Exploring IoT Secuirty, Privacy and Data Protection
Abstract
Internet of things rapid growth is causing security and privacy concerns. Internet of medical things are devices designed for remote monitoring for the patients with chronic diseases. The security of the patient data at the collection, transmission and storage is critical for data integrity and privacy. The access to the patient data is limited only to users with high privileges i.e. for doctor and patient. On the other hand encrypted data is decrypted with shared keys by authorize user only. The technique is well suited for the access of data to only authentic users. The smart device connectivity with other devices is frequent that is sometimes raise questions related to security of these devices. The authentication of the devices is an important concern which is proposed this article. The authentication technique is robust as compared to other proposed technique due to having secure authentication at each step of devices to connect with main smart device. The Lightweight neural network method introduced for the network intrusion detection which is designed for IoT devices having low computing capability and low storage space. LNN model is excellent for classifying the smart devices traffic for normal and attack scenarios. In industrial IoTs trust management is the key factor to allow or deny the specific device to enter into the smart network. The trust between two nodes is calculated based on the device previous history with other devices. The approach is efficient for trust management based access to the devices. Fog assisted IoTs based on trust management and security component shows that their lightweight efficiency is higher as compared to other models for the security of resource constrained devices. For Industrial IoTs advanced encryption is best scenario where number of the devices frequently join and leave the network. The security measures at each level of the smart device is critical to security of data and privacy protection. The access based on human stored biodata or biometrics is secured enough for access to smart devices. The doubled encryption-decryption approach providing strong security measures for smart device generated data and users privacy. The Quick Response or QR code enabled technique providing critical information for device security enabled techniques increase buyer’s trust, which is important for deployment of security enabled smart devices around the world.
Keywords: Internet of things security, data protection, privacy, data encryption, network intrusion detection, fog-assisted IoTs, Trust management.
