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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
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Wireless Network Control System for Electro Stati Precipitator in Cement Plants
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    Wireless control networks (WCNs), based on distributed control systems of wireless sensor and actuator networks, integrate four technologies: control, computer network and wireless communications. Electrostatic precipitator (ESP) in cement plants reduces the emissions from rotary kiln by 99.8% approximately. It is an important thing to change the existing systems (wireline) to wireless because of dusty and hazardous environments. In this paper, we designed a wireless control system for ESP using Truetime 2 beta 6 simulator, depending on the mathematical model that have been built using identification toolbox of Matlab v7.1.1. We also study the effect ofusing wireless network on performance and stability of the closed l

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Publication Date
Thu Dec 19 2024
Journal Name
Ieee Explorer
A Novel Flow Priority and Continuity Control Mechanism in SDN Network
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In recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate p

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Publication Date
Tue May 26 2026
Journal Name
Journal Of Baghdad College Of Dentistry
An Assessment of the Efficacy of Sinus Balloon Technique on Transcrestal Maxillary Sinus Floor Elevation Surgery
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Background: A minimally invasive antral membrane balloon elevation (MIAMBE) has been introduced to overcome the invasiveness of modified Caldwell-Luc (lateral approach) and the drawbacks of the osteotome (summers' technique) in maxillary sinus floor elevation surgery. Materials and methods: A total of 13 adult Iraqi patients aged 28-55 years, 4 males and 9 females underwent sinus floor elevation surgery via crestal approach by using sinus balloon technique. A panoramic radiograph and (Cone beam computed tomography (CBCT)/or medical CT scan) were obtained before and after surgery. Postoperative gained bone was assessed and the patient reactions including pain, nasal bleeding, and ecchymosis were recorded. The whole follow up period was 1yea

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Clinical And Experimental Dentistry
Effect of Incorporating Date Seeds Microparticles on Compressive Strength and Microhardness of Conventional Glass Ionomer (an In Vitro Study)
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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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

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Publication Date
Tue May 26 2026
Journal Name
Al–bahith Al–a'alami
New Methods and Old Issues: Theoretical and Methodological Approaches to Social Network Sites in the Arab Region
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This paper critically looks at the studies that investigated the Social Network Sites in the Arab region asking whether they made a practical addition to the field of information and communication sciences or not. The study tried to lift the ambiguity of the variety of names, as well as the most important theoretical and methodological approaches used by these studies highlighting its scientific limitations. The research discussed the most important concepts used by these studies such as Interactivity, Citizen Journalism, Public Sphere, and Social Capital and showed the problems of using them because each concept comes out of a specific view to these websites. The importation of these concepts from a cultural and social context to an Ara

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Capability to a chive An Effective Marketing Performance In Banks: applied Study in a sample of Iraqi Banks
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The marketing of banking service is considered to be one of the impotent fields which showed a universal inebriates . He research showed the comparison between the application of marketing in ideas and application for loot government and private Iraqi bank. The research comets of four parts; Mythology / the concept and the importance of Banking Marketing / Research applichlion/ Conelnion and  recommendation.

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Evaluate the effectiveness of internal control systems and their role in providing an effective governance framework in Sudanese banks
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   The study aimed to find out the relationship between the dimensions of internal control systems and the availability of an effective governance framework in the Sudanese banks. The study used descriptive and analytical method for collecting and analyzing the study data using SPSS program. The questionnaire was used as an analysis tool. The target sample of Sudanese bank employees, the study found several results, including that the bank avoids methods that lead to the rational use of available resources, and identifies and separation of tasks among employees, in addition to rapid response to reports The study found several recommendations, including the need for a list of banks that are sufficiently flexible and comp

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Publication Date
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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