Research On Secure Device Pairing For The Internet Of Things

The development of the Internet of Things(Io T)technology makes tremendous smart devices of Io T seamlessly integrate into people’s life,involving multiple fields such as home,education,logistics,and security.The smart devices of Io T are interconnected through wireless communication technology and have data sharing and information processing capabilities.With the built-in sensor chip,the smart device can sense the surrounding physical environment and provide more powerful and intelligent services.However,the open nature of wireless channels makes data exchanged between smart devices vulnerable to eavesdropping,tampering,and Man-in-the-Middle attacks.And the dynamic setting,highly distribution and diverse nature of the environment of Io T make it impractical to apply the traditional methods such as Public Key Infrastructure to establish secure channels.Secure device pairing is proposed to establish a secure communication channel at physical layer between legitimate devices to protect users’ privacy and promote the development of the Internet of Things.The existing pairing schemes based on the reciprocity of the wireless channel have disadvantages such as the need for specific detection tools,the need for very close distance between devices,and strict time alignment requirements.The context-based pairing schemes become new feasible schemes because legitimate devices can use sensors to perceive the ambient environment and extract environmental fingerprints for identity authentication and key agreement.In this paper,we mainly study the context-based secure device pairing schemes.For the two scenarios of Io T,which are wearable devices and smart homes,we propose two pairing mechanisms using acceleration and ambient sound signals as entropy sources respectively.1.For the wearable device scenario,we propose a gait-based secure device pairing scheme.Firstly,the built-in accelerometer and magnetometer sensors are used to collect the data when user is walking.Then acceleration signals and magnetometer signals are converted from the device’s local coordinate system to the world coordinate system to solve inconsistency problem of the device placement position and orientation.And we propose a position-aware data pre-processing method.Furthermore,we design a new quantization method,which can generate a shared key with sufficient randomness.To demonstrate the feasibility and evaluate the performance,experiments have been performed on a real-world data set of fifteen subjects’ seven different body parts.Our experimental results show that the method is robust against active attackers,and can significantly distinguish the intra-and inter-body cases.The similarity of the keys extracted from intra-body can reach 80%,then information reconciliation and privacy amplification technology are used to agree on a consistent shared key.2.For the smart home scenario,we propose an audio-based secure device pairing scheme.In the smart home scenario,legitimate devices are placed in the security boundary(exterior wall of the house).Due to the inconvenience of moving household appliances and their distances are a little bit far,we propose a pairing method that uses sound signals as the source of entropy.The protocol leverages the time interval between significant sound signals as a random source to extract the audio fingerprint.To increase the rate of key generation,an additional sound source is introduced,which can send sound pulse signals at random time intervals.At the same time,it can enhance the randomness of keys.Finally,the system prototype has been implemented on the Android platform.Lots of experiments have been performed in a real physical environment to prove that the solution can effectively resist attackers outside the security boundary,and the pairing success rate of legitimate devices within the security boundary reached 90%.