BITS Faculty Publications

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Author: search.filters.author.Tiwari, KamleshSubject: search.filters.subject.EEE

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    PUF-AQKD: a hardware-assisted quantum key distribution protocol for man-in-the-middle attack mitigation pdf
    (IEEE, 2025-05) Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh
    The Quantum Key Distribution (QKD) protocol utilizes quantum mechanics principles for cryptographic key exchange, ensuring absolute secrecy. Current QKD techniques are susceptible to man-in-the-middle (MITM) attacks due to the absence of an inherent mechanism for identity verification within the quantum channel. For authentication, these systems rely on classical or post-quantum cryptography, which diminishes the perfect security advantage provided by QKD. We present a Physical Unclonable Function (PUF)-based authenticated QKD protocol (PUF-AQKD), which avoids the necessity for authenticated classical channels and is useful in mitigating MITM attacks. The fundamental concept of PUF-AQKD is to implement a phase shift in the basis used for polarizing the transmitted qubits. The phase shift is dictated by PUFs, which are anticipated to result in analogous (correlated) responses for devices manufactured under similar conditions but dissimilar responses in different conditions. An adversary lacking a correlated PUF response shared by Alice and Bob would inadvertently increase the Quantum Bit Error Rates (QBER) observed at Bob’s end. We present a mathematical model to assess the efficacy of the proposed PUF-AQKD method and perform simulations utilizing the NetSquid simulator. The mathematical analysis and simulation findings indicate that PUF-AQKD can efficiently identify eavesdroppers, even during incomplete measurements, without the necessity of an authorized classical channel.
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    Quantum key distribution optimization: reducing communication overhead in post-processing steps
    (IEEE, 2025-03) Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh
    Quantum Key Distribution (QKD) is a ground-breaking method in modern cryptography that uses quantum mechanics to establish secure communication channels. Unlike classical cryptographic techniques, QKD provides unconditional security based on quantum principles, such as the no-cloning theorem and the uncertainty principle. However, existing QKD systems often suffer from high overhead in key post-processing, affecting efficiency and scalability, especially in resource-constrained environments such as IoT. This paper addresses these challenges by introducing two key optimizations to enhance the efficiency and security of QKD systems. First, we propose a method using Pseudorandom Number Generators (PRNGs) to determine key bit positions for verification by Alice and Bob, significantly reducing communication over-head. Second, we employ hash-based subsequence comparison to minimize data exchange and leverage the cryptographic strength of hash functions. Results demonstrate that these strategies effectively reduce key post-processing overhead and improve the efficiency of QKD systems in real-world conditions making QKD more practical and scalable for diverse application contexts.
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    Enhanced lightweight quantum key distribution protocol for improved efficiency and security
    (IEEE, 2025) Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh
    Quantum Key Distribution (QKD) provides secure communication by leveraging quantum mechanics, with the BB84 protocol being one of its most widely adopted implementations. However, the classical post-processing steps in BB84, such as sifting, error correction, and key verification, often result in significant communication overhead, limiting its efficiency and scalability. In this work, we propose three key optimizations for BB84: (1) PRNG-based predetermined key bit positioning, which eliminates redundant bit exchanges during sifting, (2) hash-based subsequence comparison, enabling lightweight and efficient key verification, and (3) adaptive basis reconciliation, which minimizes the communication costs associated with basis matching. The proposed optimizations achieve a 50% reduction in communication overhead for large key sizes compared to traditional QKD protocols, as demonstrated through rigorous performance analysis. While the focus of this work is on the BB84 protocol, these optimizations are also directly applicable to a broader class of Discrete-Variable QKD (DV-QKD) protocols, such as six-state, B92, and E91, which share a fundamentally similar post-processing structure. This generality highlights the modularity and adaptability of the proposed methods across diverse QKD implementations. The proposed optimizations enhance post-processing efficiency and scalability, enabling practical deployment in bandwidth-limited environments like IoT networks, secure financial systems, and defense communications, thereby supporting broader adoption of quantum communication systems.
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    Scanned to Digital Face Images Matching With Siamese Network
    (IEEE, 2018) Gupta, Karunesh Kumar; Tiwari, Kamlesh
    Often in law enforcement and forensic application it is needed to match scanned facial image with a digital face image. This is because in many scenario, non-digital face images are obtained from the crime scene, news articles etc. that are needed to be identified. Non-digital face images are first scanned and then enhanced to match against the database. Challenges arrives because of poor quality of non-digital image, artifacts introduced in scanning process and high saturation etc. therefore matching becomes difficult. The methods used in literature involve specialized hand crafted pre-processing. In our paper, we propose an automated way of matching by using Siamese networks. The proposed method have been able to achieve an EER of 2.346% that is better than the current state-of-the-art.
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    Finger Knuckleprint Based Personal Authentication Using Siamese Network
    (IEEE, 2019) Gupta, Karunesh Kumar; Tiwari, Kamlesh
    Online security is a major concern today and incidents of forged identity cards and hacked passwords are common throughout the world. Therefore, there is a need for robust personal authentication mechanisms using biometrics for various access control systems. Popular biometric traits such as fingerprint have problems in rural areas, due to wearing down of fingerprint pattern from hard manual labor. This is also a problem for people who work with calcium oxide, because it is known to dissolve the upper layers of the skin due to its basicity. This paper proposes a finger-knuckle-print (FKP) based human authentication system that is immune to the above problems because the finger dorsal region is not exposed to labor surfaces. The paper uses pre-processed knuckle ROI images to train a Siamese convolutional neural network model. The proposed algorithm has been validated using open-source PolyU finger-knuckle-print database from 165 individuals, and has achieved 99.24% CRR, 0.78% EER that is better than the state-of-the-art.