Security

The recent developments in the field of the Internet of Things (IoT) bring alongside them quite a few advantages. Examples include real-time condition monitoring, remote control and operation and sometimes even remote fault remediation. Still, despite bringing invaluable benefits, IoT-enriched entities inherently suffer from security and privacy issues. This is partially due to the utilization of insecure communication protocols such as the Open Charge Point Protocol (OCPP) 1.6. OCPP 1.6 is an application-layer communication protocol used for managing electric vehicle chargers.

The dataset contains thousands of signal frames from 60 ZigBee devices. The devices and USRP N210 were placed on two movable cabinets on wheels with a maximum distance of 3 meters between them. Due to distance constraints, a coaxial attenuator with an attenuation of 60 dB was fitted at the receiver in order to obtain signals at low SNR. The SNR of the received signal is changed by adjusting the distance between the two cabinets, which can be reduced to about 0 dB when the distance is about 3 metres.

One of the leading causes of early health detriment is the increasing levels of air pollution in major cities and eventually in indoor spaces. Monitoring the air quality effectively in closed spaces like educational institutes and hospitals can improve both the health and the life quality of the occupants. In this paper, we propose an efficient Indoor Air Quality (IAQ) monitoring and management system, which uses a combination of cutting-edge technologies to monitor and predict major air pollutants like CO2, PM2.5, TVOCs, and other factors like temperature and humidity.

DALHOUSIE NIMS LAB ATTACK IOT DATASET 2025-1 dataset comprises of four prevalent types attacks, namely Portscan, Slowloris, Synflood, and Vulnerability Scan, on nine distinct Internet of Things (IoT) devices. These attacks are very common on the IoT eco-systems because they often serve as precursors to more sophisticated attack vectors. By analyzing attack vector traffic characteristics and IoT device responses, our dataset will aid to shed light on IoT eco-system vulnerabilities.