# Special Issue \"Internet of Things for Smart Homes\"
## 2 A Review of the Contributions in this Special Issue
The expanding market for smart homes affords a more pleasant and more natural way of life to users while introducing new hurdles for protecting privacy. Moreover, due to the intrinsic features of wireless devices and smart appliances, such as resource limitations and the adoption of the wireless medium, they are expected to be exposed to different attacks. In such circumstances, cryptographic methods should be employed to preserve user privacy and wireless devices against various attacks. The authors of [6] analyze the security vulnerabilities in modern three-factor authentication and key agreement schemes. They introduce a system model for smart homes based on wireless devices in which a secure and lightweight three-factor authentication and key agreement scheme are employed. In the security verification, the authors prove that the proposed design satisfies the security specifications and resists against different attacks. The physical-layer security for a cognitive Internet of things model is assessed in [7]. The authors propose a cooperative jammer selection transmission protocol to preserve the information of primary users against eavesdropping. The numerical results reveal that the proposed protocol has more reliable primary secrecy performance than the non-security management model. The authors of [8] describes security threats, such as privacy infringement and personal information leak, in smart homes constituted by IoT devices. They address the evaluation method of these threats from the framework of situational awareness and exhibits the way of IoT threat knowledge from the viewpoint of decision-makers or managers. The obtained evaluations can provide support for a real-time response to the swiftly growing security operating environment of the future and can afford to periodic risk estimation in response to cyber threats, cyber-attacks, and cyber warfare from a perspective of national security. Software applications could manage smart home appliances. Consequently, the software protection of these devices is crucial. The authors of [9] introduce a reverse engineering analysis prevention method employing the relationship between Dalvik bytecode and machine code. The suggested scheme preserves the application from the static analysis by restricting the exposure of the Dalvik bytecode, which is easier to investigate confronted with machine code. The reverse engineering defense of the scheme presented by the authors is confirmed through reverse engineering analysis tests on its application. Smart home environments represent a significant interdisciplinary research field of computer science that is situated at the crossing of computer networks, applied computing, and embedded systems. In detail, the center on smart features led the research community to the application and experimentation of different intelligent computing methods and networks for improving the performance of smart home environments. The authors of [10] introduce a design project for a single-equipment with a multiple-application system for commanding a robot car based on Arduino in a smart environment. The suggested system practices a mechanism for managing the robot car based on hand gesture recognition and commands it based on a mobile application with touch buttons and voice recognition. The results obtained in extensive experiments confirm the simplicity, adaptability, dependability, specificity, and real low cost of the proposed system. Consequently, it could be easily implemented in smart cars or smart homes. Knowledge of things framework, able to share local information between IoT devices requiring similar or identical data at the edge, is proposed in [11]. The prototype developed by the authors consists of a smart mirror and a smart doorbell which require the same knowledge for face recognition. The outcomes of the investigations reveal that the proposed framework decreases both the response time to practice intelligent IoT devices and the power consumption for computation.