On the public citation graph

Random forest classifier‐based safe and reliable routing for opportunistic IoT networks

https://doi.org/10.1002/dac.4646
0 signed · 34 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-981-13-0589-4_31openalex-snapshot
Detection of Advanced Malware by Machine Learning Techniques
inferredcites →https://doi.org/10.1007/978-981-15-3666-3_24openalex-snapshot
Machine Learning Based Efficient Multi-copy Routing for OppIoT Networks
inferredcites →https://doi.org/10.1007/s00500-014-1511-6openalex-snapshot
Evaluation of machine learning classifiers for mobile malware detection
inferredcites →https://doi.org/10.1007/s11276-020-02331-1openalex-snapshot
RLProph: a dynamic programming based reinforcement learning approach for optimal routing in opportunistic IoT networks
inferredcites →https://doi.org/10.1016/j.asoc.2017.07.027openalex-snapshot
A principle component analysis-based random forest with the potential nearest neighbor method for automobile insurance fraud identification
inferredcites →https://doi.org/10.1016/j.comnet.2010.05.010openalex-snapshot
The Internet of Things: A survey
inferredcites →https://doi.org/10.1016/j.cose.2016.12.001openalex-snapshot
Defense against packet collusion attacks in opportunistic networks
inferredcites →https://doi.org/10.1016/j.eswa.2020.113187openalex-snapshot
Anomaly explanation with random forests
inferredcites →https://doi.org/10.1016/j.jnca.2012.12.028openalex-snapshot
Opportunistic IoT: Exploring the harmonious interaction between human and the internet of things
inferredcites →https://doi.org/10.1016/j.jnca.2017.12.005openalex-snapshot
MATEM: A unified framework based on trust and MCDM for assuring security, reliability and QoS in DTN routing
inferredcites →https://doi.org/10.1016/j.procs.2018.07.177openalex-snapshot
Detection of DNS DDoS Attacks with Random Forest Algorithm on Spark
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1109/aina.2017.17openalex-snapshot
Supernova and Hypernova Misbehavior Detection Scheme for Opportunistic Networks
inferredcites →https://doi.org/10.1109/eit.2018.8500111openalex-snapshot
Random Forest Classifier in SDN Framework for User-Based Indoor Localization
inferredcites →https://doi.org/10.1109/greencom-ithings-cpscom.2013.122openalex-snapshot
Random Forest Classification for Detecting Android Malware
inferredcites →https://doi.org/10.1109/icdar.1995.598994openalex-snapshot
Random decision forests
inferredcites →https://doi.org/10.1109/jsyst.2016.2630923openalex-snapshot
A Machine Learning-Based Protocol for Efficient Routing in Opportunistic Networks
inferredcites →https://doi.org/10.1109/mcom.2006.248176openalex-snapshot
Opportunistic networking: data forwarding in disconnected mobile ad hoc networks
inferredcites →https://doi.org/10.1109/pst.2016.7906930openalex-snapshot
Using machine learning to secure IoT systems
inferredcites →https://doi.org/10.1109/sahcn.2019.8824952openalex-snapshot
A Machine Learning Approach Using Classifier Cascades for Optimal Routing in Opportunistic Internet of Things Networks
inferredcites →https://doi.org/10.1109/sp.2012.16openalex-snapshot
Dissecting Android Malware: Characterization and Evolution
inferredcites →https://doi.org/10.1109/tnnls.2015.2404803openalex-snapshot
Machine Learning Methods for Attack Detection in the Smart Grid
inferredcites →https://doi.org/10.1145/2701415openalex-snapshot
Verification of a Cryptographic Primitive
inferredcites →https://doi.org/10.4108/icst.simutools2009.5674openalex-snapshot
The ONE simulator for DTN protocol evaluation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/dac.4808openalex-snapshot
Energy‐efficient fuzzy logic‐based cross‐layer hierarchical routing protocol for wireless Internet‐of‐Things sensor networks
inferred← citeshttps://doi.org/10.1002/dac.5416openalex-snapshot
An application of meta‐heuristic and nature‐inspired algorithms for designing reliable networks based on the Internet of things: A systematic literature review
inferred← citeshttps://doi.org/10.1002/dac.5500openalex-snapshot
A systematic literature review of machine learning applications in IoT
inferred← citeshttps://doi.org/10.1007/s11277-024-11298-7openalex-snapshot
Kernel Extreme Learning Machine-Based Optimization Model for Routing in Opportunistic Networks
inferred← citeshttps://doi.org/10.1016/j.dcan.2022.07.002openalex-snapshot
Decentralized content sharing in mobile ad-hoc networks: A survey
inferred← citeshttps://doi.org/10.1016/j.iot.2022.100597openalex-snapshot
Deep Q learning based secure routing approach for OppIoT networks
inferred← citeshttps://doi.org/10.1016/j.iot.2025.101613openalex-snapshot
H-TERF: A hybrid approach combining fuzzy multi-criteria decision-making techniques and enhanced random forest to improve WBAN-IoT
inferred← citeshttps://doi.org/10.1016/j.pmcj.2024.101917openalex-snapshot
A comprehensive survey on Machine Learning techniques in opportunistic networks: Advances, challenges and future directions
inferred← citeshttps://doi.org/10.1155/2022/5067849openalex-snapshot
Modified Data Delivery Strategy Based on Stochastic Block Model and Community Detection in Opportunistic Social Networks
inferred← citeshttps://doi.org/10.7717/peerj-cs.2211openalex-snapshot
Hybrid computing framework security in dynamic offloading for IoT-enabled smart home system
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.