Chaotic Metaheuristics with Multi-Spiking Neural Network Based Cloud Intrusion Detection

Cloud Computing(CC)provides data storage options as well as computing services to its users through the Internet.On the other hand,cloud users are concerned about security and privacy issues due to the increased number of cyberattacks.Data protection has become an important issue since the users’information gets exposed to third parties.Computer networks are exposed to different types of attacks which have extensively grown in addition to the novel intrusion methods and hacking tools.Intrusion Detection Systems(IDSs)can be used in a network to manage suspicious activities.These IDSs monitor the activities of the CC environment and decide whether an activity is legitimate(normal)or malicious(intrusive)based on the established system’s confidentiality,availability and integrity of the data sources.In the current study,a Chaotic Metaheuristics with Optimal Multi-Spiking Neural Network-based Intrusion Detection(CMOMSNN-ID)model is proposed to secure the cloud environment.The presented CMOMSNNID model involves the Chaotic Artificial Bee Colony Optimization-based Feature Selection(CABC-FS)technique to reduce the curse of dimensionality.In addition,the Multi-Spiking Neural Network(MSNN)classifier is also used based on the simulation of brain functioning.It is applied to resolve pattern classification problems.In order to fine-tune the parameters relevant to theMSNN model,theWhale Optimization Algorithm(WOA)is employed to boost the classification results.To demonstrate the superiority of the proposed CMOMSNN-ID model,a useful set of simulations was performed.The simulation outcomes inferred that the proposed CMOMSNN-ID model accomplished a superior performance over other models with a maximum accuracy of 99.20%.

Innovation of Super Early-Mature Millet Germplasm with Sweet-Stem and Multi-Spikes

A new millet (Setaria italica Beauv) variety, super early-mature millet No.1, was bred by means of gene bank breedingmethod of target characters. This variety has the following outstanding characters. (1) Super early-mature. This varietyonly needs 1550C effective accumulated temperature and can normally maturate in the Bashang Region in Hebei Provinceof Chi na, which can break through the limit zone of millet cultivation and move the cultivation zone northward greatly. (2)Multi-spikes, in addition to the effect tilling at the top, the nodes in the low-middle part also can produce spikes. (3) Sweetstem have high sugar content. The contents of whole-sugar, soluable sugar and deoxidized sugar are 74.8, 200.5, 237.2%higher than the regular varieties respectively. (4) High gross protein content. The content of gross protein is higher thanthe regular varieties by 3.9-30.4%. (5)Changeable grain color. The grain color of super early-mature millet No.1 is red inShijiazhuang, but yellow in the Bashang region. In addition, this variety is characterized by good quality, high yield, andgood synthetic traits