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.
Has been studied both processes Almetzaz and extortion of a substance Alklanda Maysan different amounts of Alcaúlan Guy 70% alcohol solution using the method when the wavelength
Algae have been used in different applications in various fields such as the pharmaceutical industry, environmental treatments, and biotechnology. Studies show that the preparation of nanoparticles by a green synthesis method is a promising solution to many medical and environmental issues. In the current study, the green alga Stigeoclonium attenuatum (Hazen) F.S. Collins 1909 was isolated and identified from the Al-Hillah River (Governorate of Babylon) in the middle of Iraq. The green synthesis by the aqueous extract of algae was used to prepare the nanoflakes of ZnO. Nanoflakes of ZnO are characterized by X-Ray diffraction (XRD) and scanning electron microscope (SEM) with flakes shape and dimensions ranging be
... Show MoreTrue random number generators are essential components for communications to be conconfidentially secured. In this paper a new method is proposed to generate random sequences of numbers based on the difference of the arrival times of photons detected in a coincidence window between two single-photon counting modules
Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them. This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c
... Show MoreIn this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from
... Show MoreIn this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant
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