Using Backdoor Attacks to Find Areas of Interest in Images

The power of neural networks increases in popularity more and more everyday. However, as for any powerful and popular tool, the security is hard to gain, here it is also the case. In recent years, backdoor attacks have become more and more popular through malicious parties, being risky for both organisations and people. In this paper we discuss the main methods of prevention against this type of attack. We also provide an experiment, with the help of which we tried to see what part of an image influences its classification. Therefore, using an algorithm for identifying backdoor attacks we made an experiment intended to find the interest zone in X-ray images.

Authors

Institutions

Publication Details

Journal
BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE
Published
2025-02-04
DOI
https://doi.org/10.70594/brain/16.1/14
Primary Topic
Digital Media Forensic Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using Backdoor Attacks to Find Areas of Interest in Images

Andreea Ioniţă
1 links
BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE
Digital Media Forensic Detection
article

Using Backdoor Attacks to Find Areas of Interest in Images

Andreea Ioniţă
article en

Abstract

The power of neural networks increases in popularity more and more everyday. However, as for any powerful and popular tool, the security is hard to gain, here it is also the case. In recent years, backdoor attacks have become more and more popular through malicious parties, being risky for both organisations and people. In this paper we discuss the main methods of prevention against this type of attack. We also provide an experiment, with the help of which we tried to see what part of an image influences its classification. Therefore, using an algorithm for identifying backdoor attacks we made an experiment intended to find the interest zone in X-ray images.

BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCEVol. 16(1)
Alexandru Ioan Cuza University (RO)
Openalex Percentile: Top 99%
Digital Media Forensic Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.