Abhishek Parakh

Nitin Jha, Prateek Paudel, Abhishek Parakh et al.

Small modular nuclear reactors (SMRs) are redefining the energy generation landscape by enabling the deployment of modular, scalable, and pre-built power units that can be used to build distributed autonomous microgrids for critical infrastructure and burgeoning AI factories. Often, these microgrids are linked together to provide a resilient, decentralized power generation infrastructure. Consequently, the cybersecurity of microgrids is of critical importance. In this work, we propose a quantum augmented network framework for resilient microgrids. We integrate the ideas of secure quantum networking, quantum anonymous notification, and quantum random number generation to strengthen the integrity, confidentiality, and privacy of microgrid networks. To substantiate the possible benefits of using quantum augmented microgrids, we simulate a practical high-impact classical attack: a traffic analysis and priority-action spoofing campaign that can (1) deanonymize the anonymous notification for a high-priority action, (2) force excessive key usage, and (3) induce harmful allow/block operations at the control level. We quantify how these attacks affect information leakage, spoof acceptance, key sufficiency, and operational outcomes such as latency, deadline misses, unserved energy, etc. This quantum augmented microgrid (QuAM) framework lets us evaluate trade-offs between privacy, availability, and the operational cost of mitigation (cover traffic, verification delays, and key-rotation policies), further paving the path for the study of more nuanced attacks that arise due to the use of quantum-classical integrated frameworks.

Nitin Jha, Abhishek Parakh, Mahadevan Subramaniam

The scalability of current quantum networks is limited due to noisy quantum components and high implementation costs, thereby limiting the security advantages that quantum networks provide over their classical counterparts. Quantum Augmented Networks (QuANets) address this by integrating quantum components in classical network infrastructure to improve robustness and end-to-end security. To enable such integration, Quantum Anonymous Notification (QAN) is a method to anonymously inform a receiver of an incoming quantum communication. Therefore, several quantum primitives will serve as core tools, namely, quantum voting, quantum anonymous protocols, quantum secret sharing, etc. However, all current quantum protocols can be compromised in the presence of several common channel noises. In this work, we propose an improved quantum anonymous notification (QAN) protocol that utilizes rotation operations on shared GHZ states to produce an anonymous notification in an n-user quantum-augmented network. We study the behavior of this modified QAN protocol under the dephasing noise model and observe stronger resilience to false notifications than earlier QAN approaches. The QAN framework is also proposed to be integrated with a machine-learning classifier, an enhanced quantum-augmented network. Finally, we discuss how this notification layer integrates with QuANets so that receivers can allow switch-bypass handling of quantum payloads, reducing header-based information leakage and vulnerability to targeted interference at compromised switches.

Prateek Paudel, Nitin Jha, Abhishek Parakh et al.

Classical generative adversarial networks (GANs) have been applied to generate adversarial network traffic capable of attacking intrusion detection systems, but they suffer from shortcomings such as the need for large amounts of high-dimensional datasets, mode collapse, and high computational overhead. In this work, we propose a hybrid quantum-classical GAN (QC-GAN) framework where a variational quantum generator is used to generate synthetic network traffic flows mimicking malicious traffic using latent representations. Instead of sampling classical noise vectors, we encode the latent vector (the hidden features) as a quantum state, which is the basis for claiming more expressive latent representations and reducing computational overhead. A classical discriminator will be trained on real-world datasets (UNSW-NB15) and the proposed QC-GAN-generated fake network flows. In this configuration, the generator aims to minimize the discriminator's ability to distinguish real from fake traffic, while the discriminator aims to maximize its classification accuracy, in an iterative manner. In our attack model, we assume that the attacker is a state actor with access to limited quantum computing power, whereas the discriminator is chosen to be classical, as will likely be the case for most end users and organizations. We test the generated flows using classical intrusion detection system (IDS) models, such as a random forest classifier and a convolutional neural network-based classifier, for their ability to bypass the detection process. This work aims to highlight the possibilities of quantum machine learning as a means of generating advanced attack flows and stress testing classical IDS. Lastly, we further evaluate how hardware-based noise affects these attacks to offer a new perspective on IDS, highlighting the need for a quantum resilient defense system.

Nitin Jha, Abhishek Parakh, Mahadevan Subramaniam

In the past decade, several small-scale quantum key distribution networks have been established. However, the deployment of large-scale quantum networks depends on the development of quantum repeaters, quantum channels, quantum memories, and quantum network protocols. To improve the security of existing networks and adopt currently feasible quantum technologies, the next step is to augment classical networks with quantum devices, properties, and phenomena. To achieve this, we propose a change in the structure of the HTTP protocol such that it can carry both quantum and classical payload. This work lays the foundation for dividing one single network packet into classical and quantum payloads depending on the privacy needs. We implement logistic regression, CNN, LSTM, and BiLSTM models to classify the privacy label for outgoing communications. This enables reduced utilization of quantum resources allowing for a more efficient secure quantum network design. Experimental results using the proposed methods are presented.

Abhishek Parakh

Quantum teleportation allows one to transmit an arbitrary qubit from point A to point B using a pair of (pre-shared) entangled qubits and classical bits of information. The conventional protocol for teleportation uses two bits of classical information and assumes that the sender has access to only one copy of the arbitrary qubit to the sent. Here, we ask whether we can do better than two bits of classical information if the sender has access to multiple copies of the qubit to be teleported. We place no restrictions on the qubit states. Consequently, we propose a modified quantum teleportation protocol that allows Alice to reset the state of the entangled pair to its initial state using only local operations. As a result, the proposed teleportation protocol requires the transmission of only one classical bit with a probability greater than one-half. This has implications for efficient quantum communications and security of quantum cryptographic protocols based on quantum entanglement.

J. Joel vanBrandwijk, Abhishek Parakh

Operations on a pair of entangled qubits are conventionally presented as the application of the tensor product of operations. The tensor product is linearly extended to act synchronously across the entire entangled system. When simulating an entangled system, the conventional approach is possible and practical if both parts of the entangled system exist within the same physical simulator. However, if we wish to simulate an entangled system across a distributed network, sending half of the entangled pair to another simulator on another computer system, the synchronous approach becomes difficult. In the first part of this paper, we demonstrate a method of simulating operations on entangled states in a distributed environment which is equivalent to the conventional approach. The advantage to our approach is that we can simulate distributed quantum systems on physically distributed hardware. Such a system advances the possibilities of demonstrating distributed quantum algorithms for research, teaching, and learning. Further, the security of quantum key exchange depends on successfully detecting the presence of an eavesdropper. In most cases this is done by comparing the errors introduced by an eavesdropper with the channel error rate. In other words, the communicating parties must tolerate some errors without losing a significant amount of key information. In the second part of this paper, we characterize the effects of amplitude damping errors on quantum key distribution protocols and explore allowable tolerances. Through simulations we observe that the effect of these errors, in some cases, is highly dependent on where the eavesdropper is located on the channel. In this paper, we also briefly describe the development of a new quantum simulation library called QooSim.

Matthew Battey, Abhishek Parakh

We present a new quasigroup based block encryption system with and without cipher-block-chaining. We compare its performance against Advanced Encryption Standard-256 (AES256) bit algorithm using the NIST statistical test suite (NIST-STS) that tests for randomness of a sequence. Since it is well known that a good encryption algorithm must destroy any statistical properties of the input sequence and produce an output close to a true random sequence, the NIST-STS suite results provide a good test bench. In almost all tests from the suite the proposed algorithm performs better than AES256.