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Review of NLP-based Systems in Digital Forensics and Cybersecurity (2021) …
Review of NLP-based Systems in Digital Forensics and Cybersecurity (2021)
category
context
nlp
semantics
grammar
pragmatics
morphology
Latent
Dirichlet Allocation (LDA)
aproiori algorithm
SIIMCO datasets
cosine similarity algorithm
skip-gram modeling is a word2vec algorithm variant
synchronous learning
doc2vec
Paragraph vectors
LSTM classifier
ransomware detection
system logs analysis
correctness
methodology how did they do it?
statistics
open challenges
struggle with contexts in phrases and words, colloquial,synonyms, slang, sarcasm, ambiguity, mistakes in text or speech, homophones, domain-knowledge, etc
backdoor attacks on NLP-based systems and applications. Word-level, Character-level, and Sentence-level triggers have been proven to attack NLP systems [130]. Various other types of attacks, including AI-driven attacks, NLP operations, etc., can be found in the literature [8].
conclusion
how i can apply this to my work?
contribution
references
Identifying Forensic Interesting Files in
Digital Forensic Corpora by Applying Topic Modelling (2021)
credibility
who wrote it?
David Okore Ukwen, with one publication
where is is working?
researcher
where was it published? was it refered?
isdfs (2021) - no citations