Biblio

The Internet of Things (IoT) is rapidly evolving, while introducing several new challenges regarding security, resilience and operational assurance. In the face of an increasing attack landscape, it is necessary to cater for the provision of efficient mechanisms to collectively verify software- and device-integrity in order to detect run-time modifications. Towards this direction, remote attestation has been proposed as a promising defense mechanism. It allows a third party, the verifier, to ensure the integrity of a remote device, the prover. However, this family of solutions do not capture the real-time requirements of industrial IoT applications and suffer from scalability and efficiency issues. In this paper, we present a lightweight dynamic control-flow property-based attestation architecture (CFPA) that can be applied on both resource-constrained edge and cloud devices and services. It is a first step towards a new line of security mechanisms that enables the provision of control-flow attestation of only those specific, critical software components that are comparatively small, simple and limited in function, thus, allowing for a much more efficient verification. Our goal is to enhance run-time software integrity and trustworthiness with a scalable and decentralized solution eliminating the need for federated infrastructure trust. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security do not hinder the deployment of intelligent edge computing systems.

We develop and evaluate a data hiding method that enables smartphones to encrypt and embed sensitive information into carrier streams of sensor data. Our evaluation considers multiple handsets and a variety of data types, and we demonstrate that our method has a computational cost that allows real-time data hiding on smartphones with negligible distortion of the carrier stream. These characteristics make it suitable for smartphone applications involving privacy-sensitive data such as medical monitoring systems and digital forensics tools.

We develop and evaluate a data hiding method that enables smartphones to encrypt and embed sensitive information into carrier streams of sensor data. Our evaluation considers multiple handsets and a variety of data types, and we demonstrate that our method has a computational cost that allows real-time data hiding on smartphones with negligible distortion of the carrier stream. These characteristics make it suitable for smartphone applications involving privacy-sensitive data such as medical monitoring systems and digital forensics tools.

Outsourcing a huge amount of local data to remote cloud servers that has been become a significant trend for industries. Leveraging the considerable cloud storage space, industries can also put forward the outsourced data to cloud computing. How to collect the data for computing without loss of privacy and confidentiality is one of the crucial security problems. Searchable encryption technique has been proposed to protect the confidentiality of the outsourced data and the privacy of the corresponding data query. This technique, however, only supporting search functionality, may not be fully applicable to real-world cloud computing scenario whereby secure data search, share as well as computation are needed. This work presents a novel encrypted cloud-based data share and search system without loss of user privacy and data confidentiality. The new system enables users to make conjunctive keyword query over encrypted data, but also allows encrypted data to be efficiently and multiply shared among different users without the need of the "download-decrypt-then-encrypt" mode. As of independent interest, our system provides secure keyword update, so that users can freely and securely update data's keyword field. It is worth mentioning that all the above functionalities do not incur any expansion of ciphertext size, namely, the size of ciphertext remains constant during being searched, shared and keyword-updated. The system is proven secure and meanwhile, the efficiency analysis shows its great potential in being used in large-scale database.