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.
Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
... Show MoreThe current study aims at identifying the impact of using learning acceleration model on the achievement of mathematics for third intermediategrade students. Forachieving this, the researchers chose the School (Al-Kholood Secondary School for Girls) affiliated to the General Directorate of Babylon Education / Hashemite Education Department for the academic year (2021/2021), The sample reached to (70) female students from the third intermediate grade, with (35) female students for each of the two research groups. The two researchers prepared an achievement test consisting of (25) objective items of multiple choice type, The psychometric properties of the test were confirmed, and after the completion of the experiment, the achievement test wa
... Show MoreIn this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational req
... Show MoreIn this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.
The organization uses many techniques and methods to ensure that they will succeed and adapted with velocity change in the internal and external environment by decision taking, especially strategic decisions.
Strategic decisions are very important for organization success because it can predict the future and deal with uncertainty, in this circumstances they need accurate and comprehensive information to make effective strategic decision.
To achieve that purpose it must owned successful Strategic Information System ( SIS ) and determined the critical success factors for this system ,which can assisted the worker to focus on the important activities to develop it.
... Show MoreThe aim of this study to identity using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students. The researchers used the experimental method to design equivalent groups with a preand post-test, and the research community was identified with the students of the third stage in the college for the academic year 2020-2021 .The subject was, (3) class were randomly selected, so (30) students distributed into (3) groups). has been conducted pretesting after implementation of the curriculum for (4) weeks and used the statistical bag of social sciences(SPSS)to process the results of the research and a set of conclusions was reached, the most important of which is t
... Show MoreThe importance of the research lies in knowing the effect of the exercises of the reciprocal method in developing some physical abilities in learning the performance of the players for the effectiveness of the long jump in an economical manner in terms of time and effort and knowing their positive impact and the extent of their impact in creating the required learning for students, and the research aims to prepare reciprocal style exercises in developing some abilities The researchers used the experimental method in the pre and post test for the experimental and control groups to suit the nature of the research, and the research community was identified for the long jump players, the Specialized School for Talent Care in the 2022 sports sea
... Show MoreConclusion The observation of the phenomenon of structural evolution of the international system and its instability on a particular situation, by its transition from unipolar to polarity to bipolarism and then to unilateralism in the early 1990s led by the United States, and to the present moment, To say that the structure by which the hierarchy of superpowers or the regime is directed in terms of its various capacities that qualify it, and with the consent of the rest of the States directing the regime to lead and lead the world's first place, has no direct relation to the stability of this system, I hope other more influential in its stability. The structure of the new international order will be completely different in terms of the r
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