Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection

QAM-DWT-SVD Based Watermarking Scheme for Medical Images

This paper presents a new semi-blind image watermarking system for medical applications. The new scheme utilizes Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) to embed a textual data into original medical images. In particular, text characters are encoded by a Quadrature Amplitude Modulation (QAM-16). In order to increase the security of the system and protect then the watermark from several attacks, the embedded data is submitted to Arnold Transform before inserting it into the host medical image. To evaluate the performances of the scheme, several medical images have been used in the experiments. Simulation results show that the proposed watermarking system ensures good imperceptibility and high robustness against several attacks

HYBRID WATERMARKING CITRA DIGITAL MENGGUNAKAN TEKNIK DWT-DCT DAN SVD

Sebagai salah satu teknik perlindungan data multimedia, watermarking telah banyak dikembangkan. Teknik watermarking dapat dilakukan pada domain transformasi, dengan menggabungkan metode Discrete Wavelet Transform (DWT) dan Discrete Cosine Transform (DCT).Watermarking pada citra digital harus memperhatikan tiga kriteria: security, robustness, dan imperceptibility. Dua kriteria terakhir merupakan hal yang paling sering bertentangan pada watermarking domain transformasi. Singular Value Decomposition (SVD) sebagai salah satu metode yang paling populer dari aplikasi aljabar linear telah banyak dimanfaatkan dalam pengolahan sinyal termasuk watermarking. Penggabungan DWT-DCT dan SVD ditujukan untuk mengatasi konflik di antara robustness dan imperceptibility. Nilai Peak Signal to Noise Ratio (PSNR) dan Normalized Cross Correlation (NC) yang diperoleh dari percobaan menyatakan bahwa skema hybrid watermarking ini menghasilkan watermark yang tahanterhadap berbagai serangan, serta kualitas yang tinggi dari citra yang disisipi watermark. Hal ini menunjukkan bahwa konflik antara robustness dan imperceptibility yang muncul pada watermarking domain transformasi dapat diatasi.Kata kunci : Watermarking, DWT, DCT, SV

Image Hiding on Audio Subband Based On Centroid in Frequency Domain

ABSTRAK Audio watermarking adalah mekanisme penyembunyian data pada audio. Metode penyembunyian data yang digunakan dalam penulisan ini adalah Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), Centroid dan Quantization Index Modulation (QIM). Langkah pertama adalah host audio tersegmentasi menjadi beberapa frame. Kemudian sub-band terpilih diubah oleh FFT dengan mengubah domain sub-band dari waktu ke frekuensi. Proses centroid digunakan untuk menemukan titik pusat frekuensi untuk lokasi penyisipan untuk mendapatkan output yang lebih stabil. Proses penyematan dilakukan dengan QIM. Kinerja watermarking oleh parameter yang disesuaikan memperoleh nilai imperceptibility dengan Signal to Noise Ratio (SNR) > 21 dB, Mean Opinion Score (MOS)> 3.8 dengan kapasitas = 86.13 bps. Selain itu, untuk sebagian besar file audio terwatermark yang diserang, metode ini tahan terhadap beberapa serangan seperti Low Pass Filter (LPF) dengan fco> 6 kHz, Band Pass Filter (BPF) dengan fco 50 Hz - 6 kHz, Linear Speed Change (LSC) dan MP4 Compression dengan Bit Error Rate (BER) kurang dari 20%. Kata kunci: FFT, subband, LWT, Centroid, Audio Watermarking, QIM   ABSTRACT Audio watermarking is a mechanism for hiding data on audio. Data hiding methods used in this paper are Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), Centroid and Quantization Index Modulation (QIM). The first step is to segment host audio into several frames, then the selected sub-band is changed by the FFT by changing the sub-band domain from time to frequency. The centroid process is used to find the center of frequency for the insertion location to get a more stable output. The embedding process is done by QIM. The watermarking performance by adjusted parameters obtains the imperceptibility value with Signal to Noise Ratio (SNR)> 21 dB, Mean Opinion Score (MOS)> 3.8 with a capacity = 86.13 bps. In addition, for most of attacked watermarked audio files, this method is resistant to several attacks such as Low Pass Filter (LPF) with fco> 6 kHz, Band Pass Filter (BPF) with fco 50 Hz - 6 kHz, Linear Speed Change (LSC) and MP4 Compression with Bit Error Rate (BER) less than 20%. Keywords: FFT, subband, LWT, Centroid, Audio Watermarking, QI

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

Alpha Channel Fragile Watermarking for Color Image Integrity Protection

This paper presents a fragile watermarking algorithm`m for the protection of the integrity of color images with alpha channel. The system is able to identify modified areas with very high probability, even with small color or transparency changes. The main characteristic of the algorithm is the embedding of the watermark by modifying the alpha channel, leaving the color channels untouched and introducing a very small error with respect to the host image. As a consequence, the resulting watermarked images have a very high peak signal-to-noise ratio. The security of the algorithm is based on a secret key defining the embedding space in which the watermark is inserted by means of the Karhunen–Loève transform (KLT) and a genetic algorithm (GA). Its high sensitivity to modifications is shown, proving the security of the whole system

A robust video watermarking using simulated block based spatial domain technique

A digital watermark embeds an imperceptible signal into data such as audio, video and images, for different purposes including authentication and tamper detection. Tamper detection techniques for video watermarking play a major role of forensic evidence in court. The existing techniques for concealing information in the multimedia host are mostly based on spatial domain rather than frequency domain. The spatial domain techniques are not as robust as frequency domain techniques. In order to improve the robustness of spatial domain, a watermark can be embedded several times repeatedly. In order for spatial domain techniques to be more efficient, more payload is needed to embed additional information. The additional information would include the redundant watermarks to ensure the achievable robustness and more metadata of pixels to ensure achievable efficiency to detect more attacks. All these required additional information will degrade the imperceptibility. This research focuses on video watermarking, particularly with respect to Audio Video Interleaved (AVI) form of video file format. The block-wise method is used to determine which block exactly altered. A high imperceptible and efficient tamper detection watermarking technique is proposed which embeds in first and second Least Significant Bits (LSB). The proposed technique divides the video stream to 2*2 nonoverlapping simulated blocks. Nine common attacks to video have been applied to the proposed technique. An imperceptible and efficient tamper detection technique with a novel method of video segmentation to comprise more pixels watermarked is proposed. Experimental results show the technique is able to detect the attacks with the average of Peak Signal-to-Noise Ratio (PSNR) as 47.87dB. The results illustrate the proposed technique improves imperceptibility and efficiency of tamper detection