Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is openly accessible. It evaluates the performance of a complete arrangement of machine learning algorithms and network traffic features to indicate the best features for detecting the assured attack classes. Our goal is storing the address of destination IP that is utilized to detect an intruder by method of misuse detection.
The present study was designed to synthesize a number of new Ceftriaxone derivatives by its involvement with a series of different amines, through the chemical derivatization of its 2-aminothiazolyl- group into an amide with chloroacetyl chloride, which on further conjugation with these selected amines will produce compounds with pharmacological effects that may extend the antimicrobial activity of the parent compound depending on the nature of these moieties.
Ceftriaxone was first equipped with a spacer arm (linker) by the action of chloroacetyl chloride in aqueous medium and then further reacted with seven different aliphatic and aromatic amines which resulted in the production of the aimed final target products. The syntheses
... Show MoreIn this work, N-hydroxy phthalimide derivatives (NHPID) were synthesized from the nucleuphilic substitution reactions of (NHPI) with different halides (alkyl halides, sulfonyl halides, benzoyl halides and benzyl halides). The products were distinguished using FTIR spectrum and Nuclear magnetic resonsnce (1H-NMR and 13CNMR), in addition to other characteristic methods such as sodium fution for sulfur determination. followed by measuring antibacterial (with different types of gram positive/gram negative bacteria) and antifungal activities of these compounds.
The amino thiadiazole [I] on treatment with aromatic aldehydes yielded Schiff bases [IIa-c], which cyclized to thiazolidinone [IIIa-c] derivatives by reaction with thioglycolic acid. Reaction of carbon disulfide and methyl iodide with [I] gavedithiomethyl [IV] which on treatment with o-phenylenediamine gave the condensed N-Imidazolythiadiazolylamine [V], However, reaction of [I] with phenylisocyanate and phenylisothiocyanate afforded the carbamideand carbothiamide derivatives [VI. VII] ac. The structure of these compounds was characterized from their melting point, FTIR spectroscopy and elementalanalysis
Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks
... Show MoreFace Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra
... Show MoreBackground: Hyperthyroidism refers to overactive of thyroid gland leading to excessive synthesis of thyroid hormones and accelerated metabolism in the peripheral tissue. Objective: The aim of this study is to evaluate a new member of the IL-1 super family of cytokines interleukin-33(IL-33) levels in serum .in order to evaluate its utility as clinical bio marker of autoimmune disease (i.e. hyperthyroidism) Methods: The present study was conducted on 30 patients from the Iraqi female patients with hyperthyroidism attending Baghdad teaching hospital, in addition to 30 healthy controls. All subjects were (35-65) years old. Parameters measured in the sera of patients and healthy groups, were interleukin -33 (IL-33), Thyroxin (T4), Thyroxin (T3)
... Show MoreResearchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l
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