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Cluster Based Cost Efficient Intrusion Detection System For Manet

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Saravanan Kumarasamy, Hemalatha B, Hashini P

Cryptography and Security · Submitted 6 Nov 2013

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The system optimizes the leader election and intrusion detection process.

how it is stated · asserted 1.00 read the record →

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arXiv ID1311.1446 (version 1)
Pith IDBFIMYXFR, Pith's permanent record of this paper and its review
CitationHashini P, Hemalatha B, Saravanan Kumarasamy. "Cluster Based Cost Efficient Intrusion Detection System For Manet." arXiv:1311.1446 (2013). https://pith.science/paper/BFIMYXFR
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Open the compiled record

Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 13,768 input tokens, $0.0006 reported.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.06 · human participants 0.02 · controlled comparison 0.04 · randomized assignment 0.02 · states quantitative result 0.03 · compares with prior results 0.05 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

Mobile ad-hoc networks are temporary wireless networks. Network resources are abnormally consumed by intruders. Anomaly and signature based techniques are used for intrusion detection. Classification techniques are used in anomaly based techniques. Intrusion detection techniques are used for the network attack detection process. Two types of intrusion detection systems are available. They are anomaly detection and signature based detection model. The anomaly detection model uses the historical transactions with attack labels. The signature database is used in the signature based IDS schemes. The mobile ad-hoc networks are infrastructure less environment. The intrusion detection applications are placed in a set of nodes under the mobile ad-hoc network environment. The nodes are grouped into clusters. The leader nodes are assigned for the clusters. The leader node is assigned for the intrusion detection process. Leader nodes are used to initiate the intrusion detection process. Resource sharing and lifetime management factors are considered in the leader election process. The system optimizes the leader election and intrusion detection process. The system is designed to handle leader election and intrusion detection process. The clustering scheme is optimized with coverage and traffic level. Cost and resource utilization is controlled under the clusters. Node mobility is managed by the system.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Mobile ad-hoc networks are temporary wireless networks. background 1.00 0.04 0.02 asserted 1.00
s1 Network resources are abnormally consumed by intruders. background 1.00 0.09 0.02 asserted 1.00
s2 Anomaly and signature based techniques are used for intrusion detection. background 0.97 0.07 0.03 asserted 1.00
s3 Classification techniques are used in anomaly based techniques. background 0.94 0.07 0.02 asserted 1.00
s4 Intrusion detection techniques are used for the network attack detection process. background 0.99 0.06 0.03 asserted 1.00
s5 Two types of intrusion detection systems are available. background 1.00 0.05 0.03 asserted 1.00
s6 They are anomaly detection and signature based detection model. background 1.00 0.06 0.03 asserted 1.00
s7 The anomaly detection model uses the historical transactions with attack labels. background 0.87 0.07 0.03 asserted 1.00
s8 The signature database is used in the signature based IDS schemes. background 0.98 0.07 0.02 asserted 1.00
s9 The mobile ad-hoc networks are infrastructure less environment. background 1.00 0.06 0.02 asserted 1.00
s10 The intrusion detection applications are placed in a set of nodes under the mobile ad-hoc network environment. method 0.70 0.16 0.03 asserted 1.00
s11 The nodes are grouped into clusters. method 0.95 0.32 0.03 asserted 1.00
s12 The leader nodes are assigned for the clusters. method 0.98 0.36 0.03 asserted 1.00
s13 The leader node is assigned for the intrusion detection process. method 0.95 0.33 0.05 asserted 1.00
s14 Leader nodes are used to initiate the intrusion detection process. method 0.96 0.24 0.06 asserted 1.00
s15 Resource sharing and lifetime management factors are considered in the leader election process. method 0.91 0.47 0.06 asserted 1.00
s16 The system optimizes the leader election and intrusion detection process. contribution 0.92 0.67 0.26 asserted 1.00
s17 The system is designed to handle leader election and intrusion detection process. contribution 0.91 0.62 0.08 asserted 1.00
s18 The clustering scheme is optimized with coverage and traffic level. contribution 0.52 0.64 0.11 asserted 1.00
s19 Cost and resource utilization is controlled under the clusters. contribution 0.74 0.56 0.13 asserted 1.00
s20 Node mobility is managed by the system. method 0.51 0.49 0.07 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from argument 0.88.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Mobile ad-hoc networks are temporary wireless networks. Network resources are abnormally consumed by intruders. Anomaly and signature based techniques are used for intrusion detection. Classification techniques are used in anomaly based techniques. Intrusion detection techniques are used for the network attack detection process. Two types of intrusion detection systems are available. They are anomaly detection and signature based detection model. The anomaly detection model uses the historical transactions with attack labels. The signature database is used in the signature based IDS schemes. The mobile ad-hoc networks are infrastructure less environment. The intrusion detection applications are placed in a set of nodes under the mobile ad-hoc network environment. The nodes are grouped into clusters. The leader nodes are assigned for the clusters. The leader node is assigned for the intrusion detection process. Leader nodes are used to initiate the intrusion detection process. Resource sharing and lifetime management factors are considered in the leader election process. The system optimizes the leader election and intrusion detection process. The system is designed to handle leader election and intrusion detection process. The clustering scheme is optimized with coverage and traffic level. Cost and resource utilization is controlled under the clusters. Node mobility is managed by the system.

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