Proxy re-encryption schemes for IoT and crowd sensing

IoT, crowd sensing and smart cities will be a traffic challenge. New communication paradigms as asynchronous messaging carry and forward, scheduled delivery and temporary storage will be needed to manage network resources dynamically. Since traditional end to end security will require keeping security associations among devices for a long time draining valuable resources, we propose and evaluate the use of proxy re-encryption protocols in these scenarios as a solution for reliable and flexible security

Secure store and forward proxy for dynamic IoT applications over M2M networks

Internet of Things (IoT) applications are expected to generate a huge unforeseen amount of traffic flowing from Consumer Electronics devices to the network. In order to overcome existing interoperability problems, several standardization bodies have joined to bring a new generation of Machine to Machine (M2M) networks as a result of the evolution of wireless sensor/actor networks and mobile cellular networks to converged networks. M2M is expected to enable IoT paradigms and related concepts into a reality at a reasonable cost. As part of the convergence, several technologies preventing new IoT services to interfere with existing Internet services are flourishing. Responsive, message-driven, resilient and elastic architectures are becoming essential parts of the system. These architectures will control the entire data flow for an IoT system requiring sometimes to store, shape and forward data among nodes of a M2M network to improve network performance. However, IoT generated data have an important personal component since it is generated in personal devices or are the result of the observation of the physical world, so rises significant security concerns. This article proposes a novel opportunistic flexible secure store and forward proxy for M2M networks and its mapping to asynchronous protocols that guarantees data confidentiality

A Framework Based on Distributed Ledger Technologies for Data Management and Services in Intelligent Transportation Systems

Data are becoming the cornerstone of many businesses and entire systems infrastructure. Intelligent Transportation Systems (ITS) are no different. The ability of intelligent vehicles and devices to acquire and share environmental measurements in the form of data is leading to the creation of smart services for the benefit of individuals. In this paper, we present a system architecture to promote the development of ITS using distributed ledgers and related technologies. Thanks to these, it becomes possible to create, store and share data generated by users through the sensors on their devices or vehicles, while on the move. We propose an architecture based on Distributed Ledger Technologies (DLTs) to offer features such as immutability, traceability and verifiability of data. IOTA, a promising DLT for IoT, is used together with Decentralized File Storages (DFSes) to store and certify data (and their related metadata) coming from vehicles or by the users' devices themselves (smartphones). Ethereum is then exploited as the smart contract platform that coordinates the data sharing through access control mechanisms. Privacy guarantees are provided by the usage of distributed key management systems and Zero Knowledge Proof. We provide experimental results of a testbed based on real traces, in order to understand if DLT and DFS technologies are ready to support complex services, such as those that pertain to ITS. Results clearly show that, while the viability of the proposal cannot be rejected, further work is needed on the responsiveness of DLT infrastructures

Blockchain-based Data Management for Smart Transportation

Smart services for Intelligent Transportation Systems (ITS) are currently deployed over centralized system solutions. Conversely, the use of decentralized systems to support these applications enables the distribution of data, only to those entities that have the authorization to access them, while at the same time guaranteeing data sovereignty to the data creators. This approach not only allows sharing information without the intervention of a “trusted” data silo, but promotes data verifiability and accountability. We discuss a possible framework based on decentralized systems, with a focus on four requirements, namely data integrity, confidentiality, access control and persistence. We also describe a prototype implementation and related performance results, showing the viability of the chosen approach

Real-Time Crowd Counting based on wearable Ephemeral IDs

Crowd Counting is a very interesting problem aiming at counting people typically based on density averages and/or aerial images. This is very useful to prevent crowd crushes, especially on urban environments with high crowd density, or to count people in public demonstrations. In addition, in the last years, it has become of paramount importance for pandemic management. For those reasons, giving users automatic mechanisms to anticipate high risk situations is essential. In this work, we analyze ID-based Crowd Counting, and propose a real-time Crowd Counting system based on the Ephemeral ID broadcast by contact tracing applications on wearable devices. We also performed some simulations that show the accuracy of our system in different situations