Quantum Attack Simulation

The Quantum Attack Simulator aims to provide an educational and research-oriented tool for understanding the security of quantum communication systems. In version 1.0, the simulator focuses exclusively on the BB84 protocol, simulating its behavior under various attack scenarios and environmental conditions. This simulator helps visualize and analyze the impact of depolarization noise and two well-known quantum communication attacks: Man-in-the-Middle (MITM) and Photon Number Splitting (PNS).

• BB84 Protocol Overview
  • Key Components of BB84 Communication
  • BB84 Communication Process
• Depolarization Noise
• Attack Scenarios
  • Man-in-the-Middle (MITM) Attack
  • Photon Number Splitting (PNS) Attack
    • PNS Detection: Decoy State Method
• Simulation Example Scenarios

The BB84 protocol is a quantum key distribution protocol that enables two parties (commonly referred to as “Sender” and “Receiver”) to securely generate a shared cryptographic key.

In quantum cryptography, the BB84 protocol stands as a cornerstone, offering quantum mechanics and information security. Since its introduction by Bennett and Brassard in 1984, this protocol has been of immense study and practical application, more so in the area of quantum key distribution, QKD. In the article Quantum Key Distribution Protocols: BB84, I explained the inner details of the BB84 protocol, giving an overview of how it works and its theoretical background. This post goes further into the practical realization of QKD with the BB84 protocol.

The classical binary values (0 and 1) that form the basis of the key. For example, the Sender generates a random sequence of bits:
Sender's Bits: 1110010101010111111000010111011010000111

Each bit is assigned a state:

• Signal States (S): Qubits carrying actual information that contribute to the final cryptographic key.
• Decoy States (D): Qubits inserted into the communication to detect potential attacks like Photon Number Splitting (PNS).

Sender's States: SDSDSDSSSSSSSDDDDDSDSSSSSSSSSSSSDDDDSSDD

The basis used for encoding and measuring qubits. Two options are used in BB84:

• Z-Basis (Computational basis): Encodes bits as |0⟩ and |1⟩.
• X-Basis (Diagonal basis): Encodes bits as |+⟩ and |−⟩.

Sender's Bases: ZXXXZXZZZXXZXXZZXZZXZZZZZXZZXZXXXZZXXXZX

Qubits in decoy states are assigned intensity levels (low, medium, high) to improve attack detection. Signal states have none intensity since they are not used for detection:
Sender's Intensities: ['none', 'high', 'none', 'medium', 'none', ...]

The Sender encodes random bits into qubits using randomly chosen bases and sends them to the Receiver through a quantum channel.

The Receiver measures each qubit using a randomly chosen basis. When the Receiver’s basis matches the Sender’s, the bit is successfully transmitted. Otherwise, the measurement is random.

Example:
Receiver's Bases: XXZZXZZZZXXZZZXZZXXXZZXXXXZZZXXXXXXZZXXZ
Receiver's Bits: 1101100101011011000000110111111010001110

After transmission, the Sender and Receiver compare their bases (over a classical channel). Bits where the bases match are used to form the final cryptographic key.

The table below illustrates an example process where the Sender and Receiver generate a cryptographic key using signal states. The comparison of encoding bases and the resulting qubit representations determine which bits are kept to construct the final shared key.

The protocol includes checks for mismatches caused by noise or potential attacks. Decoy states and error analysis help identify anomalies, ensuring the security of the key.

Before starting, it is crucial to understand what depolarization noise is and how man-in-the-middle, PNS attacks work in communication with BB84.

Depolarization noise refers to the random flipping of qubit states during transmission due to imperfections in the quantum channel. This noise:

• Simulates natural environmental disturbances.
• Can be mistaken for eavesdropping unless carefully analyzed.

A MITM attack involves an adversary intercepting quantum communication between the Sender and Receiver:

• The attacker measures the qubits using a randomly chosen basis.
• After measurement, the attacker resends qubits to the Receiver, potentially introducing errors.

