prikaz prve stranice dokumenta Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata
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master's thesis
Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:576093
Prhat, Tomislav
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Prhat, T. (2023). Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:576093

Prhat, Tomislav. "Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:576093

Prhat, Tomislav. "Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:576093

Prhat, T. (2023). 'Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 04 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:576093

Prhat T. Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 November 04] Available at: https://urn.nsk.hr/urn:nbn:hr:168:576093

T. Prhat, "Napadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:576093

Metadata
TitleNapadi na neuronske mreže za detekciju objekata umetanjem stražnjih vrata
Title (english)Backdoor Attacks Upon Object Detection Neural Networks
AuthorTomislav Prhat
MentorSven Lončarić (mentor)
Committee memberSven Lončarić (predsjednik povjerenstva)
Committee memberMarko Subašić (član povjerenstva)
Committee memberTomislav Petković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-04, Croatia
Abstract
U ovom radu dan je opis glavnih dijelova i principa rada modela za detekciju te prikriveni napadi na takve modele. Kroz poglavlja su se postepeno objašnjavali dijelovi, počevši s opisom neuronskih mreža kao temeljnog bloka strojnog učenja, pregleda srodnih radova, detaljnog objašnjenja prikrivenih napada i raznih strategija napada, zatim su objašnjene vrste okidača korištene u ovom radu, te konačno implementacija prikrivenih napada umetanjem stražnjih vrata u modele za detekciju objekata. Eksperimenti su provedeni kako bi se ispitala učinkovitost i rezultati prikrivenih napada na detekciju objekata. Rezultati eksperimenata pružaju uvid u utjecaj i rizike koje prikriveni napadi mogu imati na performanse neuronskih mreža u detekciji objekata. Konačni rezultati ovog rada su zadovoljavajući, dvije vrste okidača su imale lošije rezultate, dok su dvije vrste imale bolje rezultate nego u polaznom radu.
Abstract (english)
This paper describes the main parts and working principles of detection models and backdoor attacks on such models. Through the chapters, the parts were gradually explained, starting with the description of neural networks as a fundamental block of machine learning, an overview of related works, detailed explanations of stealth attacks and various attack strategies, then the types of triggers used in this work were explained, and the final implementation of backdoor attacks by inserting back doors in object detection models. Experiments were conducted to test the effectiveness and results of backdoor attacks on object detection. The results of the experiments provide insight into the impact and risks that backdoor attacks can have on the performance of neural networks in object detection. The final results of this work are satisfactory, two types of triggers had worse results, while two types had better results than in the initial paper.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:576093
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2023-10-11 10:13:33