A novel multipurpose watermarking scheme capable of protecting and authenticating images with tamper detection and localisation abilities

Technologies that fall under the umbrella of Industry 4.0 can be classified into one of its four significant components: cyber-physical systems, the internet of things (IoT), on-demand availability of computer system resources, and cognitive computing. The success of this industrial revolution lies in how well these components can communicate with each other, and work together in finding the most optimised solution for an assigned task. It is achieved by sharing data collected from a network of sensors. This data is communicated via images, videos, and a variety of other signals, attracting unwanted attention of hackers. The protection of such data is therefore pivotal, as is maintaining its integrity. To this end, this paper proposes a novel image watermarking scheme with potential applications in Industry 4.0. The strategy presented is multipurpose; one such purpose is authenticating the transmitted image, another is curtailing the illegal distribution of the image by providing copyright protection. To this end, two new watermarking methods are introduced, one of which is for embedding the robust watermark, and the other is related to the fragile watermark. The robust watermark's embedding is achieved in the frequency domain, wherein the frequency coefficients are selected using a novel mean-based coefficient selection procedure. Subsequently, the selected coefficients are manipulated in equal proportion to embed the robust watermark. The fragile watermark's embedding is achieved in the spatial domain, wherein self-generated fragile watermark(s) is embedded by directly altering the pixel bits of the host image. The effective combination of two domains results in a hybrid scheme and attains the vital balance between the watermarking requirements of imperceptibility, security and capacity. Moreover, in the case of tampering, the proposed scheme not only authenticates and provides copyright protection to images but can also detect tampering and localise the tampered regions. An extensive evaluation of the proposed scheme on typical images has proven its superiority over existing state-of-the-art methods

Analysis of Deep Learning Methods for Wired Ethernet Physical Layer Security of Operational Technology

The cybersecurity of power systems is jeopardized by the threat of spoofing and man-in-the-middle style attacks due to a lack of physical layer device authentication techniques for operational technology (OT) communication networks. OT networks cannot support the active probing cybersecurity methods that are popular in information technology (IT) networks. Furthermore, both active and passive scanning techniques are susceptible to medium access control (MAC) address spoofing when operating at Layer 2 of the Open Systems Interconnection (OSI) model. This thesis aims to analyze the role of deep learning in passively authenticating Ethernet devices by their communication signals. This method operates at the physical layer or Layer 1 of the OSI model. The security model collects signal data from Ethernet device transmissions, applies deep learning to gather distinguishing features from signal data, and uses these features to make an authentication decision on the Ethernet devices. The proposed approach is passive, automatic, and spoof-resistant. The role of deep learning is critical to the security model. This thesis will look at analyzing and improving deep learning at each step of the security model including data processing, model training, model efficiency, transfer learning on new devices, and device authentication

A NOVEL TECHNIQUE FOR SECURE ENCRYPTED MESSAGES IN MOBILE AND PERVASIVE APPLICATIONS

More than applications rely on the existence of small devices that can exchange information and form communication networks. In a significant portion of such applications, the confidentiality and integrity of the communicated messages are of particular interest. In this work, to propose two novel techniques for authenticating short encrypted messages that are directed to meet the requirements of mobile and pervasive applications. By taking advantage of the fact that the message to be authenticated must also be encrypted, to propose provably secure authentication codes that are more efficient than any message authentication code in the literature. The key idea behind the proposed techniques is to utilize the security that the encryption algorithm can provide to design more efficient authentication mechanisms, as opposed to using standalone authentication primitives

Twofold Video Hashing with Automatic Synchronization

Video hashing finds a wide array of applications in content authentication, robust retrieval and anti-piracy search. While much of the existing research has focused on extracting robust and secure content descriptors, a significant open challenge still remains: Most existing video hashing methods are fallible to temporal desynchronization. That is, when the query video results by deleting or inserting some frames from the reference video, most existing methods assume the positions of the deleted (or inserted) frames are either perfectly known or reliably estimated. This assumption may be okay under typical transcoding and frame-rate changes but is highly inappropriate in adversarial scenarios such as anti-piracy video search. For example, an illegal uploader will try to bypass the 'piracy check' mechanism of YouTube/Dailymotion etc by performing a cleverly designed non-uniform resampling of the video. We present a new solution based on dynamic time warping (DTW), which can implement automatic synchronization and can be used together with existing video hashing methods. The second contribution of this paper is to propose a new robust feature extraction method called flow hashing (FH), based on frame averaging and optical flow descriptors. Finally, a fusion mechanism called distance boosting is proposed to combine the information extracted by DTW and FH. Experiments on real video collections show that such a hash extraction and comparison enables unprecedented robustness under both spatial and temporal attacks.Comment: submitted to Image Processing (ICIP), 2014 21st IEEE International Conference o

Paperless Transfer of Medical Images: Storing Patient Data in Medical Images

Medical images have become an integral part ofpatient diagnosis in recent years. With the introduction of HealthInformation Management Systems (HIMS) used for the storageand sharing of patient data, as well as the use of the PictureArchiving and Communication Systems (PACS) formanipulating and storage of CT Scans, X-rays, MRIs and othermedical images, the security of patient data has become a seriousconcern for medical professionals. The secure transfer of theseimages along with patient data is necessary for maintainingconfidentiality as required by the Data Protection Act, 2011 inTrinidad and Tobago and similar legislation worldwide. Tofacilitate this secure transfer, different digital watermarking andsteganography techniques have been proposed to safely hideinformation in these digital images. This paper focuses on theamount of data that can be embedded into typical medical imageswithout compromising visual quality. In addition, ExploitingModification Direction (EMD) is selected as the method of choicefor hiding information in medical images and it is compared tothe commonly used Least Significant Bit (LSB) method.Preliminary results show that by using EMD there little to nodistortion even at the highest embedding capacity