Similarity Hash based Scoring of Portable Executable Files for Efficient Malware Detection in IoT
- Submitting institution
-
Oxford Brookes University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 185741447
- Type
- D - Journal article
- DOI
-
10.1016/j.future.2019.04.044
- Title of journal
- Future Generation Computer Systems
- Article number
- -
- First page
- 824
- Volume
- 110
- Issue
- -
- ISSN
- 0167-739X
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- 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
-
3
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Portable executable files are considered as the main cause of devastation by malwares. Accordingly, this work has developed a novel technique through conjoint hashing schemes that effectively assign scores to malwares and assist in significantly reducing false detection. This work builds on collaboration among OBU, Bradford, and an industrial partner from Cyber Risk Intelligence at BNP Paribas. This research work has led to completion of a PhD and the findings can potentially be used in a real security system.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -