A deep learning approach with Bayesian optimization and ensemble classifiers for detecting denial of service attacks

Detecting malicious behavior is important for preventing security threats in a computer network. Denial of Service (DoS) is among the popular cyber attacks targeted at web sites of high‐profile organizations and can potentially have high economic and time costs. In this paper, several machine learning methods including ensemble models and autoencoder‐based deep learning classifiers are compared and tuned using Bayesian optimization. The autoencoder framework enables to extract new features by mapping the original input to a new space. The methods are trained and tested both for binary and multi‐class classification on Digiturk and Labris datasets, which were introduced recently for detecting various types of DDoS attacks. The best performing methods are found to be ensembles though deep learning classifiers achieved comparable level of accuracy.     

WiSEGATE: Wireless Sensor Network Gateway framework for internet of things

With internet of things vision, computing systems get the ubiquity of real world. Wireless Sensor Network (WSN) technology plays a critical role for the construction of this paradigm. Hence, WSN technology should be adapted to support interoperability with the commodity internet entities. Since technological background of WSN and IP networks do not fit each other, this effort is not a straightforward process. In this paper, we introduce WiSEGATE which addresses end-to-end reliable interconnection problem between multiple internet entities and sensor nodes. WiSEGATE is a prototype of a new web server which supports three tier service scheme with a data acquisition mechanism of WSN to access the physical data in particular locations in the real world. In WiSEGATE, an interconnection gateway handles operations required for the interoperability. Since this gateway maintains reliable TCP/IP connections of the interconnected entities, the resource constraint sensor nodes on WSN do not require a TCP/IP stack for handling end-to-end connections. A lightweight service layer is implemented on a sensor node for operations required by the interconnection. The strength and novelty of the model lies in the fact that this lightweight service layer relieves extra memory usage for end-to-end connection management. For determining limits of the proposed model, firstly, we examined the steps for request/response mechanism and modeled the gateway as a queueing system. By doing this, we derive a definition of the request traffic. For proof of concept, we performed comprehensive tests in simulation and real testbed environments for WLAN connection. WiSEGATE can achieve reasonable response times up to 80 simultaneous connections from remote entities to WSN when WLAN PER is less than 0.2.     

Effects of operational parameters on emission performance and combustion efficiency in small-scale CFBCs

A well-designed CFBC can burn coal with high efficiency and within acceptable levels of gaseous emissions. In this theoretical study effects of operational parameters on combustion efficiency and the pollutants emitted have been estimated using a developed dynamic 2D (two-dimensional) model for CFBCs. Model simulations have been carried out to examine the effect of different operational parameters such as excess air and gas inlet pressure and coal particle size on bed temperature, the overall CO, NO_x and SO₂ emissions and combustion efficiency from a small-scale CFBC. It has been observed that increasing excess air ratio causes fluidized bed temperature decrease and CO emission increase. Coal particle size has more significant effect on CO emissions than the gas inlet pressure at the entrance to fluidized bed. Increasing excess air ratio leads to decreasing SO₂ and NO_x emissions. The gas inlet pressure at the entrance to fluidized bed has a more significant effect on NO_x emission than the coal particle size. Increasing excess air causes decreasing combustion efficiency. The gas inlet pressure has more pronounced effect on combustion efficiency than the coal particle size, particularly at higher excess air ratios. The developed model is also validated in terms of combustion efficiency with experimental literature data obtained from 300 kW laboratory scale test unit. The present theoretical study also confirms that CFB combustion allows clean and efficient combustion of coal.     