In a PNS attack, an adversary exploits decoy states by:

• Measuring one or more photons from a multi-photon signal.
• Forwarding the remaining photons to the Receiver.
• This reduces the attacker’s detection probability but increases error rates at certain intensity levels.

This type of attack leverages the vulnerability of quantum channels when multiple photons are emitted simultaneously, such as in certain implementations of quantum communication systems. By selectively intercepting and measuring a portion of the photons, the attacker can gain partial information about the transmitted key while minimizing detection risks.

Decoy states play a crucial role in detecting this type of attack by enabling an analysis of error rates across different intensity levels. Higher error rates in decoy states compared to the expected threshold may indicate the presence of a PNS attack.

The Decoy State Method plays a critical role in detecting and preventing Photon Number Splitting (PNS) attacks in the BB84 protocol. This method works by introducing decoy qubits alongside the actual information-carrying qubits. These decoy qubits serve as a trap for eavesdroppers and help differentiate between natural noise and intentional attacks.

How Decoy States Detect PNS Attacks:

1. Intensity Variability:
   Each decoy qubit is assigned a randomly chosen intensity level (low, medium, or high). An attacker attempting a PNS attack might selectively measure or manipulate these qubits. By analyzing the error rates across different intensity levels, any abnormality caused by selective manipulation can reveal the attack.
2. Error Rate Analysis:
   During communication, the Sender and Receiver compare the error rates of decoy qubits with expected thresholds. A higher-than-expected error rate in specific intensity levels (e.g., low intensity) suggests the presence of a PNS attack.

Addressing Overlap with Depolarization Noise:

While the decoy state method effectively detects PNS attacks, depolarization noise (a natural environmental disturbance) can introduce false positives. To prevent misinterpretation:

• The simulator implements a baseline error rate threshold for depolarization noise.
• If observed errors exceed this threshold and exhibit a distinct pattern across intensity levels, a PNS attack is flagged.
• Decoy qubits are exclusively used for analysis, ensuring that false positives do not compromise the integrity of the actual key generation process.

By combining decoy states with robust error analysis, the BB84 protocol remains resilient against sophisticated attacks like PNS, even in noisy quantum channels.

The simulator demonstrates these principles through detailed scenarios and outputs. For example:

• Depolarization Noise Scenario:
  Simulates natural disturbances in the quantum channel, showing how random qubit flips affect the key agreement process without external attacks. This scenario highlights the importance of distinguishing environmental noise from eavesdropping attempts.

• PNS Attack Scenario:
  Simulates a Photon Number Splitting (PNS) attack, where an attacker selectively measures multi-photon signals. The simulator shows how such attacks alter error rates across decoy states, enabling detection through advanced error analysis.

• Man-in-the-Middle (MITM) Attack Scenario:
  Simulates an attacker intercepting qubits, measuring them with randomly chosen bases, and resending them to the Receiver. This process introduces mismatched bits, which the simulator detects by comparing the observed error rate against the expected noise thresholds. The scenario emphasizes the importance of basis comparison during key agreement to identify tampered transmissions.

• Security Checks:
  Visualizes the thresholds and comparisons used to distinguish between natural noise, such as depolarization, and malicious interference. This ensures that errors caused by environmental factors are not misinterpreted as attacks, maintaining the integrity of the key generation process.

These examples provide a comprehensive view of how the BB84 protocol handles various noise and attack scenarios. You can explore the practical implementation of these cases in the simulator’s GitHub repository, which includes:

• Step-by-step usage instructions.
• Example outputs and visualizations for all scenarios.
• Theoretical explanations of error analysis and attack detection techniques.

The project is available also on Python Package Index (PyPI). Detailed usage instructions and source code can be found on PyPI too.

By working through these scenarios, users can gain a deeper understanding of how quantum communication systems maintain security against both environmental challenges and adversarial threats.