Biblio

We tackle the problem where a server owns a trained Machine Learning (ML) model and a client/user has an unclassified query that he wishes to classify in secure and private fashion using the server’s model. During the process the server learns nothing, while the user learns only his final classification and nothing else. Since several ML classification algorithms, such as deep neural networks, support vector machines-SVM (and hyperplane decisions in general), Logistic Regression, Naïve Bayes, etc., can be expressed in terms of matrix operations, initially we propose novel secure matrix operations as our building blocks. On top of them we build our secure and private ML classification algorithms under strict security and privacy requirements. As our underlying cryptographic primitives are shown to be resilient to quantum computer attacks, our algorithms are also suitable for the post-quantum world. Our theoretical analysis and extensive experimental evaluations show that our secure matrix operations, hence our secure ML algorithms build on top of them as well, outperform the state of the art schemes in terms of computation and communication costs. This makes our algorithms suitable for devices with limited resources that are often found in Industrial IoT (Internet of Things)

The natural redundancy in video data due to its spatio-temporal correlation of neighbouring pixels require highly complex encryption process to successfully cipher the data. Conventional encryption methods are based on lengthy keys and higher number of rounds which are inefficient for low powered, small battery operated devices. Motivated by the success of lightweight encryption methods specially designed for IoT environment, herein an efficient method for video encryption is proposed. The proposed technique is based on a recently proposed encryption algorithm named Secure IoT (SIT), which utilizes P and Q functions of the KHAZAD cipher to achieve high encryption at low computation cost. Extensive simulations are performed to evaluate the efficacy of the proposed method and results are compared with Secure Force (SF-64) cipher. Under all conditions the proposed method achieved significantly improved results.

Nowadays, the proliferation of smart, communication-enable devices is opening up many new opportunities of pervasive applications. A major requirement of pervasive applications is to be secured. The complexity to secure pervasive systems is to address a end-to-end security level: from the device to the services according to the entire life cycle of devices, applications and platform. In this article, we propose a solution combining both hardware and software elements to secure communications between devices and pervasive platform based on certificates issued from a Public Key Infrastructure. Our solution is implemented and validated with a real device extended by a secure element and our own Public Key Infrastructure.