As organizations generate and store more data in the cloud and hybrid infrastructures, their databases’ attack surface area grows. This makes organizational databases a prime target for cyber-attacks. Using only the perimeter security and existing database controls is not enough to protect against APT, insider threat and zero-day attack. A novel Database Cybersecurity System framework is presented to move beyond silos to proactive, smart layered security, in this article. The proposed system provides real-time threat analytics, adaptive encryption, and incident automation all within one management centre. It involves designing a core monitoring agent, analysis engine based on machine learning, and policy enforcement module. Comparison analysis shows that DBCS has better performance than traditional IDS and SIEM against contextual awareness and response latency. Which results in enhanced security of blockchain networks with decentralized BCS? The pseudo-code presents the basic functions for anomaly detection and automatic quarantine. As per the simulated results, we find 92% reduction of false positive and mean time to respond (MTTR) to critical threat to be less than 2 seconds and that in case of conventional it is 15 minutes. Ultimately, this paper shows that behavior baselining through machine learning along with immutable audit logging through the blockchain can secure the next-generation database. Implementation and capacity building should be carefully undertaken, it is recommended. The networks of Professor must embed Cyber Defense Ecosystems.
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Use Almtafr axis to study the response component that isolates gave a positive response to the use of standard Almtafr which leads to lower the temperature and the number of cells at a temperature suitable Rifampicin resistant less than that TJ and similarly reflected on the frequency of mutations induced
In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.
So, this study aimed at testing the system performance at poor s
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Abstract
The aim of this work is to create a power control system for wind turbines based on fuzzy logic. Three power control loop was considered including: changing the pitch angle of the blade, changing the length of the blade and turning the nacelle. The stochastic law was given for changes and instant inaccurate assessment of wind conditions changes. Two different algorithms were used for fuzzy inference in the control loop, the Mamdani and Larsen algorithms. These two different algorithms are materialized and developed in this study in Matlab-Fuzzy logic toolbox which has been practically implemented using necessary intelligent control system in electrical engineerin
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In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load at different operating frequencies. The effect of relative density, depth of embedment, foundation area as well as the imposed harmonic load was investigated. It was found that the amplitude of displacement of the foundation increases with increasing the amplitude of dynamic force and operating frequency meanwhile it decreases with increasing the relative density of sand, degree of saturation, depth of embedment and contact area of footing. The maximum displacement was noticed at 33.34 to 41.67 Hz. The maximum displaceme
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Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or
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