Hardware Implementations of Video Watermarking

Various digital watermarking (WM) techniques for still imaging have been studied in the last several years. Recently, many new WM schemes have been proposed for other types of digital multimedia data, such as text, audio and video. This paper presents a brief overview of existing digital video WM. We classify WM techniques and discuss the properties of video WM. Since each WM application has its own specific requirements, WM design must take the intended application into consideration. Video WM applications are also discussed in the paper. The features of video WM implementations in software and hardware and their differences are presented through the description of four examples of existing work

Wireless Multimedia Sensor Networks Applications and Security Challenges

The emergence of low-cost and mature technologies in wireless communication, visual sensor devices, and digital signal processing facilitate of wireless multimedia sensor networks (WMSNs). Like sensor networks which respond to sensory information such as humidity and temperature, WMSN interconnects autonomous devices for capturing and processing video and audio sensory information. WMSNs will enable new applications such as multimedia surveillance, traffic enforcement and control systems, advanced health care delivery, structural health monitoring, and industrial process control. Due to WMSNs have some novel features which stem the fact that some of the sensor node will have video cameras and higher computation capabilities. Consequently, the WMSNs bring new security of challenges as well as new opportunities. This paper presents WMSNs application and security challenges

Copyright Protection for Digital Images on Portable Devices

The astonishing rapid diffusion of portable devices (i.e. smartphones, tablets, etc.) has had a big, and often positive, impact on our every-day life. These devices have new advanced features developed specifically because of user demand. For example, it is now possible to publish directly the pictures obtained by means of the internal camera of a smartphone on our social network accounts, or on an image hosting service. It is therefore important to have tools, on the portable devices, that can prove the ownership of the pictures and to use them before publishing images. Digital watermarking techniques are commonly used for the copyright protection of images and videos. We have developed a tool for portable devices based on the Android OS that allows the embedding of a digital visible or invisible watermark into a digital image

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

Copyright protection of scalar and multimedia sensor network data using digital watermarking

This thesis records the research on watermarking techniques to address the issue of copyright protection of the scalar data in WSNs and image data in WMSNs, in order to ensure that the proprietary information remains safe between the sensor nodes in both. The first objective is to develop LKR watermarking technique for the copyright protection of scalar data in WSNs. The second objective is to develop GPKR watermarking technique for copyright protection of image data in WMSN

Global motion compensated visual attention-based video watermarking

Imperceptibility and robustness are two key but complementary requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often suffer from embedding distortions resulting in poor visual quality in host media. This paper proposes a unique video watermarking algorithm that offers a fine balance between imperceptibility and robustness using motion compensated wavelet-based visual attention model (VAM). The proposed VAM includes spatial cues for visual saliency as well as temporal cues. The spatial modeling uses the spatial wavelet coefficients while the temporal modeling accounts for both local and global motion to arrive at the spatiotemporal VAM for video. The model is then used to develop a video watermarking algorithm, where a two-level watermarking weighting parameter map is generated from the VAM saliency maps using the saliency model and data are embedded into the host image according to the visual attentiveness of each region. By avoiding higher strength watermarking in the visually attentive region, the resulting watermarked video achieves high perceived visual quality while preserving high robustness. The proposed VAM outperforms the state-of-the-art video visual attention methods in joint saliency detection and low computational complexity performance. For the same embedding distortion, the proposed visual attention-based watermarking achieves up to 39% (nonblind) and 22% (blind) improvement in robustness against H.264/AVC compression, compared to existing watermarking methodology that does not use the VAM. The proposed visual attention-based video watermarking results in visual quality similar to that of low-strength watermarking and a robustness similar to those of high-strength watermarking