Acoustic side-channel attacks are a type of side-channel attack that exploits the sound emitted by a target system. These attacks can steal sensitive data, such as passwords or credit card numbers.
Deep learning is a type of artificial intelligence that can learn complex patterns from data. In acoustic side-channel attacks, deep learning can be used to train a model to classify the sounds emitted by a keyboard into different keystrokes.
How Does a Deep Learning-Based Acoustic Side-Channel Attack Work?
The attack works by first recording the sound of the keyboard. The sound is then converted into a mel spectrogram, a graphical representation of the frequency content of the sound over time. The mel spectrogram is then fed into a deep learning model, which is trained to classify the sounds into different keystrokes.
The deep learning model is trained on a Mel spectrogram dataset labeled with the corresponding keystrokes. Once the model is trained, it can be used to classify the sound of a keyboard in real-time.
Recent Research Into Deep Learning-Based Acoustic Side-Channel Attacks
The accuracy of deep learning-based acoustic side-channel attacks is very high. In a recent test, researchers achieved an accuracy of 95% when using the attack to decipher laptop keystrokes.
When trained on keystrokes recorded by a nearby phone, the classifier achieved an accuracy of 95%, the highest accuracy seen without the use of a language model. When trained on keystrokes recorded using the video-conferencing software Zoom, an accuracy of 93% was achieved, a new best for the medium. Our results prove the practicality of these side channel attacks via off-the-shelf equipment and algorithms. We discuss a series of mitigation methods to protect users against these series of attacks. 
This attack is a reminder that side-channel attacks are a severe threat to security. Users should take steps to protect their devices from these attacks, such as using a keyboard cover or a noise-canceling microphone.
Here are some additional tips for protecting your devices from deep learning-based acoustic side-channel attacks:
- Use a keyboard cover. A keyboard cover can help to block the sound emitted by the keyboard.
- Use a noise-canceling microphone. A noise-canceling microphone can help to reduce the background noise that could interfere with the attack.
- Keep your device away from potential attackers. If an attacker is close to your device, they can collect more accurate sound data.
- Update your device's firmware. Firmware updates can often include security patches that can help to protect your device from side-channel attacks.
- Be aware of the risks. Side-channel attacks are a real threat, but they are not well-known. Be mindful of the risks and take steps to protect your devices.
How an IT Services Provider Can Mitigate These Challenges
A managed IT services provider can help address acoustic side-channel attacks in several ways:
- Educate employees about the risks. Managed IT services providers can educate employees about the dangers of acoustic side-channel attacks and how to protect themselves. This education can be provided in various ways, such as through training sessions, email newsletters, and intranet articles.
- Install security software. Managed IT services providers can install security software on employees' devices to help protect them from acoustic side-channel attacks. This software can include firewalls, antivirus software, and intrusion detection systems.
- Monitor for suspicious activity. Managed IT services providers can monitor employees' devices for suspicious activity, such as unusual keystroke patterns or attempts to access sensitive data. This monitoring can help to identify and prevent acoustic side-channel attacks.
- Update software regularly. Managed IT services providers can update employees' software regularly to help protect them from known security vulnerabilities. This includes updating operating systems, firmware, and applications.
- Implement physical security measures. Managed IT services providers can implement physical security measures to help protect employees' devices from acoustic side-channel attacks. This can include locking devices in cabinets or rooms and using noise-canceling technology in meeting rooms.
- https://www.facebook.com/thehackernews. (n.d.). New "Deep Learning Attack" Deciphers Laptop Keystrokes with 95% Accuracy. The Hacker News. Retrieved August 14, 2023, from https://thehackernews.com/2023/08/new-deep-learning-attack-deciphers.html
- Side-channel attack. (2023, August 9). In Wikipedia. https://en.wikipedia.org/wiki/Side-channel_attack
- Harrison, J., Toreini, E., & Mehrnezhad, M. (2023). A Practical Deep Learning-Based Acoustic Side Channel Attack on Keyboards. ArXiv. https://doi.org/10.1109/EuroSPW59978.2023.00034
- Gartzman, D. (2020, January 16). Getting to Know the Mel Spectrogram. Medium. https://towardsdatascience.com/getting-to-know-the-mel-spectrogram-31bca3e2d9d0
- Lindskog, N. (2023, April 28). Why side-channel analysis attacks are increasing and how to stop them (H. Englund, Ed.) [Review of Why side-channel analysis attacks are increasing and how to stop them]. Erricson.com; Erricson. https://www.ericsson.com/en/blog/2023/4/side-channel-analysis
Dai, Z., Liu, H., Le, Q. V., & Tan, M. (2021). CoAtNet: Marrying Convolution and Attention for All Data Sizes. ArXiv. https://arxiv.org/abs/2106.04803
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