Much of the effort into preventing these “side-channel attacks” has focused on the vulnerability of digital processors. Hackers, for example, can measure the electric current drawn by a smartwatch’s CPU and use it to reconstruct secret data being processed, such as a password.
MIT researchers recently published a paper in the IEEE Journal of Solid-State Circuits, which demonstrated that analog-to-digital converters in smart devices, which encode real-world signals from sensors into digital values that can be processed computationally, are vulnerable to power side-channel attacks. A hacker could measure the power supply current of the analog-to-digital converter and use machine learning algorithms to accurately reconstruct output data.
Now, in two new research papers, engineers show that analog-to-digital converters are also susceptible to a stealthier form of side-channel attack, and describe techniques that effectively block both attacks. Their techniques are more efficient and less expensive than other security methods.
Minimizing power consumption and cost are critical factors for portable smart devices, says Hae-Seung Lee, the Advanced Television and Signal Processing Professor of Electrical Engineering, director of the Microsystems Technology Laboratories, and senior author of the most recent research paper.
“Side-channel attacks are always a cat and mouse game. If we hadn’t done the work, the hackers most likely would have come up with these methods and used them to attack analog-to-digital converters, so we are preempting the action of the hackers,” he adds.
Joining Lee on the paper is first-author and graduate student Ruicong Chen; graduate student Hanrui Wang; and Anantha Chandrakasan, dean of the MIT School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. The research will be presented at the IEEE Symposium on VLSI Circuits. A related paper, written by first-author and graduate student Maitreyi Ashok; Edlyn Levine, formerly with MITRE and now chief science officer at America’s Frontier Fund; and senior author Chandrakasan, was recently presented at the IEEE Custom Integrated Circuits Conference.
The authors of the IEEE Journal of Solid-State Circuits paper are lead-author Taehoon Jeong, who was a graduate student at MIT and is now with Apple, Inc, Chandrakasan, and Lee, a senior author.
MIT researchers developed two security schemes that protect analog-to-digital converters (ADC) from power and electromagnetic side-channel attacks using randomization. On the left is a micrograph of an ADC that randomly splits the analog-to-digital conversion process into groups of unit increments and switches them at different times. On the right is a micrograph of an ADC that splits the chip into two halves, enabling it to select two random starting points for the conversion process while speeding up the conversion. Credit: Courtesy of the researchers
A noninvasive attack
To conduct a power side-channel attack, a malicious agent typically solders a resistor onto the device’s circuit board to measure its power usage. But an electromagnetic side-channel attack is noninvasive; the agent uses an electromagnetic probe that can monitor electric current without touching the device.
The researchers showed that an electromagnetic side-channel attack was just as effective as a power side-channel attack on an analog-to-digital converter, even when the probe was held 1 centimeter away from the chip. A hacker could use this attack to steal private data from an implantable medical device.
To thwart these attacks, the researchers added randomization to the ADC conversion process.
An ADC takes an unknown input voltage, perhaps from a biometric sensor, and converts it to a digital value. To do this, a common type of ADC sets a threshold in the center of its voltage range and uses a circuit called a comparator to compare the input voltage to the threshold. If the comparator decides the input is larger, the ADC sets a new threshold in the top half of the range and runs the comparator again.
This process continues until the unknown range becomes so small it can assign a digital value to the input.
The ADC typically sets thresholds using capacitors, which draw different amounts of electric current when they switch. An attacker can monitor the power supplies and use them to train a machine-learning model that reconstructs output data with surprising accuracy.
Randomizing the process
To prevent this, Ashok and her collaborators used a random number generator to decide when each capacitor switches. This randomization makes it much harder for an attacker to correlate power supplies with output data. Their technique also keeps the comparator running constantly, which prevents an attacker from determining when each stage of the conversion began and ended.
