Volume 05 Issue 06-2025
36
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
05
ISSUE
06
Pages:
36-40
OCLC
–
1368736135
A
BSTRACT
Quantum-dot Cellular Automata (QCA) has emerged as a promising nanotechnology for ultra-low-power
and high-speed cryptographic circuit design. However, its vulnerability to power analysis attacks (PAA)
remains a critical concern. This paper reviews existing QCA-based cryptographic implementations,
including the Serpent cipher, A5/1 stream cipher, and True Random Number Generators (TRNGs),
analyzing their resistance to side-channel attacks. We evaluate power consumption models, security trade-
offs, and novel design methodologies for secure nanocommunication.
K
EYWORDS
Power analysis attack, Random number generation, pseudo-random number generation, entropy,
cryptography, simulations.
I
NTRODUCTION
As digital systems continue to scale down to the
nanoscale level, the demand for secure and energy-
efficient cryptographic hardware has intensified.
Traditional CMOS (Complementary Metal-Oxide
Semiconductor)
technology,
despite
its
widespread adoption, faces critical limitations in
terms of power leakage, heat dissipation, and
scalability. In response to these challenges,
Journal
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Copyright:
Original
content from this work
may be used under the
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commons
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4.0 licence.
Research Article
Power Analysis Attacks And Cryptographic Circuit Design In
Quantum-Dot Technology
Submission Date:
May 12,
2025,
Accepted Date:
May 30, 2025,
Published Date:
June 19, 2025
Crossref doi:
https://doi.org/10.37547/ijasr-05-06-05
Nuriddin Safoev
Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent,
Uzbekistan
Sirojiddin Salimov
Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent,
Uzbekistan
Volume 05 Issue 06-2025
37
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
05
ISSUE
06
Pages:
36-40
OCLC
–
1368736135
Quantum-dot Cellular Automata (QCA) has
emerged
as
a
promising
post-CMOS
nanotechnology, offering near-zero static power
dissipation, ultra-dense circuitry, and high clocking
frequencies. These characteristics make QCA
particularly
attractive
for
implementing
cryptographic systems in secure nano- and
quantum communication environments [1].
However, the benefits of QCA do not inherently
guarantee immunity against all forms of cyber
threats. Among the most insidious are side-channel
attacks, especially Power Analysis Attacks (PAA),
which exploit variations in power consumption to
deduce secret cryptographic keys. While
conventional CMOS-based systems have been
extensively studied under these attack models, the
susceptibility of QCA circuits remains an
underexplored but pressing concern.
This paper investigates the vulnerability of various
QCA-based cryptographic implementations to
power analysis attacks. We place a particular
emphasis on the Serpent block cipher, known for
its robust mathematical structure and 32-round
security-enhanced architecture, as well as the A5/1
stream cipher and True Random Number
Generators (TRNGs) designed using QCA logic. The
study
further
explores
reversible
logic
implementations, such as authentication circuits
based on Fredkin gates, highlighting their impact
on reducing power signatures and enhancing fault
tolerance [2].
By analyzing power models, logic designs, and
architectural trade-offs, this work aims to provide
a comprehensive understanding of the security
landscape for QCA-based cryptographic circuits.
Our goal is to assess whether QCA technology can
truly serve as a secure foundation for next-
generation cryptographic systems, or whether
novel countermeasures must be integrated to
withstand the evolving threats of side-channel
attacks.
2.
Power
Analysis
Attacks
on
QCA
Cryptographic Circuits
2.1 Upper Bound Power Model in QCA
To evaluate the vulnerability of QCA-based circuits
against power analysis attacks (PAA), [3] proposed
an upper bound power model. This model
estimates the worst-case dynamic power
consumption in QCA circuits, accounting for
polarization switching activities that occur during
signal propagation. In their investigation, a 4-bit ×
4-bit sub-module of the Serpent cipher was
implemented in QCA to observe how even minimal
power variations can be exploited. The results
revealed that correlation-based attacks (CPA) were
capable of identifying the correct cryptographic
key, indicating that the intrinsic low-power
advantage of QCA does not inherently guarantee
resistance to side-channel threats.
