Biblio

The Internet of Things (IoT) relies on sensor devices to measure real-world phenomena in order to provide IoT services. The sensor readings are shared with multiple entities, such as IoT services, other IoT devices or other third parties. The collected data may be sensitive and include personal information. To protect the privacy of the users, the data needs to be protected through an encryption algorithm. For sharing cryptographic cipher-texts with a group of users Attribute-Based Encryption (ABE) is well suited, as it does not require to create group keys. However, the creation of ABE cipher-texts is slow when executed on resource constraint devices, such as IoT sensors. In this paper, we present a modification of an ABE scheme, which not only allows to encrypt data efficiently using ABE but also reduces the size of the cipher-text, that must be transmitted by the sensor. We also show how our modification can be used to realise an instantaneous key revocation mechanism.

Internet of Things (IoT) and 5G are emerging technologies that prompt a mobile service platform capable of provisioning billions of communication devices which enable ubiquitous computing and ambient intelligence. These novel approaches are guaranteeing gigabit-level bandwidth, ultra-low latency and ultra-high storage capacity for their subscribers. To achieve these limitations, ETSI has introduced the paradigm of Multi-Access Edge Computing (MEC) for creating efficient data processing architecture extending the cloud computing capabilities in the Radio Access Network (RAN). Despite the gained enhancements to the mobile network, MEC is subjected to security challenges raised from the heterogeneity of IoT services, intricacies in integrating virtualization technologies, and maintaining the performance guarantees of the mobile networks (i.e. 5G). In this paper, we are identifying the probable threat vectors in a typical MEC deployment scenario that comply with the ETSI standards. We analyse the identified threat vectors and propose solutions to mitigate them.

The heart of the Internet of Things (IoT) is data. IoT services processes data from sensors that interface their physical surroundings, and from other software such as Internet weather databases. They produce data to control physical environments via actuators, and offer data to other services. More recently, service-centric designs for managing the IoT have been proposed. Data-centric or name-based communication architectures complement these developments very well. Especially for edge-based or site-local installations, data-centric Internet architectures can be implemented already today, as they do not require any changes at the core. We present the Virtual State Layer (VSL), a site-local data-centric architecture for the IoT. Special features of our solution are full separation of logic and data in IoT services, offering the data-centric VSL interface directly to developers, which significantly reduces the overall system complexity, explicit data modeling, a semantically-rich data item lookup, stream connections between services, and security-by-design. We evaluate our solution regarding usability, performance, scalability, resilience, energy efficiency, and security.