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National Science Foundation

Cyber-Physical Systems Virtual Organization

Read-only archive of site from September 29, 2023.

CPS-VO

legitimate application

biblio

Visible to the public Text Mining for Malware Classification Using Multivariate All Repeated Patterns Detection

Submitted by grigby1 on Thu, 10/29/2020 - 11:12am
  • privacy
  • Metrics
  • mobile computing
  • mobile devices
  • Mobile handsets
  • mobile phones
  • mobile users
  • multivariate all repeated pattern detection
  • Payloads
  • malware family classification
  • pubcrawl
  • randomly selected malware applications
  • resilience
  • Resiliency
  • smart phones
  • smartphone users
  • Social network services
  • Text Mining
  • invasive software
  • Androids
  • ARPaD
  • bank accounts
  • cyber criminals
  • Data mining
  • Human behavior
  • Humanoid robots
  • internet
  • Android Malware Detection
  • legitimate application
  • LERP-RSA
  • malware
  • malware classification
  • malware dataset
  • malware detection
  • malware families
biblio

Visible to the public Detecting mobile botnets through machine learning and system calls analysis

Submitted by grigby1 on Mon, 12/04/2017 - 12:57pm
  • malware
  • threat minimization
  • system call analysis
  • statistical feature extraction
  • statistical analysis
  • self-generated dataset
  • Resiliency
  • pubcrawl
  • pattern detection
  • Monitoring
  • Mobile handsets
  • mobile environment
  • mobile computing
  • Mobile communication
  • mobile botnet detection
  • Metrics
  • anomalous behavior identification
  • machine learning algorithms
  • machine learning
  • legitimate application
  • learning (artificial intelligence)
  • invasive software
  • Internet security
  • internet
  • host-based approach
  • feature extraction
  • desktop domain
  • computer network security
  • Compositionality
  • close-to-reality scenario
  • botnets
  • anomaly-based approach

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