2.2 Serpent Cipher in QCA
The Serpent cipher, characterized by its 32-round
substitution-permutation
network
(SPN)
architecture, offers enhanced cryptographic
strength compared to AES (Rijndael), particularly
due to its increased round count and conservative
design principles. Despite its theoretical
robustness, QCA-based implementations of
Volume 05 Issue 06-2025
38
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
05
ISSUE
06
Pages:
36-40
OCLC
–
1368736135
Serpent remain susceptible to PAAs, as attackers
can exploit the key-dependent internal operations
of the cipher [4]. This vulnerability allows for the
sequential recovery of subkeys by analyzing power
consumption patterns during encryption.
In a study conducted by authors[5], a detailed QCA-
based realization of the Serpent cipher was
developed, featuring:
A 128-bit input block size and full 32-round SPN
architecture.
Key mixing operations implemented using AND
and NOT gate logic, along with linear
transformations using AND/OR gates.
A highly compact 16:1 multiplexer-based S-Box
design, composed of approximately 4,800 QCA
cells, requiring 10 clock cycles to produce each S-
Box output.
These design characteristics demonstrate the
feasibility of implementing complex ciphers in
QCA, but also underscore the pressing need for
side-channel
countermeasures,
given
that
attackers can still leverage subtle power
differences to mount effective PAAs.
3. QCA-Based Cryptographic Architectures
3.1 Encryption and Decryption in QCA
Authors [9] proposed a Quantum-dot Cellular
Automata
(QCA)-based
encoder-decoder
architecture
tailored
for
secure
nanocommunication. The core encryption and
decryption operations follow a bitwise XOR
mechanism:
𝐵
𝑖
= 𝐸
𝐾
𝑖
(𝐴
𝑖
) = 𝐴
𝑖
+ 𝐾
𝑖
𝑚𝑜𝑑 2
𝐴
𝑖
= 𝐷
𝐾
𝑖
(𝐵
𝑖
) = 𝐵
𝑖
+ 𝐾
𝑖
𝑚𝑜𝑑 2
Here, A_i denotes the plaintext bit, K_i the key bit,
and B_i the corresponding ciphertext bit. The
addition modulo 2 effectively implements a logical
XOR operation.
The proposed QCA circuit occupies an area of
approximately 36,000 nm², comprising 42 cells,
including three majority gates and two inverters.
Notably, the design is scalable and can
accommodate arbitrary key lengths, making it
well-suited
for
nano-level
cryptographic
applications.
3.2 A5/1 Stream Cipher Implementation
Authors[6] realized the A5/1 stream cipher
—
originally used in GSM communication
—
within the
QCA framework. The implementation leverages
majority gates to control the behavior of shift
registers, which form the backbone of the ciphering
mechanism. A dedicated memory block is designed
to retain data when the ENABLE signal is high and
to update the stored values when the signal is low.
This functional behavior highlights the potential of
QCA technology in supporting real-time stream
cipher architectures, with efficient control and
minimal area overhead.
3.3 Reversible Authentication Circuits
In [7], Fredkin gates
—
well-known reversible logic
primitives
—
were employed to develop an energy-
efficient reversible authentication circuit. The
design achieves a low quantum cost of 0.041 and
Volume 05 Issue 06-2025
39
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
05
ISSUE
06
Pages:
36-40
OCLC
–
1368736135
demonstrates reduced power dissipation by
eliminating information loss. Additionally, the
circuit's robustness against thermal noise was
evaluated using Hamming distance analysis (see
Fig. 28), underscoring its suitability for low-power,
thermally-stable
QCA
implementations
in
authentication protocols.
4. Secure Nanocommunication and TRNGs
4.1 Cryptographic Nano-Routers
A secure nanocommunication architecture was
introduced in [8], incorporating XOR-based
encoder and decoder circuits for data encryption
and decryption. The communication flow is
managed by a QCA-based nano-router utilizing a
4:1 multiplexer (MUX) and a 1:4 demultiplexer
(DEMUX) to securely route encrypted data
between nodes. This design highlights the potential
of QCA for integrating compact, secure routing
mechanisms within nanoscale networks, ensuring
confidentiality and controlled data flow at the
physical layer. Ref. [8] proposed a nano-
communication architecture with:
Encoder/Decoder: XOR-based circuits.
Nano-router: 4:1 MUX and 1:4 DEMUX for
encrypted data routing.
