The Future Internet of Things: Secure, Efficient, and Model-Based

Abstract

The Internet of Things' (IoT's) rapid growth is constrained by resource use and fears about privacy and security. A solution jointly addressing security, efficiency, privacy, and scalability is needed to support continued expansion. We propose a solution modeled on human use of context and cognition, leveraging cloud resources to facilitate IoT on constrained devices. We present an architecture applying process knowledge to provide security through abstraction and privacy through remote data fusion. We outline five architectural elements and consider the key concepts of the "Data Proxy" and the "Cognitive Layer." The Data Proxy uses system models to digitally mirror objects with minimal input data, while the Cognitive Layer applies these models to monitor the system's evolution and to simulate the impact of commands prior to execution. The Data Proxy allows a system's sensors to be sampled to meet a specified "Quality of Data" (QoD) target with minimal resource use. The efficiency improvement of this architecture is shown with an example vehicle tracking application. Finally, we consider future opportunities for this architecture to reduce technical, economic, and sentiment barriers to the adoption of the IoT.

Multimedia Internet of Things: A Comprehensive Survey

“…for enhancing efficiency, scalability, security, and privacy is presented in [58]. The article [59] proposes an energyefficient IoT architecture based on cloud computing, sensor sleep intervals, and QoI.…”

A Cognitive Protection System for the Internet of Things

“…We propose building Cognitive Supervisors and Firewalls using the architecture in Siegel (2017). 12 In this approach, all IoT systems and applications use the Cloud or other scalable computation as an intermediary among requests, commands, and responses. Systems are mirrored using Cloud-hosted Data Proxies, statistical or physical state-space models that take sparse sensor data and create a rich digital duplicate.…”

An Internet of Things-Based Low-Power Integrated Beekeeping Safety and Conditions Monitoring System

“…LoRaWAN header is at least 13 Bytes long (MHDR (1) + DevAddr (4) + FCtrl (1) + FCnt (2) + Fport (1) + MIC (4)) [30]. LoRaWAN maximum frame size is set up to 45 Bytes in order for the LoRaWAN gateway to operate in the edge of SF12 mode (maximum payload for SF12, 50 Bytes, SF7, 220 Bytes) [30,53]. The maximum LoRaWAN forwarding frame is the BSDP protocol forwarding frame that includes a 4 Byte application ID unique for each beehive array, the 1Byte Hive ID value identifying each beehive cell expanded to a 4 Byte value and 4 Byte values for each measurement (external-internal temperature humidity and sound/weight sensor and one 4 Byte for thermopad, peltier and humidity actuators).…”

“…The LoRaWAN scalability parameter is controlled with the over-the-air duty cycle parameter which is EU limited to 1% for all 868 MHz frequencies, leaving a maximum node data transmission time of 36 s per hour, and a minimum payload of 59 Bytes at SF7 [30,53,54]. Prior to data transmission, the central cell node authenticates with the gateway using the over-the-air activation method (OTAA) and the data transmission follows the class A transmission mode.…”