Quantum Random Number Generator: Difference between revisions
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QRNGs use random properties of quantum physics to generate a true source of entropy. This improves the quality of seed for key generation. Since the entropy sources are derived from fundamental models, all the properties and behaviors are understandable and provably secure. | QRNGs use random properties of quantum physics to generate a true source of entropy. This improves the quality of seed for key generation. Since the entropy sources are derived from fundamental models, all the properties and behaviors are understandable and provably secure. | ||
[[File:General principle of QRNG.png|thumb|300px| General principle of QRNG]] | |||
== Setup == | == Setup == | ||
Revision as of 02:34, 23 April 2022
Team Members
Wang Yang A0228753X
Xiao Yucan A0236278W
Zhang Munan A0236273E
Idea
- We live in an increasingly connected world, where a superior source of entropy is the key to data security. The effectiveness of any cryptographic system is determined by the strength of the keys it used. In turn, the strength of the key is determined by the degree of randomness used in its generation. And Quantum Random Number Generators (QRNGs) leverage the random properties of quantum physics to generate a true source of entropy, improving the quality of seed content for key generation.
- BENEFITS OF HAVING A QUANTUM RANDOM NUMBER GENERATOR:
- The source of randomness is unpredictable and controlled by quantum process.
- The entropy source tends to produce true random output.
- Live/ real-time monitoring of entropy source is possible and highly effective as well.
- All attacks on the entropy source are detectable.
- The above factors indicate that our QRNG is provably secure.
- APPLICATIONS OF QUANTUM RANDOM NUMBER GENERATOR:
- Securing data at rest in data centres
- Securing any kind of sensitive data
- Securing data in the cloud
- One-time pad for authentication in banking and other transactions
- Gaming applications and lottery
- Block-chain network
- Numerical simulations, statistical research
- IoT devices
- E-commerce and banking applications
- Cryptographic applications
- Telecom and 5G
- QUANTUM-ENABLED SECURITY AS A ROOT OF TRUST
In today’s Y2Q world, developers have to rely on the source of entropy as quantum-enabled security keys are set to become the new normal. Organisations should, therefore, implement QRNG to protect their customers’ data.
Principles
In cybersecurity, a perfect random number is the root of trust. A QRNG does not rely on mathematical algorithms but on laws of quantum physics to ‘naturally’ generate random numbers.
A QRNG can produce unpredictable outcomes in a robust and well-controlled way. It includes the power of complex deep-tech technologies such as semiconductors, optoelectronics, high precision electronics, and quantum physics that work together to create the highest level of randomness possible.
QRNGs use random properties of quantum physics to generate a true source of entropy. This improves the quality of seed for key generation. Since the entropy sources are derived from fundamental models, all the properties and behaviors are understandable and provably secure.
Setup
Gallery
- 26 February 2022:
- 5 March 2022:
- 12 March 2022:
* Fabrication may not be possible with current resources. * Instead, we will focus on characterizing existing APDs or photodiodes that are available. * Seems that there exist some possibly faulty or broken setups of APDs, we may look to troubleshoot them. * Example of APD characterization done by FYP student from CQT[1] & masters thesis on the same topic [2]. * From the PDF, it seems that the avalanche "pulse" can be measured directly. This begs the question: how does the shape of the pulse correlate to the photon counts? * Problem posed by Christain: How are single photons defined/characterized?
- 19 March 2022:
* got a working signal from the "homemade" APD! * Next is to lower the light intensity of the LED and measure the signal from the APD as a function of LED power.
- 26 March 2022:
* attempted to connect GDS 1072B to laptop. tried the driver, but the oscilloscope could not be detected. * will look into the source to debug the driver. * able to retrieve the data via thumb drive. * Signal from homemade APD is a negative logic signal. It turns on when a photon causes an electron avalanche. (this is not what we need for the characterization) * Next, will be using the APD testing kit to test the raw APD.
- 2 April 2022:
* Could not get the APD kit to work. Suspect its because of an open circuit on the board (unsure if this was intended or not). * the high voltage DC-DC converter seems to be functioning properly and responsive to control voltage.
- 9 April 2022:
* traced and compared schematic to the actual board. slight discrepancies found. * However, now the plan is to use the DC-DC converter directly to supply high voltage to the APD and measure the response to light. * The APD is shown to respond to light as expected. * Next step is to figure out a way to supply a controlled amount of light and correlate this with the response from APD. * Also, there is a need to understand the response from APD.
- 16 April 2022:
* recreated APD schematic from data sheet. * The bare APD is shown to respond to light as expected. * May have burnt out APD from the previous step due to lack of resistor.
- 23 April 2022:
* Finally able to retrieve data directly from GDS 1072B ( GDS1072B ) * Installation of the driver is described for others. * found an opensource python interface for the oscilloscope. * Next step is to allow for continuous data collection.
Background reading
[1]Quantum random number generators, Miguel Herrero-Collantes and Juan Carlos Garcia-Escartin, Rev. Mod. Phys. 89, 015004.