4.2 True Random Number Generation
In [9], a QCA-based True Random Number
Generator (TRNG) was proposed, leveraging a self-
starved feedback-based SRAM cell to produce non-
deterministic output bits. A floating clock
mechanism is introduced to enhance entropy and
ensure higher randomness levels in the generated
bitstream. Such TRNGs play a crucial role in
cryptographic systems, particularly for generating
unpredictable keys, initialization vectors, and
nonces, which are foundational to the overall
security of encryption schemes in QCA-based
systems.
5. Fault-Tolerant Designs
A fault-tolerant D-type flip-flop design was
presented in [10] for use in QCA-based shift
registers. The architecture is scalable to n-bit
configurations, offering enhanced reliability for
sequential logic applications. Power dissipation
analysis conducted using the QCAPro simulation
tool demonstrated that the proposed design
achieves lower energy consumption compared to
conventional implementations. This advancement
supports the development of robust and energy-
efficient QCA circuits for cryptographic and
communication systems where fault tolerance is
critical.
C
ONCLUSIONS
Quantum-dot Cellular Automata (QCA) presents a
promising paradigm for energy-efficient and high-
speed cryptographic circuit design, offering
significant benefits over traditional CMOS
technologies. However, as this study has
highlighted, the threat of power analysis attacks
(PAA) persists even in QCA-based systems due to
exploitable
power
consumption
patterns.
Addressing these vulnerabilities is essential for the
secure deployment of QCA in practical applications.
Volume 05 Issue 06-2025
40
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
05
ISSUE
06
Pages:
36-40
OCLC
–
1368736135
Future research should prioritize the development
of refined power models that enhance leakage
resilience, the design of robust and correlation-
resistant S-Box architectures, and the creation of
scalable True Random Number Generators
(TRNGs) to ensure high entropy in cryptographic
key generation. While QCA-based cryptographic
architectures hold substantial potential to
transform
secure
nanocommunication,
overcoming side-channel attack vectors remains a
critical research challenge. Continued innovation
in secure QCA design will be vital to realizing its full
potential in next-generation cryptographic
systems.
R
EFERENCES
1.
Chan, W. K. (2009). Random Number
Generation in Simulation.
2.
Gutterman, Z., Pinkas, B., & Reinman, T. (2006).
Analysis of the Linux Random Number
Generator.
3.
Haahr, M. (2011). Introduction to Randomness
and Random Numbers.
4.
Marsaglia, G. (2005). Random Number
Generators.
5.
Schneier, B. (2007). Dual_EC_DRBG: A Case
Study in Backdoors.
6.
Sunar, B., Martin, W., & Stinson, D. (2006). A
Provably Secure True Random Number
Generator.
7.
Eastlake, D., Schiller, J., & Crocker, S. (2005).
Randomness Requirements for Security. RFC
4086. https://www.rfc-editor.org/rfc/rfc4086
8.
Gutterman, Z., Pinkas, B., & Reinman, T. (2006).
Analysis of the Linux Random Number
Generator. IEEE Symposium on Security and
Privacy. https://doi.org/10.1109/SP.2006.26
9.
Dorrendorf, L., Gutterman, Z., & Pinkas, B.
(2007). Cryptanalysis of the Random Number
Generator of the Windows Operating System.
ACM
CCS.
https://doi.org/10.1145/1315245.1315274
10.
Lacharme, P. (2012). Security flaws in Linux's
/dev/random.
https://eprint.iacr.org/2012/251
11.
Kelsey, J., Schneier, B., Ferguson, N. (1999).
Yarrow-160: Notes on the Design and Analysis
of the Yarrow Cryptographic Pseudorandom
Number
Generator.
https://www.schneier.com/paper-yarrow.pdf
12.
Dodis, Y., et al. (2013). Security Analysis of
Pseudorandom Number Generators with Input:
/dev/random is not Robust. ACM CCS.
https://doi.org/10.1145/2508859.2516661
13.
National Institute of Standards and Technology.
(2012). A Statistical Test Suite for Random and
Pseudorandom Number Generators for
Cryptographic Applications. NIST SP 800-22
Rev. 1a. https://doi.org/10.6028/NIST.SP.800-
22r1a
14.
Müller, T. (2013). Security of the OpenSSL
PRNG. International Journal of Information
Security,
12(4),
251
–
265.
https://doi.org/10.1007/s10207-013-0213-7
