00403nas a2200121   4500008004100000245008900041210006900130260001200199300001200211490000700223100001400230856003700244       2018                        eng d00aCloud Computing Intrusion Detection Using Artificial Bee Colony-BP Network Algorithm0 aCloud Computing Intrusion Detection Using Artificial Bee ColonyB  c08/2018  a203-2090 v161 aHui, Yang  uhttps://dline.info/newl/node/68901399nas a2200133   4500008004100000245009000041210006900131260001200200300001200212490000700224520096400231100001401195856005601209       2018                        eng d00aCloud Computing Intrusion Detection Using Artificial Bee Colony-BP Network Algorithm-0 aCloud Computing Intrusion Detection Using Artificial Bee ColonyB  c08/2018  a203-2090 v163 a<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’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>
1 aHui, Yang  uhttp://dline.info/fpaper/jdim/v16i4/jdimv16i4_5.pdf