Alterdroid : Differential Fault Analysis of Obfuscated Smartphone Malware
- Submitting institution
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King's College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 111164947
- Type
- D - Journal article
- DOI
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10.1109/TMC.2015.2444847
- Title of journal
- IEEE Transactions on Mobile Computing
- Article number
- -
- First page
- 789
- Volume
- 15
- Issue
- 4
- ISSN
- 1536-1233
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Highly sophisticated malware uses obfuscation to frustrate automatic/manual code analysis, thwarting the DEFEND and DEVELOP objectives of the UK National Cyber-Security Strategy. The presented methodology (algorithm) uses Fault Analysis applied to a novel domain (malware) and produces a new way of studying sophisticated malware (based on differential analysis). This technology has led to publications providing detection against targeted malware ([1]-Targetdroid) and hidden and obfuscated components ([1]-DroidSieve), and demonstrating effectiveness with advanced attacks ([1]-Stegomalware). The paper includes large scale evaluation with qualitative case study demonstrations. Core contribution of Suarez-Tangil's PhD thesis, which won Outstanding National Award (<1% successrate) (https://blog.funcas.es/entregados-los-premios-enrique-fuentes-quintana). [1] https://nms.kcl.ac.uk/guillermo.suareztangil/
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -