Unlocking the Power Of Acoustic Cryptography
By Tom Seest
At BestCybersecurityNews, we help entrepreneurs, solopreneurs, young learners, and seniors learn more about cybersecurity.
Acoustic cryptanalysis, also known as acoustic cryptoanalysis, is an attack that uses sound from cryptosystems to extract encryption keys. It’s similar to van Eck’s phreaking, which utilizes electromagnetic radiation and voltage fluctuations from computer screens to decrypt information before it has been encrypted.
Acoustic cryptanalysis has been around for decades, and its technology is becoming so pervasive that it poses a serious risk to our data. Here’s what you should be aware of regarding this technique and how to defend against it.
Table Of Contents
Acoustic cryptanalysis in cybersecurity refers to the use of sound to decrypt encryption. It’s a type of side-channel attack that exploits sounds generated by computer hardware and has been around for years, becoming an important issue within cryptography research.
One of the earliest acoustic attacks was reportedly employed in 1956 by MI5 to detect changes to cipher settings on Egyptian Hagelin cipher machines. By listening to the sounds of the machine being reset, they were able to recognize the new settings and crack the ciphers accordingly.
Acoustic cryptoanalysis began to gain mainstream adoption during the 1960s and 1970s when FFT (frequency domain) hardware became affordable enough for intercepting sound emissions from computers. Other devices like impact printers and electromechanical deciphering machines also underwent similar attacks during this timeframe, but they tended to be more complicated and less successful.
Thus, most acoustic cryptanalysis attacks involve listening for specific acoustic events during cryptographic decryption. These changes in frequency or time can be used to determine the corresponding secret key bit, and attackers then perform a chosen ciphertext attack in order to fully extract the decryption key.
Modern computers often emit acoustic emissions that can be picked up with a microphone when placed close by and at an optimal orientation. This is especially true of laptop computers whose cooling fan vent holes often leak.
Our experiments demonstrate that these emanations are remarkably informative, providing useful data about CPU activity. Furthermore, they can be detected at reasonable distances and even in different locations within one computer.
Unfortunately, computer speakers are not completely transparent to physical side-channel countermeasures such as air gaps or Faraday cages. For instance, sound coming from the vent hole of a fan cannot be suppressed by an acoustic absorber or soundproof enclosure and may still be picked up with a microphone placed close by the vent. Furthermore, noise generated from computers may also be muffled by other electromagnetic interference sources like fan motors and pulse width modulation (PWM) driving circuits.
Acoustic cryptanalysis exploits the sounds electronic devices emit to access confidential data. These attacks are commonly employed by nation-state intelligence agencies and law enforcement officers, but they’re also popular with hackers.
Acoustic cryptanalysis techniques were originally limited to printing and encryption machines; however, recent research has demonstrated they can also be applied to computer keyboards, ATM pads, and telephone number pads. These methods use a neural network to differentiate different key sounds and recover text from audio recordings of keys being pressed.
Acoustic cryptanalysis is the most popular cryptanalysis method, which involves listening in on keyboard keystrokes with a microphone and computer software. This can provide attackers with passwords, passphrases, and personal identification numbers (PINs) based on sounds made when keys are pressed.
Researchers at Tel Aviv University have previously demonstrated how acoustic cryptanalysis can be employed to extract RSA keys, one of the most popular encryption algorithms. This technique, known as a side channel attack, was demonstrated by three Israeli security researchers at Tel Aviv University.
To exploit acoustic leakage, an attacker creates a special form of ciphertext that makes sound depend on one secret key bit. They then trigger the decryption of that ciphertext, record its audio output, and analyze it to extract the key bits.
This type of attack has the advantage of being relatively inexpensive; however, it requires a sophisticated machine-learning model. This makes it an attractive option for nation-state intelligence agencies and law enforcement authorities; however, there are risks involved as well.
Acoustic cryptanalysis can be challenging to detect due to its low bandwidth, and results are sensitive to noise. This makes acoustic cryptanalysis more risky than other techniques which require more powerful computers with better bandwidth.
