Quantum computing has emerged as a transformative technological advancement with the potential to challenge the foundations of classical cryptography. Traditional cryptographic algorithms, such as RSA, rely heavily on the computational hardness of problems like integer factorization—a problem quantum algorithm like Shor's can theoretically solve efficiently. This research investigates the practical capabilities and performance limitations of three prominent quantum simulation frameworks: Qiskit, Cirq, and QuTiP. The study aims to analyze and compare their efficiency in simulating the decryption process for encrypted data of varying bit lengths—specifically 8 -bit, 16 -bit, 32 -bit, 64 -bit, 128 -bit, and 512 -bit keys. By simulating classical decryption schemes through quantum circuits, we assess the computational resources, execution time, and overall performance of each platform. This benchmarking helps to highlight how effectively these simulators can model cryptographic tasks and where they currently fall short in terms of scalability and execution time. The results offer valuable insights into the practicality of deploying quantum computing for real-world cryptographic operations and outline the current limitations imposed by simulation-based approaches, especially as key sizes grow in complexity. Ultimately, this research contributes to a deeper understanding of how existing quantum tools perform under cryptographic workloads and what improvements are necessary to make quantum-assisted cryptanalysis viable at scale.
Quantum computing has emerged as a transformative technological advancement with the potential to challenge the foundations of classical cryptography. Traditional cryptographic algorithms, such as RSA, rely heavily on the computational hardness of problems like integer factorization—a problem quantum algorithm like Shor's can theoretically solve efficiently. This research investigates the practical capabilities and performance limitations of three prominent quantum simulation frameworks: Qiskit, Cirq, and QuTiP. The study aims to analyze and compare their efficiency in simulating the decryption process for encrypted data of varying bit lengths—specifically 8 -bit, 16 -bit, 32 -bit, 64 -bit, 128 -bit, and 512 -bit keys. By simulating classical decryption schemes through quantum circuits, we assess the computational resources, execution time, and overall performance of each platform. This benchmarking helps to highlight how effectively these simulators can model cryptographic tasks and where they currently fall short in terms of scalability and execution time. The results offer valuable insights into the practicality of deploying quantum computing for real-world cryptographic operations and outline the current limitations imposed by simulation-based approaches, especially as key sizes grow in complexity. Ultimately, this research contributes to a deeper understanding of how existing quantum tools perform under cryptographic workloads and what improvements are necessary to make quantum-assisted cryptanalysis viable at scale.
The rapid advancement of quantum computing threatens to undermine the security foundations of modern cryptographic systems, particularly those based on integer factorization and discrete logarithm problems. Algorithms such as Shor’s and Grover’s promise exponential or quadratic speedups, rendering RSA, ECC, and certain symmetric schemes vulnerable within the next decade. This paper presents a simulated evaluation of classical cryptographic algorithms against quantum attacks, followed by a performance assessment of post-quantum cryptographic (PQC) schemes—specifically lattice-based, hash-based, and code-based algorithms. A testing framework was developed using a quantum simulator (Qiskit) and a classical benchmarking environment to model potential attack timelines and measure computational efficiency. Results demonstrate that RSA-2048 can be theoretically broken within 8 hours on a 4000-qubit fault-tolerant quantum processor, while ECC-P256 succumbs in less than 4 hours. In contrast, lattice-based schemes such as CRYSTALS-Kyber resisted quantum simulation attacks, maintaining equivalent classical security levels with only a 27% performance overhead. The study also analyzes the trade-offs between key size, encryption/decryption speed, and resistance to quantum attacks. Our findings emphasize the urgent need for migration to NIST-recommended PQC algorithms and provide a decision-support matrix for selecting suitable replacements in government and enterprise systems.
The rapid advancement of quantum computing presents a significant challenge to classical cryptographic systems that underpin modern digital security infrastructures. In particular, RSA-2048 encryption, widely deployed in banking and financial institutions for secure transactions, relies on the computational hardness of integer factorization. However, the emergence of quantum algorithms—especially Shor’s algorithm—poses a fundamental threat to RSA security by enabling polynomial-time factorization of large integers on sufficiently powerful quantum computers. This case study investigates the vulnerability of RSA-2048 within a banking environment, analyzing the mathematical foundations of the threat, potential timelines for quantum feasibility, and associated cybersecurity risks. The study further examines the implications for financial data protection, digital signatures, and secure communication channels. In response to these emerging risks, the paper explores post-quantum cryptographic alternatives, including lattice-based, hash-based, and code-based schemes, and evaluates their suitability for banking applications. The findings emphasize the urgency of transitioning toward quantum-resistant cryptographic frameworks and propose strategic recommendations for proactive cryptographic migration to ensure long-term data confidentiality and system resilience.
