2010 3rd International Conference on Computer Science and Information Technology 2010
DOI: 10.1109/iccsit.2010.5563886
|View full text |Cite
|
Sign up to set email alerts
|

Hybrid Intrusion Detection System for enhancing the security of a cluster-based Wireless Sensor Network

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
55
0

Year Published

2011
2011
2023
2023

Publication Types

Select...
4
3
1

Relationship

0
8

Authors

Journals

citations
Cited by 56 publications
(55 citation statements)
references
References 8 publications
0
55
0
Order By: Relevance
“…• In [7], a Hybrid Intrusion Detection System (HIDS) has been proposed in heterogeneous cluster based WSN (CWSN).The attacks such as spoofed, altered, or replayed routing information, sinkhole, sybil, wormholes, acknowledgment spoofing, select forward, hello floods can be detected using this model.…”
Section: Hierarchical Approach •mentioning
confidence: 99%
See 1 more Smart Citation
“…• In [7], a Hybrid Intrusion Detection System (HIDS) has been proposed in heterogeneous cluster based WSN (CWSN).The attacks such as spoofed, altered, or replayed routing information, sinkhole, sybil, wormholes, acknowledgment spoofing, select forward, hello floods can be detected using this model.…”
Section: Hierarchical Approach •mentioning
confidence: 99%
“…Hybrid IDS [7] 1) Its detection rate and accuracy are high for using hybrid approach. Decision making model is very simple and fast.…”
mentioning
confidence: 99%
“…They exhibited that the exploratory outcomes demonstrate the technique advances the detection rate and count speed and beat the standard GA-based strategies. Finally, an Intrusion Detection System made in bunch head is proposed by [13]. Where, the proposed IDS is a Hybrid Intrusion Detection System (HIDS) and it comprises of anomaly and misuse detection module.…”
Section: Related Workmentioning
confidence: 99%
“…The future research will be to investigate other data mining techniques with a view to enhance the detection accuracy as close as possible to 100% while maintaining a low false positive rate. Qinglei Zhang et al [9] proposed a framework for a new approach in intrusion detection by combining two existing machine learning methods (i.e. SVM and CSOACN).…”
Section: Related Workmentioning
confidence: 99%