@article {689,
	title = {Cloud Computing Intrusion Detection Using Artificial Bee Colony-BP Network Algorithm},
	journal = {Journal of Digital Information Management},
	volume = {16},
	year = {2018},
	month = {08/2018},
	pages = {203-209},
	type = {Research},
	author = {Yang Hui}
}
@article {825,
	title = {Cloud Computing Intrusion Detection Using Artificial Bee Colony-BP Network Algorithm-},
	journal = {Journal of Digital Information Management},
	volume = {16},
	year = {2018},
	month = {08/2018},
	pages = {203-209},
	type = {Research},
	chapter = {203},
	abstract = {<p>\&nbsp;Cloud computing characterizes a methodology for computing communications in a much effective manner, and a business paradigm for trading computing resources and services. Alternatively, these difficult and distributed planning{\textquoteright}s turn a striking objective for intruders. Cloud computing provides huge latent for enhancing production and decrease expenditures. However it simultaneously acquires several novel security risks. Intrusion Detection Systems (IDS) have been employed broadly for identifying malicious actions in network communication and hosts. In this work, an artificial bee colony-BP neural network algorithm is applied to the detection module, in order to detect the complicated aggressive behaviors. Through example verification, the artificial bee colony-BP network algorithm has improved intrusion detection efficiency and classification precision, and can effectively guarantee the safety of the cloud computing environment.</p>
},
	doi = {https://doi.org/10.6025/jdim/2018/16/4/203-209},
	url = {http://dline.info/fpaper/jdim/v16i4/jdimv16i4_5.pdf},
	author = {Yang Hui}
}
