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.
Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.
The aim of this work is to design an algorithm which combines between steganography andcryptography that can hide a text in an image in a way that prevents, as much as possible, anysuspicion of the hidden textThe proposed system depends upon preparing the image data for the next step (DCT Quantization)through steganographic process and using two levels of security: the RSA algorithm and the digitalsignature, then storing the image in a JPEG format. In this case, the secret message will be looked asplaintext with digital signature while the cover is a coloured image. Then, the results of the algorithmare submitted to many criteria in order to be evaluated that prove the sufficiency of the algorithm andits activity. Thus, the proposed algorit
... Show MoreThe increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage (5, 10 and 20 wt.% ) of (n-heptane, toluene, and a mixture of different ratio
... Show MoreIn this work, the rate of charge transfer (CT) reaction at the N3-ZnS interface was calculated using a quantitative computational model to evaluate the efficiency of N3-ZnS heterojunction dye-sensitized solar cell devices using different types of solvents. This work discussed the influence of the effective driving energy force on the charge transport rate and performance of N3-ZnS devices with various solvents based on a donor-acceptor model. A solar cell model was used to study the optical efficiency when changing some of its parameters, such as the type of material and the thickness of the film, as they are important factors influencing the quality of the solar cell. It was found that the transition energy varies with different so
... Show MoreOrganizations must interact with the environment around them, so the environment must be suitable for that interaction. These companies are now trying to become Learning Organizations because it try to face that challenges may rise from its environments. The Learning Organization is a concept that is becoming an increasingly widespread philosophy in modern companies, from the largest multinationals to the smallest ventures. What is achieved by this philosophy depends considerably on one's interpretation of it and commitment to it. This study gives a definition that we felt was the true ideology behind the Learning Organization and Group Working. A Learning Organization is one in which people at all levels
... Show MoreThe research aimed at designing teaching sessions using the self-scheduling strategy with a competitive style in learning handball as well as identifying differences between pre and post tests in both groups in learning short and long passes in handball. The researchers used the experimental method on 2nd-grade secondary school students. The researchers concluded using the self-scheduling strategy due to its positive effect on learning short and long handball passes in handball. Finally, the researchers recommended applying strategies and styles in teaching different school levels as well as making similar studies using teaching strategies and styles for learning handball skills in students.