Speakertospeaker covert ultrasonic communication Abstract   In this paper we show how two or more airgapped computers in the same room, equipped with passive speakers, headphones, or earphones can covertly exchange data via ultrasonic waves. Microphones are not required. Our method is based on the capability of a malware to exploit a specific audio chip feature in order to reverse the connected speakers from output devices into input devices  unobtrusively rendering them microphones. We discuss the attack model and provide technical background and implementation details. We show that although the reversed speakersheadphonesearphones were not originally designed to perform as microphones, they still respond well to the nearultrasonic range (18xc2xa0kHz to 24xc2xa0kHz). We evaluate the communication channel with different equipment, and at various distances and transmission speeds, and also discuss some practical considerations. Our results show that the speakertospeaker communication can be used to covertly transmit data between two airgapped computers positioned a maximum of 9xc2xa0m away from one another. Moreover, we show that two (microphoneless) headphones can exchange data from a distance of 3xc2xa0m apart. This enables xe2x80x98headphonestoheadphonesxe2x80x99 covert communication, which is discussed for the first time in this paper.

Compromising Speech Privacy under Continuous Masking in Personal Spaces This paper explores the effectiveness of common sound masking solutions deployed for preserving speech privacy in workplace environment such as hospitals, financial institutions, lawyers offices, nursing homes and government buildings. With the increased awareness about personal privacy among the general population, we set out to examine the effectiveness of current speech privacy preserving tools. We seek to determine if the general approach used by the current masking mechanisms is adequate to provide the level of privacy desired from these solutions. In addition, we also seek to investigate preservation of speech privacy in the face of ubiquitous and less conspicuous devices like smartphones that possess the capability of sound recording with inbuilt noise cancellation technology. Our approach in this paper is to expose the vulnerability in sound masking technology in scenarios that require preserving privacy in personal spaces. We use human listeners to attack speech privacy under sound masking where we aim to identify spoken words eavesdropped under different scenarios. We also test currently available speech recognition tools to assess their performance at decoding speech in noisy environment. Our results indicate that pink noise, the commonly used technology to provide speech privacy for use in personal space, is ineffective against a dedicated eavesdropping adversary that uses commonplace devices such as smartphones to record the speech and noise reduction tools to counteract sound masking.