Mitigating IoT data management security concerns through blockchain and machine learning based solutions: Study and Conceptual Design

The Internet of Things industry is expanding rapidly. However, many security breaches occur, and privacy is often at stake in traditional IoT networks. These centralized systems will not be able to cope with dynamically changing environments. In light of these risks, it is crucial to prevent and minimize the chances of attacks occurring....

Machine Learning-based Techniques for Secure and Efficient IoT Data Management

The dramatic increase in the number of Internet of Things (IoT) devices has created rapid growth for exploitation of security flaws and vulnerabilities. Particularly for critical infrastructure and real-time systems security threats can be highly damaging. Machine Learning (ML) algorithms have demonstrated the ability to combat the security...

Exploring effective notification mechanisms for infected IoT devices

Many Internet of Things (IoT) devices that are currently on the market lack security and therefore many of them got infected with malware to launch powerful distributed denial of service (DDoS) attacks. Notifications from Internet Service Providers (ISPs) to their customers play a crucial role in the fight to clean up the malware infected IoT...

LoRaWAN: Vulnerability Analysis and Practical Expoitation

Internet of Things (IoT) applications nowadays have a wide impact on people’s daily life while the size of IoT has been increasing rapidly. Millions of devices huge amount of data and different kinds of new protocols can bring many security issues.<br/>LoRaWAN is a MAC layer protocol for long-range low-power communication dedicated to the IoT....