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An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and the most recent attack patterns in network traffic, ensuring data quality for analysis, (2) CSNN‐based Detection, where outlier identification is conducted by comparing two dataset groups (the normal set and the attack set) within the same time period to enhance anomaly detection and (3) In the evaluation level, the detection performance of the proposed model is assessed by comparing it with two benchmark models: ZD‐Deep Learning (ZD‐DL) and ZD‐ Convolutional Neural Network (ZD‐CNN). The implementation results demonstrate that ZD‐ CSNN achieves superior accuracy in detecting zero‐day attacks compared to both ZD‐DL and ZD‐CNN.</p>
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
An Experimental Study of the Server-based Unfairness Solutions for the Cross-Protocol Scenario of Adaptive Streaming over HTTP/3 and HTTP/2
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Since the introduction of the HTTP/3, research has focused on evaluating its influences on the existing adaptive streaming over HTTP (HAS). Among these research, due to irrelevant transport protocols, the cross-protocol unfairness between the HAS over HTTP/3 (HAS/3) and HAS over HTTP/2 (HAS/2) has caught considerable attention. It has been found that the HAS/3 clients tend to request higher bitrates than the HAS/2 clients because the transport QUIC obtains higher bandwidth for its HAS/3 clients than the TCP for its HAS/2 clients. As the problem originates from the transport layer, it is likely that the server-based unfairness solutions can help the clients overcome such a problem. Therefore, in this paper, an experimental study of the se

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
The Economic Feasibility of the beekeeping project Using the method of mobile promiscuous
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               An update of our research is the first to develop and reform the agricultural sector . and promoting production and productivity of this sector multi-sources , which is the management and beekeeping one source . Been applied to the style of beekeeping mobile promiscuous includes twentieth cell in the Iraqe project of mussiab . in which there exist a variety of crops and trees .

Experiment had proved successful and led to raise the level of npoduction of single Dell of the honey to 49 kg over the previous year and surpassed the average production percell in the province of Babylon , which the amount of 13.945 kg , another

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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers 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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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Enhancement Ear-based Biometric System Using a Modified AdaBoost Method
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          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

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Publication Date
Thu Mar 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
PART 2 An Experiment on the Box plot
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Abstract

These experiments seek to investigate the effects of the fixed variations to the basic box plot on subjects' judgments of the box lengths. The study consists of two experiments, were constructed as an extension to the experiments carried out previously by Hussin, M.M. (1989, 2006).  Subjects were asked to judge what percentage the shorter represented of the longer length in pairs of box lengths and give an estimate of percentage, one being a standard plot and the other being of a different box length and also varying with respect to other elements such as, box width or whisker length. When he (1989) suggested in the future research points (1, 2), the changing length of the st

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Publication Date
Fri Aug 30 2024
Journal Name
Iraqi Journal Of Science
The Migration Effect on an Eco-toxicant Model
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This paper proposes and studies an ecotoxicant system with Lotka-Volterra functional response for predation including prey protective region. The equilibrium points and the stability of this model have been investigated analytically both locally and globally. Finally, numerical simulations and graphical representations have been utilized to support our analytical findings

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Analysing errors in learning the preasent continuous tense:Associating interference with strategy of instruction
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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Strategic audit in detection of financial corruption cases in Iraq - Proposed Framework
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This research focuses on detecting the financial corruption cases in Iraq in light of adoption the strategic audit, the paper deals with the problem of the proliferation corruption cases particularly financial in Iraq and dramatically in the presence of audit and control devices as well as inspection and integrity devices, which indicates the existence of deficiencies and weaknesses in those devices in the implementation of audit and control functions in order to detect the corruption cases in the economic units in Iraq.

Stems objective of this research through the provision of approach of strategic audit concepts and indicate the extent importance of adopting of strategic audit as a means to detect the f

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Publication Date
Fri May 16 2025
Journal Name
Asean Journal Of Science And Engineering
Enhancing Predictive Maintenance in Energy Systems Using a Hybrid Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) Framework for Rotating Machinery
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This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

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