Conference proceeding
Behavioral Anomaly Detection of Malware on Home Routers
PROCEEDINGS OF THE 2017 12TH INTERNATIONAL CONFERENCE ON MALICIOUS AND UNWANTED SOFTWARE (MALWARE)
01 Jan 2017
Abstract
The Internet of Things (IoT) introduced new targets and attack vectors for malicious actors who infect insecure devices with malware in order to form large botnets that can launch distributed denial of service (DDoS) attacks. These botnets comprise various infected devices such as Internet-connected cameras and home routers. This paper focuses on the unsolved problem of creating robust malware detection to secure home routers. This research compares the effectiveness of three different approaches to behavioral malware detection on home endpoint routers through the observation of kernel-level system calls on these routers: i) principal component analysis (PCA), ii) one-class support vector machines, and iii) a naive anomaly detector based on unseen n-grams.
Metrics
3 Record Views
Details
- Title
- Behavioral Anomaly Detection of Malware on Home Routers
- Creators
- Ni An - Drexel Univ, Dept Elect & Comp Engn, Philadelphia, PA 19104 USAAlexander Duff - Drexel Univ, Dept Comp Sci, Philadelphia, PA 19104 USAGaurav Naik - Drexel Univ, Dept Comp Sci, Philadelphia, PA 19104 USAMichalis Faloutsos - Univ Calif Riverside, Dept Comp Sci & Engn, Riverside, CA 92521 USASteven Weber - Drexel UniversitySpiros Mancoridis - Drexel UniversityIEEE
- Publication Details
- PROCEEDINGS OF THE 2017 12TH INTERNATIONAL CONFERENCE ON MALICIOUS AND UNWANTED SOFTWARE (MALWARE)
- Conference
- 2017 12TH INTERNATIONAL CONFERENCE ON MALICIOUS AND UNWANTED SOFTWARE (MALWARE)
- Publisher
- IEEE
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Computer Science (Computing)
- Identifiers
- 991019170597304721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Software Engineering
- Computer Science, Theory & Methods
- Engineering, Electrical & Electronic