Quantum computing has rapidly progressed from a theoretical concept to real—even if still nascent—hardware accessible via the cloud. With this progress comes new security concerns, most notably side-channel attacks, which exploit unintentional information leaks to compromise systems. Recent research reveals sophisticated side-channel risks not only in classical but also in quantum systems, threatening both quantum computation and communication.
In this post, we'll delve deep into:
A side-channel attack is a method for extracting secret information from a system not by breaking its algorithms, but by analyzing physical or analog phenomena produced during operation. They use the 'side effects'—like timing, power consumption, sound, electromagnetic leaks—of handling or processing protected data.
Quantum systems, just like classical, interact with their environment. Their operations—via lasers, microwaves, or electrical pulses—can inadvertently reveal handled data. As Quantum Key Distribution (QKD) and cloud quantum processors become more widespread, attackers can exploit quantum-specific side-channels, sometimes remotely!
Quantum computers use qubits, which exist in superpositions of 0 and 1. Operations (gates) are applied using precise control pulses—microwave, optical, or electrical signals—that manipulate these qubits according to quantum algorithms.
Control pulses (commonly microwave signals in IBM/Google hardware) are integral to all quantum operations:
Any variance or pattern in these pulses can theoretically act as a side-channel.
A 2023 study, "Power Side Channels of Quantum Computing", introduced and evaluated five novel attacks that leverage control pulse information—data retrievable even via cloud quantum computers.
Let's briefly overview each:
pulse access (limited on most public backends, but enough for analysis).Diagram: Attack Flow
User uploads quantum job → Control software compiles to pulses → Pulses sent to hardware (logs available) → Adversary accesses logs → Secrets inferred
In a 2025 study by the University of Toronto (Phys.org coverage), researchers identified unexpected, multi-dimensional side-channels in real-world quantum communication systems, threatening protocols like QKD.
Suppose Alice and Bob use a commercial QKD system. An attacker, Eve, captures not only the intended signal photons but also those in previously disregarded modes (spectral, temporal, polarization). Eve, using advanced detectors, reconstructs a partial key—without raising suspicion.
Whether it’s control pulses in computation or multi-mode leaks in communication, quantum tech is far from immune to side-channel risks.
Even as we transition to Post-Quantum Cryptography (PQC) (classical algorithms designed to be quantum-resistant), side-channel resilience is a critical requirement.
According to Secure-IC:
# Toy example: Masking a secret with random value in Python
import secrets
def mask_secret(secret):
mask = secrets.randbelow(1 << len(bin(secret)))
masked = secret ^ mask
# During processing, use (masked, mask) instead of secret directly
return (masked, mask)
def unmask(masked, mask):
return masked ^ mask
# Example usage:
secret = 12345
masked, mask = mask_secret(secret)
recovered = unmask(masked, mask)
assert recovered == secret
Detecting and analyzing side-channel leakage requires a combination of active scanning, log inspection, and signal analysis.
# Example: Find all IBM Quantum Qiskit pulse logs in local directory
find ./qiskit_jobs/ -type f -iname "*pulse*" -print
Suppose you have pulse log files (JSON format). Here's how you might extract gate timings.
import json
import glob
for fname in glob.glob('./qiskit_jobs/*pulse*.json'):
with open(fname) as f:
pulse_data = json.load(f)
for instr in pulse_data.get('experiment', {}).get('instructions', []):
print(f"Qubit: {instr.get('qubit')}, Duration: {instr.get('duration')}, Start: {instr.get('t0')}")
You could analyze for repeated gate sequences indicating algorithm structure leaks.
from collections import Counter
def extract_patterns(pulse_instructions, window=3):
patterns = []
for i in range(len(pulse_instructions) - window + 1):
pattern = tuple(pulse_instructions[i:i+window])
patterns.append(pattern)
return patterns
all_patterns = []
for fname in glob.glob('./qiskit_jobs/*pulse*.json'):
with open(fname) as f:
pulse_data = json.load(f)
instrs = [instr['name'] for instr in pulse_data.get('experiment', {}).get('instructions', [])]
all_patterns.extend(extract_patterns(instrs))
pattern_counts = Counter(all_patterns)
for pat, count in pattern_counts.most_common(5):
print(f"Pattern {pat} seen {count} times")
grep -r 'qubit' ./qiskit_jobs/* | sort | uniq -c | sort -nr | head
To secure your quantum (and post-quantum) infrastructure:
Cultivate awareness that no cryptosystem is secure by design forever. Regularly evaluate hardware and software against the latest attack methodologies.
As quantum systems become increasingly mainstream—both for computation and for secure communications—the incentive to discover and exploit their side-channels grows.
Side-channel attacks are evolving in tandem with our hardware. Quantum computers and quantum communication systems introduce new, unique forms of potential leakage—some previously unknown until the latest research. Security engineers, system designers, and users must all be proactive, adopting best practices and staying informed as quantum systems move from the lab to the cloud. Regularly revisit your threat model. If there’s a channel, there could be a side-channel.
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