Evolving malware variants as antigens for antivirus systems
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gp-bibliography.bib Revision:1.7964
- @Article{murali2023evolving,
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author = "Ritwik Murali and Palanisamy Thangavel and
C. Shunmuga Velayutham",
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title = "Evolving malware variants as antigens for antivirus
systems",
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journal = "Expert Systems with Applications",
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year = "2023",
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volume = "226",
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pages = "120092",
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month = "15 " # sep,
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keywords = "genetic algorithms, genetic programming, Antigens,
Evolutionary algorithms, Malware, Malware evolution,
Virus variants",
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publisher = "Elsevier",
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ISSN = "0957-4174",
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URL = "https://human-competitive.org/sites/default/files/ritwik_gecco_humies_2023.txt",
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URL = "https://human-competitive.org/sites/default/files/paper_a_ritwik.pdf",
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URL = "https://www.sciencedirect.com/science/article/pii/S0957417423005948",
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DOI = "doi:10.1016/j.eswa.2023.120092",
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size = "15 pages",
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abstract = "We propose MAGE, A Malware Antigen Generating
Evolutionary algorithm that is capable of generating
unseen variants of a given source malware. MAGE evolves
malware variants by employing code transformation
functions as mutation operators and intra-population
Jaccard similarity metric as fitness function. By
virtue of these design choices, MAGE is capable of
generating active malware variants with diverse code
structure variations while retaining the maliciousness
of the source malware. These malware variants (similar
to biological antigens) generated throughout the run of
MAGE forms a potential dataset of malware variants. The
dataset can be used to train an adaptive Antivirus
engine to learn the code structure variations that make
up the space of malware variants. This could augment
the engines ability to detect unseen malware variants,
thus preventing attacks from the same. The efficacy of
MAGE has been demonstrated with two malware viz. Timid
, a COM infector and Intruder, an EXE infector. The
simulation experiments demonstrate the potential and
versatility of MAGE towards generating diverse malware
variants.",
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notes = "Finalist 2023 HUMIES Also known as
\cite{MURALI2023120092}",
- }
Genetic Programming entries for
Ritwik Murali
Palanisamy Thangavel
C Shunmuga Velayutham
Citations