MIT Research News' Journal

Securing the “internet of things” in the quantum age

MIT researchers have developed a novel cryptography circuit that can be used to protect low-power “internet of things” (IoT) devices in the coming age of quantum computing.

Quantum computers can in principle execute calculations that today are practically impossible for classical computers. Bringing quantum computers online and to market could one day enable advances in medical research, drug discovery, and other applications. But there’s a catch: If hackers also have access to quantum computers, they could potentially break through the powerful encryption schemes that currently protect data exchanged between devices.

Today’s most promising quantum-resistant encryption scheme is called “lattice-based cryptography,” which hides information in extremely complicated mathematical structures. To date, no known quantum algorithm can break through its defenses. But these schemes are way too computationally intense for IoT devices, which can only spare enough energy for simple data processing.

In a paper presented at the recent International Solid-State Circuits Conference, MIT researchers describe a novel circuit architecture and statistical optimization tricks that can be used to efficiently compute lattice-based cryptography. The 2-millimeter-squared chips the team developed are efficient enough for integration into any current IoT device.

The architecture is customizable to accommodate the multiple lattice-based schemes currently being studied in preparation for the day that quantum computers come online. “That might be a few decades from now, but figuring out if these techniques are really secure takes a long time,” says first author Utsav Banerjee, a graduate student in electrical engineering and computer science. “It may seem early, but earlier is always better.”

Moreover, the researchers say, the circuit is the first of its kind to meet standards for lattice-based cryptography set by the National Institute of Standards and Technology (NIST), an agency of the U.S. Department of Commerce that finds and writes regulations for today’s encryption schemes.

Joining Banerjee on the paper are Anantha Chandrakasan, dean of MIT’s School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science, and Abhishek Pathak of the Indian Institute of Technology.

Efficient sampling

In the mid-1990s, MIT Professor Peter Shor developed a quantum algorithm that can essentially break through all modern cryptography schemes. Since then, NIST has been trying to find the most secure postquantum encryption schemes. This happens in phases; each phase winnows down a list of the most secure and practical schemes. Two weeks ago, the agency entered its second phase for postquantum cryptography, with lattice-based schemes making up half of its list.

In the new study, the researchers first implemented on commercial microprocessors several NIST lattice-based cryptography schemes from the agency’s first phase. This revealed two bottlenecks for efficiency and performance: generating random numbers and data storage.

Generating random numbers is the most important part of all cryptography schemes, because those numbers are used to generate secure encryption keys that can’t be predicted. That’s calculated through a two-part process called “sampling.”

Sampling first generates pseudorandom numbers from a known, finite set of values that have an equal probability of being selected. Then, a “postprocessing” step converts those pseudorandom numbers into a different probability distribution with a specified standard deviation — a limit for how much the values can vary from one another — that randomizes the numbers further. Basically, the random numbers must satisfy carefully chosen statistical parameters. This difficult mathematical problem consumes about 80 percent of all computation energy needed for lattice-based cryptography.

After analyzing all available methods for sampling, the researchers found that one method, called SHA-3, can generate many pseudorandom numbers two or three times more efficiently than all others. They tweaked SHA-3 to handle lattice-based cryptography sampling. On top of this, they applied some mathematical tricks to make pseudorandom sampling, and the postprocessing conversion to new distributions, faster and more efficient.

They run this technique using energy-efficient custom hardware that takes up only 9 percent of the surface area of their chip. In the end, this makes the process of sampling two orders of magnitude more efficient than traditional methods.

Splitting the data

On the hardware side, the researchers made innovations in data flow. Lattice-based cryptography processes data in vectors, which are tables of a few hundred or thousand numbers. Storing and moving those data requires physical memory components that take up around 80 percent of the hardware area of a circuit.

Traditionally, the data are stored on a single two-or four-port random access memory (RAM) device. Multiport devices enable the high data throughput required for encryption schemes, but they take up a lot of space.

For their circuit design, the researchers modified a technique called “number theoretic transform” (NTT), which functions similarly to the Fourier transform mathematical technique that decomposes a signal into the multiple frequencies that make it up. The modified NTT splits vector data and allocates portions across four single-port RAM devices. Each vector can still be accessed in its entirety for sampling as if it were stored on a single multiport device. The benefit is the four single-port REM devices occupy about a third less total area than one multiport device.

“We basically modified how the vector is physically mapped in the memory and modified the data flow, so this new mapping can be incorporated into the sampling process. Using these architecture tricks, we reduced the energy consumption and occupied area, while maintaining the desired throughput,” Banerjee says.

The circuit also incorporates a small instruction memory component that can be programmed with custom instructions to handle different sampling techniques — such as specific probability distributions and standard deviations — and different vector sizes and operations. This is especially helpful, as lattice-based cryptography schemes will most likely change slightly in the coming years and decades.

Adjustable parameters can also be used to optimize efficiency and security. The more complex the computation, the lower the efficiency, and vice versa. In their paper, the researchers detail how to navigate these tradeoffs with their adjustable parameters. Next, the researchers plan to tweak the chip to run all the lattice-based cryptography schemes listed in NIST’s second phase.

The work was supported by Texas Instruments and the TSMC University Shuttle Program.

Spider silk could be used as robotic muscle

Spider silk, already known as one of the strongest materials for its weight, turns out to have another unusual property that might lead to new kinds of artificial muscles or robotic actuators, researchers have found.

