Matches in SemOpenAlex for { <https://semopenalex.org/work/W3018971134> ?p ?o ?g. }
Showing items 1 to 65 of
65
with 100 items per page.
- W3018971134 abstract "As one of the fundamental approaches for code optimization and performance analysis, profiling software activities can provide information on the existence of malware, code execution problems, etc. In this paper, we propose a methodology to profile a system with no overhead. The approach leverages electromagnetic (EM) emanations while executing a program, and exploits its flow diagram by constructing a Markov model. The states of the model are considered as the heavily executed blocks (called <i>hot paths</i>) of the program, and the transition between any two states is possible only if there exists a branching operation which enables execution of corresponding states without any intermediate state. To identify the state of the program, we utilize a supervised learning method. To do so, we first collect signals for each state, extract features, and generate a dictionary. The features are considered as the activated frequencies when the program is executed. The assumption here is that there exists at least one unique frequency component that is only active for one unique state. Moreover, to degrade the e↵ect of interruptions and other signals emanated from other parts of the device, and to obtain signals with high Signal-to-Noise Ratio (SNR), we average the output of Short-Time Fourier Transform (STFT). After extracting features, we apply Principle Component Analysis (PCA) for dimension reduction which helps monitoring systems in real time. Finally, we describe experimental setup and show results to demonstrate that the proposed methodology can detect malware activity with high accuracy." @default.
- W3018971134 created "2020-05-01" @default.
- W3018971134 creator A5007992397 @default.
- W3018971134 creator A5018695384 @default.
- W3018971134 creator A5022670665 @default.
- W3018971134 creator A5051170823 @default.
- W3018971134 creator A5089665637 @default.
- W3018971134 date "2020-04-24" @default.
- W3018971134 modified "2023-10-17" @default.
- W3018971134 title "Program profiling based on Markov models and EM emanations" @default.
- W3018971134 doi "https://doi.org/10.1117/12.2560808" @default.
- W3018971134 hasPublicationYear "2020" @default.
- W3018971134 type Work @default.
- W3018971134 sameAs 3018971134 @default.
- W3018971134 citedByCount "5" @default.
- W3018971134 countsByYear W30189711342020 @default.
- W3018971134 countsByYear W30189711342021 @default.
- W3018971134 countsByYear W30189711342023 @default.
- W3018971134 crossrefType "proceedings-article" @default.
- W3018971134 hasAuthorship W3018971134A5007992397 @default.
- W3018971134 hasAuthorship W3018971134A5018695384 @default.
- W3018971134 hasAuthorship W3018971134A5022670665 @default.
- W3018971134 hasAuthorship W3018971134A5051170823 @default.
- W3018971134 hasAuthorship W3018971134A5089665637 @default.
- W3018971134 hasConcept C111919701 @default.
- W3018971134 hasConcept C113775141 @default.
- W3018971134 hasConcept C11413529 @default.
- W3018971134 hasConcept C124101348 @default.
- W3018971134 hasConcept C154945302 @default.
- W3018971134 hasConcept C187191949 @default.
- W3018971134 hasConcept C199360897 @default.
- W3018971134 hasConcept C23224414 @default.
- W3018971134 hasConcept C2777904410 @default.
- W3018971134 hasConcept C2779960059 @default.
- W3018971134 hasConcept C41008148 @default.
- W3018971134 hasConcept C541664917 @default.
- W3018971134 hasConceptScore W3018971134C111919701 @default.
- W3018971134 hasConceptScore W3018971134C113775141 @default.
- W3018971134 hasConceptScore W3018971134C11413529 @default.
- W3018971134 hasConceptScore W3018971134C124101348 @default.
- W3018971134 hasConceptScore W3018971134C154945302 @default.
- W3018971134 hasConceptScore W3018971134C187191949 @default.
- W3018971134 hasConceptScore W3018971134C199360897 @default.
- W3018971134 hasConceptScore W3018971134C23224414 @default.
- W3018971134 hasConceptScore W3018971134C2777904410 @default.
- W3018971134 hasConceptScore W3018971134C2779960059 @default.
- W3018971134 hasConceptScore W3018971134C41008148 @default.
- W3018971134 hasConceptScore W3018971134C541664917 @default.
- W3018971134 hasLocation W30189711341 @default.
- W3018971134 hasOpenAccess W3018971134 @default.
- W3018971134 hasPrimaryLocation W30189711341 @default.
- W3018971134 hasRelatedWork W1827256152 @default.
- W3018971134 hasRelatedWork W2145546708 @default.
- W3018971134 hasRelatedWork W2340189285 @default.
- W3018971134 hasRelatedWork W2348361596 @default.
- W3018971134 hasRelatedWork W2738219410 @default.
- W3018971134 hasRelatedWork W2980605179 @default.
- W3018971134 hasRelatedWork W3016595359 @default.
- W3018971134 hasRelatedWork W4205463026 @default.
- W3018971134 hasRelatedWork W4205985752 @default.
- W3018971134 hasRelatedWork W4313314976 @default.
- W3018971134 isParatext "false" @default.
- W3018971134 isRetracted "false" @default.
- W3018971134 magId "3018971134" @default.
- W3018971134 workType "article" @default.