On the public citation graph
What you see predicts what you get—lightweight agent‐based malware detection
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9780470396360.ch3openalex-snapshot
Epidemic Models, Algorithms, and Protocols in Wireless Sensor and Ad Hoc Networks
inferredcites →https://doi.org/10.1103/physreve.66.035101openalex-snapshot
Email networks and the spread of computer viruses
inferredcites →https://doi.org/10.1109/acsac.2007.24openalex-snapshot
HoneyIM: Fast Detection and Suppression of Instant Messaging Malware in Enterprise-Like Networks
inferredcites →https://doi.org/10.1109/dsn.2007.78openalex-snapshot
Quantifying the Effectiveness of Mobile Phone Virus Response Mechanisms
inferredcites →https://doi.org/10.1109/icccn.2004.1401687openalex-snapshot
Email worm modeling and defense
inferredcites →https://doi.org/10.1109/infcom.2007.211openalex-snapshot
Analysis of the Reliability of a Nationwide Short Message Service
inferredcites →https://doi.org/10.1109/infcom.2009.5062067openalex-snapshot
Defending Mobile Phones from Proximity Malware
inferredcites →https://doi.org/10.1109/infocom.2006.101openalex-snapshot
Epidemiological Modelling of Peer-to-Peer Viruses and Pollution
inferredcites →https://doi.org/10.1109/risp.1991.130801openalex-snapshot
Directed-graph epidemiological models of computer viruses
inferredcites →https://doi.org/10.1109/risp.1993.287647openalex-snapshot
Measuring and modeling computer virus prevalence
inferredcites →https://doi.org/10.1109/seccomw.2006.359562openalex-snapshot
On Mobile Viruses Exploiting Messaging and Bluetooth Services
inferredcites →https://doi.org/10.1109/spca.2006.297477openalex-snapshot
An Epidemic Model of Mobile Phone Virus
inferredcites →https://doi.org/10.1109/tmc.2008.129openalex-snapshot
Modeling Propagation Dynamics of Bluetooth Worms (Extended Version)
inferredcites →https://doi.org/10.1109/tnn.2005.853425openalex-snapshot
Spatial-temporal modeling of malware propagation in networks
inferredcites →https://doi.org/10.1126/science.1167053openalex-snapshot
Understanding the Spreading Patterns of Mobile Phone Viruses
inferredcites →https://doi.org/10.1145/1080793.1080806openalex-snapshot
Modeling epidemic spreading in mobile environments
inferredcites →https://doi.org/10.1145/1378600.1378626openalex-snapshot
Behavioral detection of malware on mobile handsets
inferredcites →https://doi.org/10.1145/1378600.1378627openalex-snapshot
Detecting energy-greedy anomalies and mobile malware variants
inferredcites →https://doi.org/10.1145/1622103.1629656openalex-snapshot
Virtualized in-cloud security services for mobile devices
inferredcites →https://doi.org/10.1145/1653662.1653691openalex-snapshot
On lightweight mobile phone application certification
inferredcites →https://doi.org/10.1145/1734583.1734595openalex-snapshot
When mobile is harder than fixed (and vice versa)
inferredcites →https://doi.org/10.1145/1920261.1920264openalex-snapshot
Toward worm detection in online social networks
inferredcites →https://doi.org/10.1145/1999995.2000017openalex-snapshot
Security versus energy tradeoffs in host-based mobile malware detection
inferredcites →https://doi.org/10.1145/570758.570768openalex-snapshot
An epidemic model for information diffusion in MANETs
inferredcites →https://doi.org/10.1145/586110.586130openalex-snapshot
Code red worm propagation modeling and analysis
inferredcites →https://doi.org/10.5555/1924943.1924971openalex-snapshot
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/widm.1456openalex-snapshot
Gaining insights in datasets in the shade of “garbage in, garbage out” rationale: Feature space distribution fitting
inferred← citeshttps://doi.org/10.1016/j.adhoc.2014.07.031openalex-snapshot
Taming epidemic outbreaks in mobile adhoc networks
inferred← citeshttps://doi.org/10.1016/j.cosrev.2021.100373openalex-snapshot
Malicious application detection in android — A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.jpdc.2021.05.004openalex-snapshot
SMS Observer: A dynamic mechanism to analyze the behavior of SMS-based malware
inferred← citeshttps://doi.org/10.1109/mwc.2015.7054729openalex-snapshot
Mobile application security: malware threats and defenses
inferred← citeshttps://doi.org/10.1109/pst.2015.7232968openalex-snapshot
Real-time signature-based detection approach for SMS botnet
inferred← citeshttps://doi.org/10.1109/sarnof.2012.6222760openalex-snapshot
Catching the Wily Hacker: A multilayer deception system
inferred← citeshttps://doi.org/10.1109/tetc.2014.2316510openalex-snapshot
Large Iterative Multitier Ensemble Classifiers for Security of Big Data
inferred← citeshttps://doi.org/10.1109/tifs.2015.2469253openalex-snapshot
Employing Program Semantics for Malware Detection
inferred← citeshttps://doi.org/10.1145/2602945.2602950openalex-snapshot
SMS mobile botnet detection using a multi-agent system
inferred← citeshttps://doi.org/10.13052/jcsm2245-1439.224openalex-snapshot
Detecting Targeted Attacks By Multilayer Deception
inferred← citeshttps://doi.org/10.3233/jifs-169849openalex-snapshot
An efficient neural network model for time series forecasting of malware
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