalam bentuk gambar. Sistem penyimpanan atau pengiriman data sidik jari seperti ini rentan terhadap serangan dari pihak-pihak seperti administrator basis data yang memiliki akses ke dalam basis data, serta peretas yang dapat menginterupsi pengiriman data. Maka dari itu, dibutuhkan suatu metode penyembunyian data biometrik sidik jari ke dalam bentuk yang lebih aman agar data sidik jari dapat dikirim melalui jaringan yang tidak aman. Pada Tugas Akhir ini dibentuk solusi menggunakan metode Chaotic Encryption dan Discrete Transform Fourier (DFT) untuk menyembunyikan data biometrik sidik jari ke dalam sinyal audio. Metode penyembunyian sidik jari ke dalam sinyal audio ini memiliki 4 tahapan, yakni enkripsi data sidik jari dengan Chaotic Encryption, transformasi sinyal audio ke dalam domain frekuensi dengan DFT, penyisipan viii data terenkripsi ke dalam domain frekuensi hasil DFT dengan kuantisasi, dan pengembalian sampel frekuensi hasil kuantisasi ke dalam sinyal audio dalam domain waktu dengan Inverse Discrete Fourier Transform (IDFT). Metode ekstraksi gambar dari sidik jari terdiri dari 3 tahapan yang merupakan komplemen dari proses-proses penyembunyian. Metode Chaotic Encryption yang digunakan adalah Skew Tent Map Encryption yang terbukti lebih unggul dibandingkan metode Chaotic Encryption yang lain. Tugas akhir ini juga mencari perbandingan metode Discrete Fourier Transform antara Walsh-Hadamard Transform (WHT) dan Discrete Cosine Transform (DCT). Proses kuantisasi adalah perubahan sampel frekuensi ke bentuk normalisasinya sesuai data yang ingin disisipkan. Di dalamnya terdapat variabel penting yang mempengaruhi kinerja aplikasi ini yang disebut quantization step (Δ), dimana variabel ini akan menjadi parameter yang diuji cobakan pada Tugas Akhir ini. Hasil uji coba menunjukkan bahwa kedua metode transformasi fourier dapat menghasilkan sinyal audio yang tidak terdengar perbedaannya bila dibandingkan dengan audio yang asli, dapat merekonstruksi gambar sidik jari dengan akurasi sebesar 100%, dan memiliki ketahanan yang sama terhadap Additive White Gaussian Noise dengan varians sebesar 484, apabila menggunakan nilai quantization step yang optimal yang bernilai 61x10-4 untuk metode Discrete Cosine Transform dan 31x10-6 untuk metode Walsh-Hadamard Transform. Perbedaan yang signifikan terletak pada running time, dimana running time DCT adalah 0,04 detik, sedangkan running time WHT adalah 1,77 detik. ====================================================================================================== Nowadays, security is one of the most important issues, especially the security of fingerprint biometric data. In general, a system which uses fingerprint data stores and transmits in the form of images. This data storage or\ud transmission system is vulnerable to attack by any party such as database administrator who has an access to the database, as well as hackers who is able to interrupt the transmission of fingerprint data. Therefore, there is a need to hide fingerprint data to a safer form so that it can be sent over nonsecure networks. This final project develops solution by using the Chaotic Encryption and the Discrete Fourier Transform (DFT) method to hide a fingerprint data into audio signals. This method consists of 4 steps. First, the fingerprint data is encrypted by Chaotic Encryption. Second, the transformation of the audio signal into a frequency domain by DFT. Third, the insertion of data into the frequency domain by quantization. And fourth, the reconstruction of audio signal by Inverse x Discrete Fourier Transform (IDFT). Fingerprint extraction method consists of 3 steps which are the complement of the data hiding method. The Chaotic Encryption method which is used in this final project is Skew Tent Map Encryption which shows superiority against other Chaotic Encryption method. This final project also tries to compare a better Discrete Fourier Transform method between Walsh-Hadamard Transform (WHT) and Discrete Cosine Transform (DCT). The quantization process modifies a frequency sample to a normalized form frequency sample using the corresponding data that needs hiding. This process also uses a certain variable which affects the performance of this application, called the quantization step (Δ). The experimental results shows that an optimal quantization value for WHT is 61x10-6 and for DCT is 31x10-4. The experimental results also shows a comparison between those fourier transform method using four different parameters. First, the difference between the audio-stego signal and the original audio signal must not be recognized by human auditory system. Second, the extraction method must be able to construct the fingerprint data with an accuracy of 100%. Third, the extraction method must be able to construct the fingerprint data with a minimum accuracy of 99,41% after the audio-stego signal is added by an Additive White Gaussian Noise with a variance of 484. And fourth, the running time of both fourier transform methods. Both fourier transform methods are able to satisfy the first three parameters with no significant result. However on the fourth parameter, the DFT shows a better and significant performance compared to the WHT, whereupon the running time of DFT is 0,04 seconds and the running time of WHT is 1,77 seconds