Smart Home

In this paper, a fuzzy ontology for Semantic Sensor Networks (SSN) is proposed for smart homes in two phases. In the first phase, using the WordNet ontology, the location and type of an object is identified with the aid of a graphical interface. This object and its synonyms are added to the list of the known objects set. Succeeding, the relation of the object with other groups is assessed based on a similarity measure in addition to using the fuzzy ontology. In the second phase, sensors with erroneous information are identified and pruned by finding a relationship between some specific factors. To this end, temperature, moisture and light are considered and the Adaptive Neuro-Fuzzy Inference System (ANFIS) is incorporated. The proposed method is implemented using some parts of the Wikipedia database and the WordNet dictionary. The first phase of the proposed method is tested with several sample requests and the system shows favorable results on finding the original group (and other related groups) of the request. For training the neural network in the second phase, the Intel lab Dataset is used. Results of this phase show that the neural network can predict the temperature and moisture factors with low error, while the light factor has more error in prediction

The smart home is an important Internet of Things applications. Due to the smartphones development, expansion of their network, and growing the data transfer rate, security in personal life has become a dramatic challenge. Therefore, it is essential to secure such a system to create a sense of relaxation in the lives of users and homeowners to deal with possible occurrences. The integration of technologies for the automation of home affairs with the Internet of things means that all physical objects can be accessed on cyberspace; therefore, the concerns raised by users about the lack of privacy and security are serious arguments that science and technology should answer. Therefore, addressing security issues is a crucial necessity for the development of the smart homes. Although authentication protocols have been proposed based on smart cards for multi-server architectures, their schemes cannot protect the system against stolen smart cards and dictionary attacks in the login phase and do not satisfy perfect forward secrecy. To overcome these limitations, this paper proposes an anonymous, secure protocol in connected smart home environments, using solely lightweight operations. The proposed protocol in this paper provides efficient authentication, key agreement, and enables the anonymity of devices and unlinkability. It is demonstrated that the computation complexity of the protocol is low as compared to the existing schemes, while security has been significantly improved. This protocol ensures that even if the stakeholder’s device or the IoT device is attacked, they are robust against them.