Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm, to detect malicious nodes in an OBS network. The proposed semi-supervised model was trained and validated with small amount data from a selected dataset. Experiments show that the model can classify the nodes into either behaving or not-behaving classes with 90% accuracy when trained with just 20% of data. When the nodes are classified into behaving, not-behaving and potentially not-behaving classes, the model shows 65.15% and 71.84% accuracy if trained with 20% and 30% of data respectively. Comparison with some notable works revealed that the proposed model outperforms them in many respects.
Abstract
The current research is attempt to test the reflection of the lean management on the human resources management practices of two of the most important communication companies operating in Iraq (`Zain & Asia cell), The research aims to Determine the extent of adoption of the lean management approach in the two researched companies, as it improving human resource management practices. The research problem represented in the existence of lack of in some aspects of the application the lean management approach in service sector and neglecting the impact of its tools on the human resource management practices. For this purpose three principle research hypotheses has been formulated, first there is a correlation rel
... Show MoreThe widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.
The present paper puts forward an enhancement for the throughput performance metric by p
... Show MoreThe research aimed to identify and build two specialized scales for cognitive load and mental stress and to identify the level of each of them among 110-meter steeplechase runners among youth, and to prepare a psychological counseling approach to reduce the level of cognitive load and mental stress among 110-meter steeplechase runners among youth, so that the two research hypotheses are that there are differences. There are statistically significant differences between the results of the pre- and post-tests of the experimental group in measuring cognitive load. There are statistically significant differences between the results of the pre- and post-tests of the experimental group in measuring mental stress. The experimental method w
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
... Show MoreLung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio
... Show MoreIn this study, cadmium oxide (CdO) was deposited on glass bases by thermal chemical spraying technique at three concentrations (0.05, 0.1, 0.15) M and then was irradiated by CO2 laser with 10.6 μm wave length and 1W power. The results of the atomic force microscope AFM test showed that the surfaces of these CdO thin films were homogenous and that the laser irradiated effect resulted in decreasing the roughness of the surface as well as the heights of the granular peaks, indicating a greater uniformity and homogeneity of the surfaces. The optical properties were studied to determine laser effect. The results of optical tests of these thin films showed that the photoluminescence spectra and absorption s
... Show MoreThe Tigris River, a vital water resource for Iraq, faces significant challenges due to urbanization, agricultural runoff, industrial discharges, and climate change, leading to deteriorating water quality. Traditional methods for assessing irrigation water quality, such as laboratory testing and statistical modeling, are often insufficient for capturing dynamic and nonlinear relationships between parameters. This study proposes a novel application of the Gravitational Search Algorithm (GSA) to estimate the Irrigation Water Quality Index (IWQI) along the Tigris River. Using data from multiple stations, the study evaluates spatial variability in water quality, focusing on key paramete
Background: The aim of this study is to evaluate the color change ∆E of the dental enamel following treatment with 2 kinds of protector (icon infiltrant, clinpro varnish) before fixed orthodontic treatment to avoid the possible white spot lesions. Materials and Methods: Fifty four subjects treated with fixed appliances were divided into 3 groups: the 1st group was control, while the 2nd and 3rd groups were treated with icon infiltrant and clinpro varnish before bonding procedure, respectively. Color parameters (L,a,b) were recorded for the middle and gingival thirds before and after bonding procedure to get the ∆E of each group. Results: One-way ANOVA test showed a non-significant difference in ∆E between the 3 groups a
... Show MoreVision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading to blindness. Computer-Aided Diagnosis systems play an essential role in detecting features in fundus images. Fundus images may include blood vessels, exudates, micro-aneurysm, hemorrhages, and neovascularization. In this paper, our model combines automatic detection for the diabetic retinopathy classification with localization methods depending on weakly-supervised learning. The model has four stages; in stage one, various preprocessing techniques are app