Antioxidant Activity,Total Phenolic Content and Selected Physicochemical Properties of White Mulberry (Morus Alba L.) Fruits

In this study, total phenolic content, antioxidant activity, mineral content and selected physicochemical properties of three white mulberry phenotypes (Morus alba L.) grown in Turkey were measured. Moisture, total soluble solids, total sugar, sucrose, reducing sugar, protein, ash, pH, titratable acidity, color (L, a, b), vitamin C, total phenolic, antioxidant activity of fruits were determined between 72.85–79.75 g/100 g fresh fruit, 21.25–28.50 g/100 g fresh fruit, 12.18–17.02 g/100 g fresh fruit, 1.57–4.36 g/100 g fresh fruit, 9.42–15.46 g/100 g fresh fruit, 0.82–0.89 g/100 g fresh fruit, 2.20–2.65 g/100 g fresh fruit, 5.70–5.86, 0.25–0.28 g/100 g fresh fruit, 31.24–68.69, ?2.46 to 15.68, 4.58–21.74, 10.15–21.50 mg/100 g fresh fruit, 18.16–19.24 μg gallic acid equivalent/mg of sample, and 33.96–38.96%, of sample respectively. Fruits were generally found high in P and low in Ca.     

Engineering of the Fluorescent‐Energy‐Conversion Arm of Phi29 DNA Packaging Motor for Single‐Molecule Studies

The bacteriophage phi29 DNA packaging motor contains a protein core with a central channel comprising twelve copies of re‐engineered gp10 protein geared by six copies of packaging RNA (pRNA) and a DNA packaging protein gp16 with unknown copies. Incorporation of this nanomotor into a nanodevice would be beneficial for many applications. To this end, extension and modification of the motor components are necessary for the linkage of this motor to other nanomachines. Here the re‐engineering of the motor DNA packaging protein gp16 by extending its length and doubling its size using a fusion protein technique is reported. The modified motor integrated with the eGFP‐gp16 maintains the ability to convert the chemical energy from adenosine triphosphate (ATP) hydrolysis to mechanical motion and package DNA. The resulting DNA‐filled capsid is subsequently converted into an infectious virion. The extended part of the gp16 arm is a fluorescent protein eGFP, which serves as a marker for tracking the motor in single‐molecule studies. The activity of the re‐engineered motor with eGFP‐gp16 is also observed directly with a bright‐field microscope via its ability to transport a 2‐µm‐sized cargo bound to the DNA.     

Fabrication of oriented electrospun cellulose nanocrystals–polystyrene composite fibers on a rotating drum

Nitrobenzene (CNC-1), trifluoromethyl benzene (CNC-2) modified and polystyrene-grafted (CNC-g) cellulose nanocrystals in polystyrene (PS)-N,N dimethylformamide (DMF) solutions were electrospun and collected as stretched and aligned fibers on a rotating drum. Scanning electron microscope pictures showed significant alignment in the case of unmodified and nitrobenzene-modified CNC-1/PS nanocomposite fibers once the linear speed of rotor reached to 15 m s⁻¹. Fiber diameter decrease was more strong with rotor speed increase in the case of trifluoromethyl benzene modified (CNC-2) and polystyrene-grafted (CNC-g) cellulose nanocrystals/PS systems. Dynamic mechanical analysis including storage and elastic modulus of electrospun-oriented fibers were performed on surface-modified and polymer-grafted CNC/PS samples. According to α transition peak, the increase in the glass-transition temperature with filler concentration was the highest in polymer-grafted CNC-g/PS composite fibers. It was due to the interpenetration of grafted polymer brushes and free polymer chains in continuous phase and resulted in restrictions of motions of polymer chains in the PS matrix. The elastic moduli of nitrobenzene (CNC-1) and trifluoromethyl benzene (CNC-2)-modified CNC-filled PS composite fibers agreed well with percolation model, which indicates the CNC–CNC interactions and network formation with an increase in concentration. Magnitude of the elastic modulus of polymer grafted CNC-g at 0.33 vol % in PS was significantly higher than the prediction from percolation theory. It was due the immobilized polymer chains around CNC-g particles. However, grafted polymer chains, at higher CNC concentrations acted like stickers among CNC particles and caused CNC agglomerates with entrapped free polystyrene from the matrix, thus caused a decrease in the elastic modulus. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48942.