| Internet of things is growing up so fast; it expected to be around 75 billion by 2025. Although the internet of things facilitated our life, however, it threats our privacy if we do not take the necessary security measures. Definitely, the attackers developed their capabilities with the fast revolution in Internet of things devices market, which is most of the time do not have high security precautions if any. In addition, Internet of things devices considers a good source for the private data due to its direct connection with the user. Internet of Things devices have a limited purpose with one kind of data. Therefore, the traffic that comes from a particular device reveals its functionality.For example, if the attacker recognizes the smart lock identities, he will know the data that comes from the smart lock means the user open/close the door. If the indoor motion camera sends the traffic that means there is a motion at that home. In this thesis, there will be a survey of the most security and privacy threats on the internet of things, examination of three commercial Internet of things devices (august smart lock, tuyaus smart bulb, ismartalarm) using home lab to show the vulnerabilities practically, the experiment implemented in home lab using only network traffic packets with no need for deep inspection. Since the data already was encrypted, however, in this experiment, there was a prediction for daily life activities for the user in his home using deep learning. In addition, a practical proposal introduced to mitigate the vulnerabilities of the IoT devices that found in this thesis. |
