Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

The present study was conducted to examine toxicological effects of copper sulfate (Cu) in common carp fish (Cyprinus carpio L.). The LC50 (median lethal concentrations) of copper on Cyprinus carpio were 3.64, 3.36, 3.04, 2.65 mg/L respectively. In general, behavioral responses of the fishes exposed to copper included uncontrolled swimming, erratic movements, loss of balance, swam near the water surface with sudden jerky movements. Haematological parameters such, red blood cells (RBC), white blood cells (WBC), haemoglobin (Hb), Packed cell volume (PCV), mean cell volume (MCV) mean cell haemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were studied. The obtained results indicated that the (RBC) and (WBC) have increas

The preparation and characterization of innovative nanocomposites based on zinc oxide nanorods (ZNR) encapsulated by graphene (Gr) nanosheets and decorated with silver (Ag), and cupper (Cu) nanoparticles (NP) were studied. The prepared nanocomposites (ZNR@Gr/Cu-Ag) were examined by different techniques including Field Emission Scanning Electron Microscope (FESEM), Transmission electron microscopy (TEM), Atomic force microscopy (AFM), UV-Vis spectrophotometer and fluorescence spectroscopy. The results showed that the ZNR has been good cover by five layers of graphene and decorated with Ag and Cu NPs with particles size of about 10-15 nm. The ZNR@Gr/Cu-Ag nanocomposites exhibit high absorption behavior in ultraviolet (UV) region of sp

Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.

Reaction of  p-fluoro benzoic acid with the thiosemicarbazide and salcialdehyde gave the new bidentate ligand .The prepared ligand Identified by FT-I.R and U.V-Visible spectcopic technique .Treatment of the prepared   ligand   with following metal ions  M=Tb(III),Eu(III),Nd(III) and La(III) ,in ethanol with a (1:1) M:L ratio and at pH=7 yielded series of neutral complexes as the general formula  [M LCl (H O ]. The prepared complexes were characterized using (FT-IR, UV-Vis) spectra , melting point, molar conductivity measurements . chloride ion content were also evolution by (mhor method) . The proposed structure of the complexes using program , chem office 3D(2004) .

The Ligand 6,6--(1,2-benzenediazo) bis (3-aminobenzoicacid) derived from o-phenylenediamine and 3-aminobenzoicacid was synthesized. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the ligand with the following metal ions (CoII, NiII, CuII and ZnII ) in aqueous ethanol with a 1:1 M:L ratio and at optimum pH. Characterization of these compounds has been done on the basis of elemental analysis, electronic data, FT-IR and UV-Vis, as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). H