Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15 database by dividing the record's attributes into four groups, including State, Protocol, Service, and the rest of the features is Digits. Four DNA characters were used to represent each protocol attribute values. While two DNA characters are used to represent State, Service and Digits attributes values. Then, the clustering method is applied to classify the records into two clusters, either attack or normal. The current experiment results showed that the proposed system has achieved a good detection rate and accuracy results equal to 81.22% and 82.05% respectively. Also, the system achieved fast encoding and clustering time that equal 0.385 seconds and 0.00325 seconds respectively for each record.
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In fish, a complex set of mechanisms deal with environmental stresses including hypoxia. In order to probe the hypothesis that hypoxia-induced stress could be manifested in varieties of pathways, a model species, mirror carp (Cyprinus carpio), were chronically exposed to hypoxic condition (dissolved oxygen level: 1.80±0.6mg/l) for 21 days and subsequently allowed to recover under normoxic condition (dissolved oxygen level: 8.2±0.5mg/l) for 7 days. At the end of these exposure periods, an integrated approach was applied to evaluate several endpoints at different levels of biological organisation. These included determination of (i) oxidative damage to DNA in erythrocytes (using modified comet assay), (ii) lipid peroxidation in liver sample
... Show MoreDouble hydrothermal method was used to prepare nano gamma alumina using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, CTAB (cetyltrimethylammonium bromide) as surfactant, and variable acids: weak acids like; citric, and acitic acids, and strong acids like; hydrochloric and nitric acids as a bridge between aluminum salts and surfactant. Different crystallization times 12, 24, 48, and 72 hrs were applied. All the batches were prepared at pH equals to 9. XRD diffraction technique was used to investigate the crystalline nano gamma alumina pure from surfactant. N2 adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the average p
... Show MoreCopper oxide thin films were deposited on glass substrate using Successive Ionic Layer Adsorption and Reaction (SILAR) method at room temperature. The thickness of the thin films was around 0.43?m.Copper oxide thin films were annealed in air at (200, 300 and 400°C for 45min.The film structure properties were characterized by x-ray diffraction (XRD). XRD patterns indicated the presence of polycrystalline CuO. The average grain size is calculated from the X-rays pattern, it is found that the grain size increased with increasing annealing temperature. Optical transmitter microscope (OTM) and atomic force microscope (AFM) was also used. Direct band gap values of 2.2 eV for an annealed sample and (2, 1.5, 1.4) eV at 200, 300,400oC respect
... Show MoreSome maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.
The operation and management of water resources projects have direct and significant effects on the optimum use of water. Artificial intelligence techniques are a new tool used to help in making optimized decisions, based on knowledge bases in the planning, implementation, operation and management of projects as well as controlling flowing water quantities to prevent flooding and storage of excess water and use it during drought.
In this research, an Expert System was designed for operating and managing the system of AthTharthar Lake (ESSTAR). It was applied for all expected conditions of flow, including the cases of drought, normal flow, and during floods. Moreover, the cases of hypothetical op
... Show MoreImage databases are increasing exponentially because of rapid developments in social networking and digital technologies. To search these databases, an efficient search technique is required. CBIR is considered one of these techniques. This paper presents a multistage CBIR to address the computational cost issues while reasonably preserving accuracy. In the presented work, the first stage acts as a filter that passes images to the next stage based on SKTP, which is the first time used in the CBIR domain. While in the second stage, LBP and Canny edge detectors are employed for extracting texture and shape features from the query image and images in the newly constructed database. The p
In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho
... Show MoreBiometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
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