The Industrial Internet of Things (IIoT) plays a powerful role in smart manufacturing by performing real-time analysis for large volumes of data. In addition, IIoT systems can monitor several factors, such as data accuracy, network bandwidth and operations latency. To perform these operations securely and in a privacy-preserving manner, one solution is to use cryptographic primitives. However, most cryptographic solutions add performance overhead causing latency. In this paper, we propose an Edge Lightweight Searchable Attributebased encryption system (ELSA). ELSA leverages the cloudedge architecture to improve search time beyond the state-of-theart. The main contributions of this paper are as follows. First, we present an untrusted cloud/trusted edge architecture, which optimises the efficiency of data processing and decision making in the IIoT context. Second, we enhance search performance over current state-of-the-art (LSABE-MA) by an order of magnitude. We achieve this by improving the organisation of the data to provide better than linear search performance. We leverage the edge server to cluster data indices by keyword and introduce a query optimiser. The query optimiser uses k-means clustering to improve the efficiency of range queries, removing the need for linear search. In addition, we achieve this without sacrificing accuracy over the results.

The digitalisation of industrial manufacturing needs the support of systems technology to enhance the efficiency of manufacturing operations, product quality, and smart decisions. This digitalisation can be achieved by the industrial internet of things (IIoT). IIoT has played a powerful role in smart manufacturing by performing real-time analysis for a large volume of data. One possible approach to perform these operations in a secure and privacy-preserving manner is to utilise cryptographic solutions. In previous work, we proposed searchable encryption with an access control algorithm for IIoT based on an edgecloud architecture, namely ELSA. This paper extends ELSA to illustrate the correlation between the number of keywords and ELSA performance. This extension supports annotating records with multiple keywords in trapdoor and record storage and allows the record to be returnable with single-keyword queries. In addition, the experiments demonstrate the scalability and efficiency of ELSA with an increasing number of keywords and complexity.

Watermarking techniques are modern and strong methods of copyright protection for authors and companies as well as for ensuring the authority and identification. They hide the company's motto or policy of using for any digital content that exchanged via the internet. Various requirements are needed to embed the watermark in digital media like transparency, capacity, security and robustness against attacks. However, applying watermark on video, with visual and audio stream parts, is still a resource of concern for scientists and interested people to ensure the integrity of the whole video and guarantee that no manipulation was made on the video. In this research, a system is presented for video copyright protection taking into account its integrity and achieving all requirements in watermarking. The system will embed the watermark in both audio and visual streams allowing the transparency control in the watermarked video. Comparing to previous works, our experimental results showed better performance under the terms of robustness against attacks.