# Secure Audio-Visual Data Exchange for Android In-Vehicle Ecosystems
## 1 Introduction and Related Work  
Pairing smart mobile devices inside modern vehicles has become a common task. Due to the increased number of mobile devices that a user carries, e.g., smartphones, smartwatches, etc., finding a fast and efficient solution for secure associations is an immediate goal. In this work we explore the use of the audio-video domain in order to securely pair devices that are located in the same vehicle. Using audio channels is particularly attractive since modern vehicles can be well isolated from the outside, assuming that doors and windows are closed, and thus devices that do not belong to the in-vehicle environment cannot eavesdrop on the communication channel. Also, when ultrasounds are used, i.e., frequencies above the 16-18 kHz range, they will not impede humans which have reduced hearing above this range. However, as also proven by our experiments, audio channels are less reliable due to existing environmental noise and microphone calibration issues. On the contrary, visual channels are far more reliable and allow devices to easily exchange data with modern technologies such as QR codes [1, 2]. However, the visual channel may be easier to intercept from the outside and for this reason merging it with the audio channel will result in a more secure and reliable solution. This mixture of the audio and visual domains is the main idea behind our approach. Security wise, we use the elliptical curve version of the Diffie-Hellman [3] key-exchange protocol. The use of elliptical curves allows many more compact keys to be used, i.e., of 160 bits. The regular key shares of the Diffie-Hellman protocol are further exchanged partly by using the audio channel and partly by using the visual channel as we later discuss. For a crisper image of the exact capabilities of the audio channels we now recall some technical data from an existing study. The work in [4] obtains a bit error rate (BER) for audiochannels that is in the range of 6.44% to 14.59%. We have observed a similar behavior in our experiments and obtained similar bit error rates as shown later. Naturally, the error rate increases with the distance, and it also depends on the frequency. Higher frequencies will tend to be more directional, and they do not have the same power as mid-range frequencies, i.e., smartphone speakers will not behave so well above the 15 kHz range. Since we are interested in exchanging keys that are at a minimum of 160 bits in length, i.e., this is the smallest size for an elliptical curve that still offers sufficient security, we choose to keep the interaction on the audio channel as low as possible. Thus, we add to the audio channel a visual channel by which the vehicle head unit can further expose its key share. To obtain a secure secret key based on the elliptical curve version of the Diffie-Hellman [3] key-exchange protocol, we use the handshake that is graphically suggested in Figure 1. In this graphical depiction, by \(P(\xi)\) we denote the elliptic curve point altered by the in-vehicle noise extracted as \(\xi\) in accordance with the SPEKE protocol described in [5]. A smartphone acoustically emits toward the head unit the value of \(aP\). Further, the head unit shares the value of \(bP\) over the visual channel and the secret session key that results from the Diffie-Hellman key-exchange, i.e., \(k_{\text{s}es}=abP\), is further used to encrypt a secret. In our case, we use the Wi-Fi network SSID and password as a secret which will allow the phone and head unit to connect to the same Wi-Fi network. We use the Wi-Fi connection key just as an example, clearly this can be replaced by any useful information. As an additional means to increase security, we use the in-vehicle noise to bootstrap security bits in the generation of the elliptical curve point \(P\) which is necessary for the guessing-resilient authenticated key-agreement protocol SPEKE described in [5]. This protocol was later analyzed in [6] and is known to be secure.