mlsanityData to 7 Oct 2026

Targeted Attack for Deep Hashing based Retrieval

arXiv 2004.07955 ↗First posted 15 Apr 2020cs.CR cs.CV cs.LGcited by 34

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Abstract (arXiv)

The deep hashing based retrieval method is widely adopted in large-scale image and video retrieval. However, there is little investigation on its security. In this paper, we propose a novel method, dubbed deep hashing targeted attack (DHTA), to study the targeted attack on such retrieval. Specifically, we first formulate the targeted attack as a point-to-set optimization, which minimizes the average distance between the hash code of an adversarial example and those of a set of objects with the target label. Then we design a novel component-voting scheme to obtain an anchor code as the representative of the set of hash codes of objects with the target label, whose optimality guarantee is also theoretically derived. To balance the performance and perceptibility, we propose to minimize the Hamming distance between the hash code of the adversarial example and the anchor code under the ℓ^∞ restriction on the perturbation. Extensive experiments verify that DHTA is effective in attacking both deep hashing based image retrieval and video retrieval.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Apr 2020.

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Citing papers per year: 2021: 7; 2022: 12; 2023: 8; 2024: 3; 2025: 4.

34 papers.

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  1. 2021Advances in adversarial attacks and defenses in computer vision: A surveycited by 127
  2. 2022LAS-AT: Adversarial Training with Learnable Attack Strategycited by 94
  3. 2022Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protectioncited by 80
  4. 2024Inducing High Energy-Latency of Large Vision-Language Models with Verbose Imagescited by 69
  5. 2022A Large-scale Multiple-objective Method for Black-box Attack against Object Detectioncited by 55
  6. 2021Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bitscited by 49
  7. 2023Backdoor Defense via Adaptively Splitting Poisoned Datasetcited by 43
  8. 2022Prior-Guided Adversarial Initialization for Fast Adversarial Trainingcited by 34
  9. 2022BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean Labelcited by 28
  10. 2022Untargeted Backdoor Attack against Object Detectioncited by 28
  11. 2021Learning to Break Deep Perceptual Hashing: The Use Case NeuralHashcited by 25
  12. 2024Adversarial Robustness for Visual Grounding of Multimodal Large Language Modelscited by 23
22 more
  1. 2022Hardly Perceptible Trojan Attack against Neural Networks with Bit Flipscited by 21
  2. 2023One-bit Flip is All You Need: When Bit-flip Attack Meets Model Trainingcited by 14
  3. 2022Versatile Weight Attack via Flipping Limited Bitscited by 13
  4. 2021Backdoor Attack on Hash-based Image Retrieval via Clean-label Data Poisoningcited by 12
  5. 2024DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domaincited by 12
  6. 2022Backdoor Defense via Suppressing Model Shortcutscited by 10
  7. 2021Deep Hash Distillation for Image Retrievalcited by 9
  8. 2021Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashingcited by 8
  9. 2023A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarkingcited by 5
  10. 2023Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrievalcited by 5
  11. 2023GSE: Group-wise Sparse and Explainable Adversarial Attackscited by 5
  12. 2025Protecting Your Video Content: Disrupting Automated Video-based LLM Annotationscited by 5
  13. 2021Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial Networkscited by 3
  14. 2025AutoSSVH: Exploring Automated Frame Sampling for Efficient Self-Supervised Video Hashingcited by 3
  15. 2022CgAT: Center-Guided Adversarial Training for Deep Hashing-Based Retrievalcited by 2
  16. 2023Collapse-Aware Triplet Decoupling for Adversarially Robust Image Retrievalcited by 2
  17. 2022ARIA: Adversarially Robust Image Attribution for Content Provenancecited by 1
  18. 2022Disappeared Command: Spoofing Attack On Automatic Speech Recognition Systems with Sound Maskingcited by 1
  19. 2023Reliable and Efficient Evaluation of Adversarial Robustness for Deep Hashing-Based Retrievalcited by 0
  20. 2023Unsupervised Multi-Criteria Adversarial Detection in Deep Image Retrievalcited by 0
  21. 2025Clean Image May be Dangerous: Data Poisoning Attacks Against Deep Hashingcited by 0
  22. 2025DiffHash: Text-Guided Targeted Attack via Diffusion Models against Deep Hashing Image Retrievalcited by 0