The most dangerous risk is that an attacker could use acoustic cryptanalysis to spy on other systems or even themselves – this is known as “self-spying”, and poses a major challenge for security professionals.
To carry out such an attack, the attacker must be able to control a computer process with only microphone recording permissions and network connectivity. Furthermore, the microphone must be close enough to capture sounds from an unprotected computer system.
Acoustic cryptanalysis is a type of side-channel attack that utilizes sounds emitted by electronic components. These sounds can provide information about the operation of the system, such as power consumption or timing signals.
Many computers emit a high-pitched noise during operation due to vibrations in some components. These noises can provide insight into the software running on the machine and, in particular, may leak sensitive information related to security-related computations.
Many techniques have been employed to prevent such attacks, such as acoustic shielding, algorithmic techniques, and application-layer mitigations that render emanations less useful to attackers (e.g., by decreasing power consumption).
The most effective countermeasure against sound attacks is sound-dampening equipment, such as “sound-proof” enclosures. This reduces the signal-to-noise ratio and makes these attacks more challenging to execute. Another option is decreasing the size of emanations by altering their execution path or padding them with random values before decryption.
In the past, researchers have employed acoustic cryptanalysis to break encryption systems such as RSA. Different secret key bits cause different sounds during decryption, and three Israeli researchers recently demonstrated how they can extract 4096-bit RSA keys from GnuPG by recording its CPU sound while running decryption routines.
They achieved this by creating a special form of ciphertext that made sound leakage dependent upon each secret key bit’s value. After activating decryption on each ciphertext, they recorded and analyzed its audio output.
These techniques can be highly efficient, but they require a significant amount of computational power and are generally costly to implement.
Fortunately, there are a variety of countermeasures that can be implemented in cryptographic libraries. These include ciphertext randomization, ciphertext normalization and modulus randomization.
These countermeasures help guarantee that the behavior of the ciphertext decryption algorithm is independent from input it receives, which is essential for avoiding side channel attacks. Though some may incur performance penalties, these solutions have been successfully integrated into several cryptographic implementations due to their cost-efficiency and effectiveness.
Acoustic cryptanalysis, also known as audio cryptanalysis in cybersecurity circles, is the practice of exploiting sounds generated by devices or internal computer hardware to circumvent encryption. This technique dates back to the 1960s and 1970s when affordable FFT hardware enabled malicious actors to intercept acoustic signals.
Acoustic cryptanalysis, though less popular today than it once was, still plays a significant role in cybersecurity. It can be employed to eavesdrop on keystrokes and detect power consumption by electronic components.
Acoustic cryptanalysis works by listening to the noises generated by a device or internal computer hardware as it performs security-related computations. It falls under the category of side-channel attacks, which are defined as “a statistical technique that exploits leakage information in the circuitry of an object or subsystem to predict or affect its behavior.
Shamir and Eran recently demonstrated how acoustic cryptanalysis can be used to quickly extract RSA keys from GnuPG using only low-bandwidth detection. They proposed various mitigation strategies, such as shrinking ciphertexts through randomization, adding modulus randomization into encipher text decryption processes and employing application-layer algorithms that don’t leak much timing information.
The acoustic detection algorithm employed in this attack is advanced, using high-frequency and ultrasonic measurements that are more precise than traditional microphones. It can detect sound emissions from computer keyboards, ATM pads, phone number pads, and notebook keyboards, as well as internal computer hardware like RAM or processors.
These techniques aren’t 100% reliable; however, the bandwidth of acoustic signals is relatively narrow (only 20 kHz for typical acoustic signals and several hundred kHz for ultrasound microphones). Furthermore, acoustic detection can be highly susceptible to interference from other noise sources.
In the future, countermeasures may include soundproof enclosures and acoustic absorbers. While these are likely less effective than other techniques, they could at least reduce signal-to-noise ratio and make acoustic detection harder to attain.
Please share this post with your friends, family, or business associates who may encounter cybersecurity attacks.