Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Genetic Material01:20

Genetic Material

2.5K
Within the human body, a complex and detailed system of trillions of cells works in unison to sustain life. Each cell houses a nucleus, which contains 46 chromosomes divided into 23 pairs. Chromosomes are highly coiled structures made of the genetic material DNA. These chromosomes are essential carriers of genetic information, with half inherited from the mother through her egg and the other half from the father's sperm, combining to create the unique genetic makeup of an individual.
2.5K
Genomics02:02

Genomics

37.7K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
37.7K
DC Generator01:19

DC Generator

1.2K
An alternator converts mechanical energy into electrical energy that varies sinusoidally, resulting in AC current. Meanwhile, a DC generator converts mechanical energy into electrical energy, which are DC pulses with the same polarity. The construction of a DC generator is similar to that of an alternator, except that the pair of slip rings is replaced by a single split ring, also called a commutator. The commutator functions like a periodic rotary switch; it changes the contacts with the...
1.2K
The Retinoblastoma Gene01:20

The Retinoblastoma Gene

4.2K
Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
The first-ever tumor suppressor gene called Rb was identified in retinoblastoma - a rare eye tumor in children. In inherited forms of the disease, a child inherits one defective copy of the Rb gene, which predisposes them to retinoblastoma. However,...
4.2K
Upsampling01:22

Upsampling

337
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
337
Stereotype Content Model02:16

Stereotype Content Model

14.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Genetic variants of p21 and p27 and hepatocellular cancer risk in a Chinese Han population: a case-control study.

International journal of cancer·2012
Same author

Inhibition of TGF-β/Smad signaling by BAMBI blocks differentiation of human mesenchymal stem cells to carcinoma-associated fibroblasts and abolishes their protumor effects.

Stem cells (Dayton, Ohio)·2012
Same author

MAIGO2 is involved in abscisic acid-mediated response to abiotic stresses and Golgi-to-ER retrograde transport.

Physiologia plantarum·2012
Same author

The internal dynamics of mini c TAR DNA probed by electron paramagnetic resonance of nitroxide spin-labels at the lower stem, the loop, and the bulge.

Biochemistry·2012
Same author

Electrochemical depassivation of zero-valent iron for trichloroethene reduction.

Journal of hazardous materials·2012
Same author

Derivation of quantum work equalities using a quantum Feynman-Kac formula.

Physical review. E, Statistical, nonlinear, and soft matter physics·2012

Related Experiment Video

Updated: Sep 26, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

703

Securing content-based image retrieval on the cloud using generative models.

Yong Wang1, Fan-Chuan Wang1, Fei Liu1

  • 1School of Computer Science and Engineering, Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu, China.

Multimedia Tools and Applications
|April 18, 2022
PubMed
Summary

This study introduces Sec-Defense-Gan, a secure framework for cloud-based Content-Based Image Retrieval (CBIR) using deep neural networks (DNNs). It protects user data and generative adversarial networks (GANs) from cloud-based threats, ensuring privacy and model integrity.

Keywords:
Content-based image retrievalDeep neural networks (DNNs)Generative adversarial networks (GANs)Lattice-based homomorphic schemesecure multiparty computation

More Related Videos

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

1.1K

Related Experiment Videos

Last Updated: Sep 26, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

703
Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

1.1K

Area of Science:

  • Cloud computing security
  • Deep learning applications
  • Image retrieval systems

Background:

  • Cloud-based Content-Based Image Retrieval (CBIR) using Deep Neural Networks (DNNs) offers scalability but faces security challenges.
  • Protecting user image confidentiality and defending against adversarial examples in CBIR is crucial.
  • Generative Adversarial Networks (GANs) can defend against adversarial attacks but are vulnerable to data reconstruction if not secured.

Purpose of the Study:

  • To address the security vulnerabilities in cloud-based CBIR systems utilizing DNNs and GANs.
  • To develop a secure framework that protects both user image data and the integrity of GAN models.
  • To enable secure generative model evaluation and gradient descent computation in GANs within a cloud environment.

Main Methods:

  • Proposed two secure generative model evaluation algorithms.
  • Developed two secure minimizer protocols for gradient descent computation.
  • Implemented Sec-Defense-Gan, a novel secure image reconstruction framework.

Main Results:

  • Demonstrated the effectiveness of Sec-Defense-Gan in maintaining confidentiality of image data, generative models, and outputs.
  • Validated the performance and correctness of the proposed framework through benchmarks on public image datasets.
  • Showcased the ability to secure GANs against potential abuse for reconstructing user data.

Conclusions:

  • Sec-Defense-Gan provides a robust solution for secure cloud-based CBIR.
  • The framework ensures data privacy and model security against sophisticated threats.
  • This research advances the security of deep learning applications in cloud environments for image retrieval.