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Air-gapped computers are disconnected from the Internet physically and logically. This measure is taken in order to prevent the leakage of sensitive data from secured networks. In the past, it has been shown that malware can exfiltrate data from air-gapped computers by transmitting ultrasonic signals via the computer's speakers. However, such acoustic communication relies on the availability of speakers on a computer.In this paper, we present 'DiskFiltration,' a covert channel which facilitates the leakage of data from an air-gapped compute via acoustic signals emitted from its hard disk drive (HDD). Our method is unique in that, unlike other acoustic covert channels, it doesn't require the presence of speakers or audio hardware in the air-gapped computer. A malware installed on a compromised machine can generate acoustic emissions at specific audio frequencies by controlling the movements of the HDD's actuator arm. Digital Information can be modulated over the acoustic signals and then be picked up by a nearby receiver (e.g., smartphone, smartwatch, laptop, etc.). We examine the HDD anatomy and analyze its acoustical characteristics. We also present signal generation and detection, and data modulation and demodulation algorithms. Based on our proposed method, we developed a transmitter on a personal computer and a receiver on a smartphone, and we provide the design and implementation details. We also evaluate our covert channel on various types of internal and external HDDs in different computer chassis and at various distances. With DiskFiltration we were able to covertly transmit data (e.g., passwords, encryption keys, and keylogging data) between air-gapped computers to a smartphone at an effective bit rate of 180 bits/minute (10,800 bits/hour) and a distance of up to two meters (six feet).

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 [29]. We discuss the attack model and provide technical background and implementation details. We show that although the reversed speakers/headphones/earphones were not originally designed to perform as microphones, they still respond well to the near-ultrasonic range (18kHz to 24kHz). 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 speaker-tospeaker communication can be used to covertly transmit data between two air-gapped computers positioned a maximum of nine meters away from one another. Moreover, we show that two (microphone-less) headphones can exchange data from a distance of three meters apart. This enables 'headphones-to-headphones' covert communication, which is discussed for the first time in this paper.

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Additive manufacturing (AM, or 3D printing) is a novel manufacturing technology that has been adopted in industrial and consumer settings. However, the reliance of this technology on computerization has raised various security concerns. In this paper, we address issues associated with sabotage via tampering during the 3D printing process by presenting an approach that can verify the integrity of a 3D printed object. Our approach operates on acoustic side-channel emanations generated by the 3D printer's stepper motors, which results in a non-intrusive and real-time validation process that is difficult to compromise. The proposed approach constitutes two algorithms. The first algorithm is used to generate a master audio fingerprint for the verifiable unaltered printing process. The second algorithm is applied when the same 3D object is printed again, and this algorithm validates the monitored 3D printing process by assessing the similarity of its audio signature with the master audio fingerprint. To evaluate the quality of the proposed thresholds, we identify the detectability thresholds for the following minimal tampering primitives: insertion, deletion, replacement, and modification of a single tool path command. By detecting the deviation at the time of occurrence, we can stop the printing process for compromised objects, thus saving time and preventing material waste. We discuss various factors that impact the method, such as background noise, audio device changes, and different audio recorder positions.