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Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific threat data recovered from the publicly available data sets CICIDS2017 and IoT-23. Classification of network anomalies and feature extraction are carried out with the help of deep learning models such as CNN and LSTM. This paper’s proposed system complies with IEEE standards like IEEE 802.15.4 for secure IoT transmission and IEEE P2413 for architecture. A testbed is developed in order to use the model and assess its effectiveness in terms of overall accuracy, detection ratio, and time to detect an event. The findings of the study prove that threat intelligence systems built with deep learning provide explicit security to IoT networks when they are designed as per the IEEE guidelines. The proposed model retains a high detection rate, is scalable, and is useful in protecting against new forms of attacks. This research develops an approach to provide standard-compliant cybersecurity solutions to enable trust and reliability in the IoT applications across the industrial sectors. More future research can be devoted to the implementation of this system within the context of the newest advancements in technologies, such as edge computing.

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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Reasoning-based Intelligent Systems
SLMS: a smart library management system based on an RFID technology
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Publication Date
Wed Jun 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Airborne Computer System Path-Tracking Based Multi-PID-PSO Controller Design
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
National Grid Connected 3-Phase Inverter based on Photovoltaic Solar System
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In this paper, a national grid-connected photovoltaic (PV) system is proposed. It extracts the maximum power point (MPP) using three-incremental-steps perturb and observe (TISP&O) maximum power point tracking (MPPT) method. It improves the classic P&O by using three incremental duty ratio (ΔD) instead of a single one in the conventional P and O MPPT method. Therefore, the system's performance is improved to a higher speed and less power fluctuation around the MPP. The Boost converter controls the MPPT and then is connected to a three-phase voltage source inverter (VSI). This type of inverter needs a high and constant input voltage. A second-order low pass (LC) filter is connected to the output of VSI to reduce t

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Publication Date
Mon Oct 31 2022
Journal Name
Ingénierie Des Systèmes D Information
Iraqi Paradigm E-Voting System Based on Hyperledger Fabric Blockchain Platform
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Voting is one of the most fundamental components of a democratic society. In 2021 Iraq held the Council of Representatives (CoR) elections in 83 electoral constituencies in 19 governorates. Nonetheless, several significant issues arose during this election, including the problem of logistics distribution, the excessively long period of ballot counting, voters can't know if their votes were counted or if their ballots were tampered with, and the inconsistent regulation of vote counting. Blockchain technology, which was just invented, may offer a solution to these problems. This paper introduces an electronic voting system for the Iraq Council of Representatives elections that is based on a prototype of the permission hyperledger fabr

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
An Electronic and Web-Based Authentication, Identification, and Logging Management System
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The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Construction of Graduation Certificate Issuing System Based on Digital Signature Technique
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With the development of computer architecture and its technologies in recent years, applications like e-commerce, e-government, e-governance and e-finance are widely used, and they act as active research areas. In addition, in order to increase the quality and quantity of the ordinary everyday transactions, it is desired to migrate from the paper-based environment to a digital-based computerized environment. Such migration increases efficiency, saves time, eliminates paperwork, increases safety and reduces the cost in an organization. Digital signatures are playing an essential role in many electronic and automatic based systems and facilitate this migration. The digital signatures are used to provide many services and s

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Publication Date
Sat Apr 01 2017
Journal Name
Image & Video Processing
Enhancement of LBP-based face identification system by adopting preprocessing techniques
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Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without ap

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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
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of coordination and joint cooperation in raising the quality of auditing in accordance with the INTOSAI standard(9150 (: Applied research in the General Company for Marketing Medicines and Medical Appliances - Kimadia
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The process of coordination and joint cooperation between SAIs and internal auditors in the public sector is considered one of the very important matters in performing efficient audits and are of high quality, especially if this coordination and cooperation is implemented in accordance with international standards, as it leads to avoiding duplication in auditing work. And the distribution of work in a distribution that achieves the objectives of auditing in general and is of general benefit to the economic unit.

The research problem lies in the weakness of the relationship between internal auditing and external auditing as a result of not applying INTOSAI Standard (9150) coordination and joint cooperation

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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