The Internet of Things (IoT) network is comprised of heterogeneous devices which are part of critical infrastructures throughout the world. To enable end-to-end security, the Public Key Infrastructure (PKI) is undergoing advancements to incorporate IoT devices globally which primarily provides device authentication. In addition to this, integrity of the software-state is vital, where Remote Attestation (RA) and Integrity Certificates play an important role. Though, Integrity Certificate verifies the software-state integrity of the device at the time of execution of the remote attestation process, it does not provide mechanisms to validate that the current software-state corresponds to the attested state. This issue is referred to as the Time-Of-Check to Time-Of-Use (TOCTOU) problem and remains unsolved in the context of Integrity Certificates. In this paper, we propose AutoCert, the first TOCTOU-secure mechanism to combine software-state integrity with PKI for IoT which resolves the TOCTOU problem in RA and Integrity Certificates. To this end, we utilize the IETF Remote Attestation Procedures architecture and standard X509 IoT profile certificates to ensure both device authentication and software assurance for IoT. We implement and evaluate the performance of the AutoCert proof-of-concept on a real IoT device, the OPTIGA TPM Evaluation Kit, to show its practicality and usability. AutoCert can validate the attested state of an IoT device in approximately 4746 milliseconds, with a minimal network overhead of 350 bytes.

Securing IoT devices is gaining attention as the security risks associated with these devices increase rapidly. TrustZone-M, a Trusted Execution Environment (TEE) for Cortex-M processors, ensures stronger security within an IoT device by allowing isolated execution of security-critical operations, without trusting the entire software stack. However, TrustZone-M does not guarantee secure cross-world communication between applications in the Normal and Secure worlds. The cryptographic protection of the communication channel is an obvious solution; however, within a low-power IoT device, it incurs high overhead if applied to each cross-world message exchange. We present ShieLD, a framework that enables a secure communication channel between the two TrustZone-M worlds by leveraging the Memory Protection Unit (MPU). ShieLD guarantees confidentiality, integrity and authentication services without requiring any cryptographic operations. We implement and evaluate ShieLD using a Musca-A test chip board with Cortex-M33 that supports TrustZone-M. Our empirical evaluation shows, among other gains, the cross-zone communication protected with ShieLD is5 timesfaster than the conventional crypto-based communication.

Attestation is a fundamental building block to establish trust over software systems. When used in conjunction with trusted execution environments, it guarantees the genuineness of the code executed against powerful attackers and threats, paving the way for adoption in several sensitive application domains. This paper reviews remote attestation principles and explains how the modern and industrially well-established trusted execution environments Intel SGX, Arm TrustZone and AMD SEV, as well as emerging RISC-V solutions, leverage these mechanisms.

The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also dealing with safety and security challenges. The approach is based on a modular and scalable cognitive IoT hardware platform. Using modular microserver technology enables the user to configure the hardware to satisfy a wide range of applications. VEDLIoT offers a complete design flow for Next-Generation IoT devices required for collaboratively solving complex Deep Learning applications across distributed systems. The methods are tested on various use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage with the first results available.

Summary Recent developments in the cloud technologies have motivated the migration of distributed large systems, specifically the Internet of Things to the cloud architecture. Since Internet of Things consist of a vast network and variety of objects, the cloud platform proves to be an ideal option. It is essential for the proper functioning of the Internet of Things to be able to share data among the system processes. The biggest problem faced during the transition of the IoTs to the cloud is the security of data especially while data sharing within the cloud and among its tenants. Information Flow Control mechanisms are one of the many solutions to enable a controlled sharing of data. Integration of Information Flow Control Systems to the existing architecture requires various levels of re‐engineering efforts. Moreover, most of the Information Flow Control systems focus on data flow within the cloud and neglect the security and integrity of data while it is being transferred to the cloud from various devices. This research focuses on securing the entire process of data migration to cloud from devices while the in‐cloud data flow is monitored by the Information Flow Control policies specified by the users. We have developed a prototype for the proposed model, and results are evaluated on the basis of energy consumption and execution time. As proposed model provides security services such as privacy, integrity, and authentication, hence it takes more execution time and consumes more energy as compared with the existing model.