The growing threat of quantum computing to classical cryptographic systems such as RSA and ECC has led to an urgent need for post-quantum cryptographic (PQC) research and implementation. The base paper, “Quantum Computing in Cryptography”, identified a major research gap - the lack of practical implementation of post-quantum algorithms, emphasizing that most existing works remain at a theoretical level. Addressing this gap, we develop and execute a practical benchmarking framework that compares classical RSA and simulated post-quantum cryptographic algorithms. The implementation integrates automatic setup, execution, and visualization of key generation, encryption, and decryption operations for both classical and PQC schemes. Experimental results demonstrate that while RSA achieves faster computational performance, it becomes vulnerable to quantum computational attacks. Conversely, post-quantum algorithms, though more computationally demanding, exhibit strong resistance against such attacks. The performance analysis highlights the trade-off between speed and quantum resilience, confirming the practical viability of PQC for future-proof cryptographic systems. This work effectively bridges the theoretical–practical divide noted in the base paper by providing a concrete, implementable model for evaluating post-quantum cryptography under realistic computational conditions.
The advent of quantum computing poses a fundamental threat to classical cryptographic systems, particularly RSA encryption, which relies on the computational limit of prime factorization. This paper presents a comparative analysis of four integer factorization approaches-a selfcurated brute-force classical implementation, optimized Trial Division, Pollard's Rho algorithm, and Shor's algorithmevaluated across a dataset of increasing semiprime inputs representative of scaled-down RSA encryption keys. Through Python-based implementations and simulations, we empirically measure and plot runtime complexity for classical methods while modeling theoretical runtimes for Shor's algorithm, given hardware limitations. Our findings reveal the exponential scaling limitations of classical algorithms, and contrast them with the polynomial-time behavior of Shor's algorithm. Despite being simulated, Shor's consistently flatter runtime trendline demonstrated its theoretical superiority and the critical urgency of post-quantum cryptography. This study not only visualizes the performance divide between classical and quantum paradigms but also underscores the transformational potential of quantum computing in modern cryptanalysis.
Quantum computing can be regarded as a disruptive enabling technology that can pose a threat to traditional cryptography as it invented new approaches to encrypt data. This paper will compare the level of security that accompanies quantum algorithms as well as the level of efficiency. Specifically, we examine the impact of efficient quantum computing on traditional cryptography and propose techniques against quantum invasions. Four quantum algorithms are analyzed for their efficiency and security benefits in the post-quantum era: Grover’s Algorithm, Shor’s Algorithm, The Quantum Key Distribution (QKD), Lattice-based cryptography. The results reveal that Grover’s algorithm improves search time complexity from O(n) to O(√n), which is advantageous over large data sets. As it will be clear shortly, Shor’s algorithm challenges RSA encryption because it outperforms classical algorithms in factoring large integers. QKD presents secure key exchange protocols that cannot be breached notwithstanding the attempts made using quantum computing. Lattice-based schemes are quantum-resistant alternatives based on the security of certain hard mathematical problems. Based on our experimental results, computational efficiency can be improved, but new cryptographic systems will have to be developed for the mitigation of quantum-related vulnerabilities. This research shows the importance of quantum-resistant cryptographic techniques to ensure data security in the emerging quantum computing era.
The advent of quantum computing poses a significant challenge to conventional cryptographic methods such as RSA, Elliptic Curve Cryptography (ECC), and Diffie-Hellman key exchange. Quantum algorithms, particularly Shor’s algorithm, have the potential to break these encryption techniques, making it essential to develop cryptographic approaches that can withstand quantum threats. Post-quantum cryptography (PQC) has emerged as a crucial area of research, aiming to establish cryptographic mechanisms that remain secure even in the presence of quantum adversaries. This study presents a detailed comparative analysis of five primary categories of quantum-resistant cryptographic algorithms: lattice-based, code-based, hash-based, multivariate polynomial, and isogeny-based encryption schemes. Each of these approaches offers distinct advantages and challenges in terms of security, efficiency, and implementation feasibility. Among them, lattice-based cryptography has gained significant attention due to its robust security properties and computational efficiency, making it a strong candidate for standardization. Conversely, code-based cryptography provides high security but is hindered by its large key sizes, affecting its practical deployment. The research includes a real-time performance assessment of selected PQC algorithms, analyzing key factors such as encryption speed, key size, and computational demands. Furthermore, the study examines the challenges associated with transitioning from classical encryption standards to quantum-resistant frameworks, including compatibility constraints, computational overhead, and the necessity for global standardization. Potential mitigation approaches, such as hybrid cryptographic techniques that integrate both classical and post-quantum encryption models, are also explored. Our findings emphasize that while quantum-resistant cryptography is still evolving, early adoption of PQC frameworks is essential for safeguarding future communication networks. This paper provides valuable insights for researchers, cybersecurity professionals, and policymakers on strategic measures to implement quantum-secure encryption systems effectively.