Trojan Taxonomy in Quantum Computing

• URL: http://arxiv.org/abs/2309.10981v1
• Date: Wed, 20 Sep 2023 00:42:21 GMT
• Title: Trojan Taxonomy in Quantum Computing
• Authors: Subrata Das, Swaroop Ghosh,
• Abstract summary: Quantum computing introduces unfamiliar security vulnerabilities demanding customized threat models. This paper develops the first structured taxonomy of Trojans tailored to quantum information systems. A categorization of quantum Trojan types and payloads is outlined ranging from reliability degradation, functionality corruption, backdoors, and denial-of-service.
• Score: 2.348041867134616
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Quantum computing introduces unfamiliar security vulnerabilities demanding customized threat models. Hardware and software Trojans pose serious concerns needing rethinking from classical paradigms. This paper develops the first structured taxonomy of Trojans tailored to quantum information systems. We enumerate potential attack vectors across the quantum stack from hardware to software layers. A categorization of quantum Trojan types and payloads is outlined ranging from reliability degradation, functionality corruption, backdoors, and denial-of-service. Adversarial motivations behind quantum Trojans are analyzed. By consolidating diverse threats into a unified perspective, this quantum Trojan taxonomy provides insights guiding threat modeling, risk analysis, detection mechanisms, and security best practices customized for this novel computing paradigm.

Related papers

• Revocable Encryption, Programs, and More: The Case of Multi-Copy Security [48.53070281993869]
  We show the feasibility of revocable primitives, such as revocable encryption and revocable programs. This suggests that the stronger notion of multi-copy security is within reach in unclonable cryptography.
  arXiv  Detail & Related papers  (2024-10-17T02:37:40Z)
• A Security Assessment tool for Quantum Threat Analysis [34.94301200620856]
  The rapid advancement of quantum computing poses a significant threat to many current security algorithms used for secure communication, digital authentication, and information encryption. A sufficiently powerful quantum computer could potentially exploit vulnerabilities in these algorithms, rendering data in insecure transit. This work developed a quantum assessment tool for organizations, providing tailored recommendations for transitioning their security protocols into a post-quantum world.
  arXiv  Detail & Related papers  (2024-07-18T13:58:34Z)
• A Quantum Automatic Tool for Finding Impossible Differentials [12.997422492640766]
  We propose two quantum automatic tools for searching impossible differentials. The proposed quantum algorithms exploit the idea of miss-in-the-middle and the properties of truncated differentials.
  arXiv  Detail & Related papers  (2024-07-14T03:00:24Z)
• Evaluation Framework for Quantum Security Risk Assessment: A Comprehensive Study for Quantum-Safe Migration [0.03749861135832072]
  The rise of large-scale quantum computing poses a significant threat to traditional cryptographic security measures. Quantum attacks undermine current asymmetric cryptographic algorithms, rendering them ineffective. This study explores the challenges of migrating to quantum-safe cryptographic states.
  arXiv  Detail & Related papers  (2024-04-12T04:18:58Z)
• TrojanNet: Detecting Trojans in Quantum Circuits using Machine Learning [5.444459446244819]
  TrojanNet is a novel approach to enhance the security of quantum circuits by detecting and classifying Trojan-inserted circuits. We generate 12 diverse datasets by introducing variations in Trojan gate types, the number of gates, insertion locations, and compilers. Experimental results showcase an average accuracy of 98.80% and an average F1-score of 98.53% in effectively detecting and classifying Trojan-inserted QAOA circuits.
  arXiv  Detail & Related papers  (2023-06-29T05:56:05Z)
• Evil from Within: Machine Learning Backdoors through Hardware Trojans [72.99519529521919]
  Backdoors pose a serious threat to machine learning, as they can compromise the integrity of security-critical systems, such as self-driving cars. We introduce a backdoor attack that completely resides within a common hardware accelerator for machine learning. We demonstrate the practical feasibility of our attack by implanting our hardware trojan into the Xilinx Vitis AI DPU.
  arXiv  Detail & Related papers  (2023-04-17T16:24:48Z)
• Cybersecurity for Quantum Computing [3.867124349164785]
  Quantum computing companies, institutions and research groups may become targets of nation-state actors, cybercriminals and hacktivists. This paper discusses the status quo of quantum computing technologies and the quantum threat associated with it. We propose recommendations on how to proactively reduce the cyberattack surface through threat intelligence and by ensuring security by design of quantum software and hardware components.
  arXiv  Detail & Related papers  (2021-10-27T18:41:30Z)
• Entanglement transfer, accumulation and retrieval via quantum-walk-based qubit-qudit dynamics [50.591267188664666]
  Generation and control of quantum correlations in high-dimensional systems is a major challenge in the present landscape of quantum technologies. We propose a protocol that is able to attain entangled states of $d$-dimensional systems through a quantum-walk-based it transfer & accumulate mechanism. In particular, we illustrate a possible photonic implementation where the information is encoded in the orbital angular momentum and polarization degrees of freedom of single photons.
  arXiv  Detail & Related papers  (2020-10-14T14:33:34Z)
• An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks [59.42357806777537]
  trojan attack aims to attack deployed deep neural networks (DNNs) relying on hidden trigger patterns inserted by hackers. We propose a training-free attack approach which is different from previous work, in which trojaned behaviors are injected by retraining model on a poisoned dataset. The proposed TrojanNet has several nice properties including (1) it activates by tiny trigger patterns and keeps silent for other signals, (2) it is model-agnostic and could be injected into most DNNs, dramatically expanding its attack scenarios, and (3) the training-free mechanism saves massive training efforts compared to conventional trojan attack methods.
  arXiv  Detail & Related papers  (2020-06-15T04:58:28Z)
• Scalable Backdoor Detection in Neural Networks [61.39635364047679]
  Deep learning models are vulnerable to Trojan attacks, where an attacker can install a backdoor during training time to make the resultant model misidentify samples contaminated with a small trigger patch. We propose a novel trigger reverse-engineering based approach whose computational complexity does not scale with the number of labels, and is based on a measure that is both interpretable and universal across different network and patch types. In experiments, we observe that our method achieves a perfect score in separating Trojaned models from pure models, which is an improvement over the current state-of-the art method.
  arXiv  Detail & Related papers  (2020-06-10T04:12:53Z)
• Backflash Light as a Security Vulnerability in Quantum Key Distribution Systems [77.34726150561087]
  We review the security vulnerabilities of quantum key distribution (QKD) systems. We mainly focus on a particular effect known as backflash light, which can be a source of eavesdropping attacks.
  arXiv  Detail & Related papers  (2020-03-23T18:23:12Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.