The resilient fibers, the team discovered, respond very strongly to changes in humidity. Above a certain level of relative humidity in the air, they suddenly contract and twist, exerting enough force to potentially be competitive with other materials being explored as actuators — devices that move to perform some activity such as controlling a valve.

The findings are being reported today in the journal Science Advances, in a paper by MIT Professor Markus Buehler, head of the Department of Civil and Environmental Engineering, along with former postdoc Anna Tarakanova and undergraduate student Claire Hsu at MIT; Dabiao Liu, an associate professor at Huazhong University of Science and Technology in Wuhan, China; and six others.

Researchers recently discovered a property of spider silk called supercontraction, in which the slender fibers can suddenly shrink in response to changes in moisture. The new finding is that not only do the threads contract, they also twist at the same time, providing a strong torsional force. “It’s a new phenomenon,” Buehler says.

“We found this by accident initially,” Liu says. “My colleagues and I wanted to study the influence of humidity on spider dragline silk.” To do so, they suspended a weight from the silk to make a kind of pendulum, and enclosed it in a chamber where they could control the relative humidity inside. “When we increased the humidity, the pendulum started to rotate. It was out of our expectation. It really shocked me.”

The researchers were able to decode the molecular structure of the two main proteins, shown here, that make up spider dragline silk. One of these, MaSp2, contains proline, which interacts with water molecules to produce the newly discovered twisting motion.

The team tested a number of other materials, including human hair, but found no such twisting motions in the others they tried. But Liu said he started thinking right away that this phenomenon “might be used for artificial muscles.”

“This could be very interesting for the robotics community,” Buehler says, as a novel way of controlling certain kinds of sensors or control devices. “It’s very precise in how you can control these motions by controlling the humidity.”

“This is a fantastic discovery because the torsion measured in spider dragline silk is huge, a full circle every millimeter or so of length,” says Pupa Gilbert, a professor of physics, chemistry, and materials science at the University of Wisconsin at Madison, who was not involved in this work. Gilbert adds, “This is like a rope that twists and untwists itself depending on air humidity. The molecular mechanism leading to this outstanding performance can be harnessed to build humidity-driven soft robots or smart fabrics.”

Spider silk is already known for its exceptional strength-to-weight ratio, its flexibility, and its toughness, or resilience. A number of teams around the world are working to replicate these properties in a synthetic version of the protein-based fiber.

While the purpose of this twisting force, from the spider’s point of view, is unknown, researchers think the supercontraction in response to moisture may be a way to make sure a web is pulled tight in response to morning dew, perhaps protecting it from damage and maximizing its responsiveness to vibration for the spider to sense its prey.

“We haven’t found any biological significance” for the twisting motion, Buehler says. But through a combination of lab experiments and molecular modeling by computer, they have been able to determine how the twisting mechanism works. It turns out to be based on the folding of a particular kind of protein building block, called proline.

Investigating that underlying mechanism required detailed molecular modeling, which was carried out by Tarakanova and Hsu. “We tried to find a molecular mechanism for what our collaborators were finding in the lab,” Hsu explains. “And we actually found a potential mechanism,” based on the proline. They showed that with this particular proline structure in place, the twisting always occurred in the simulations, but without it there was no twisting.

“Spider dragline silk is a protein fiber,” Liu explains. “It’s made of two main proteins, called MaSp1 and MaSp2.” The proline, crucial to the twisting reaction, is found within MaSp2, and when water molecules interact with it they disrupt its hydrogen bonds in an asymmetrical way that causes the rotation. The rotation only goes in one direction, and it takes place at a threshold of about 70 percent relative humidity.

“The protein has a rotational symmetry built in,” Buehler says. And through its torsional force, it makes possible “a whole new class of materials.” Now that this property has been found, he suggests, maybe it can be replicated in a synthetic material. “Maybe we can make a new polymer material that would replicate this behavior,” Buehler says.

“Silk’s unique propensity to undergo supercontraction and exhibit a torsional behavior in response to external triggers such as humidity can be exploited to design responsive silk-based materials that can be precisely tuned at the nanoscale,” says Tarakanova, who is now an assistant professor at the University of Connecticut. “Potential applications are diverse: from humidity-driven soft robots and sensors, to smart textiles and green energy generators.”

It may also turn out that other natural materials exhibit this property, but if so this hasn’t been noticed. “This kind of twisting motion might be found in other materials that we haven’t looked at yet,” Buehler says. In addition to possible artificial muscles, the finding could also lead to precise sensors for humidity.

These researchers “have used silk’s known high sensitivity to humidity and demonstrated that it can also be used in an interesting way to create very precise torsional actuators,” says Yonggang Huang, a professor of civil and environmental engineering and mechanical engineering at Northwestern University, who was not involved in this work. “Using silk as a torsional actuator is a novel concept that could find applications in a variety of fields from electronics to biomedicine, for example, hygroscopic artificial muscles and humidity sensors,” he says.

Huang adds, “What is particularly noteworthy about this work is that it combines molecular modeling, experimental validation, and a deep understanding by which elementary changes in chemical bonding scale up into the macroscopic phenomena. This is very significant from a fundamental science point of view, and also exciting for applications.”

The work included collaborators at Huazhong University of Science and Technology and Hubei University, both in Wuhan, China, and Queen Mary University of London. It was supported by the National Natural Science Foundation of China, the National Science Foundation of Hubei Province, the Young Elite Scientist Sponsorship Program by CAST, the National Institutes of Health, the MIT Undergraduate Research Opportunities Program, and the Office of Naval Research.