With the vigorous development of cloud computing, most organizations have shifted their data and applications to the cloud environment for storage, computation, and sharing purposes. During storage and data sharing ac...
详细信息
With the vigorous development of cloud computing, most organizations have shifted their data and applications to the cloud environment for storage, computation, and sharing purposes. During storage and data sharing across the participating entities, a malicious agent may gain access to outsourced data from the cloud environment. A malicious agent is an entity that deliberately breaches the data. This information accessed might be misused or revealed to unauthorized parties. Therefore, data protection and prediction of malicious agents have become a demanding task that needs to be addressed appropriately. To deal with this crucial and challenging issue, this paper presents a Malicious Agent Identification-based Data Security (MAIDS) Model which utilizes XGBoost machine learning classification algorithm for securing data allocation and communication among different participating entities in the cloud system. The proposed model explores and computes intended multiple security parameters associated with online data communication or transactions. Correspondingly, a security-focused knowledge database is produced for developing the XGBoost Classifier-based Malicious Agent Prediction (XC-MAP) unit. Unlike the existing approaches, which only identify malicious agents after data leaks, MAIDS proactively identifies malicious agents by examining their eligibility for respective data access. In this way, the model provides a comprehensive solution to safeguard crucial data from both intentional and non-intentional breaches, by granting data to authorized agents only by evaluating the agent’s behavior and predicting the malicious agent before granting data. The performance of the proposed model is thoroughly evaluated by accomplishing extensive experiments, and the results signify that the MAIDS model predicts the malicious agents with high accuracy, precision, recall, and F1-scores up to 95.55%, 95.30%, 95.50%, and 95.20%, respectively. This enormously enhances the system’s sec
In recent decades, Cellular Networks (CN) have been used broadly in communication technologies. The most critical challenge in the CN was congestion control due to the distributed mobile environment. Some approaches, ...
详细信息
The growing concerns over mitigating climate change effects resulted in power system planning and generation expansion strategies that aim in increasing penetration of intermittent renewable energy sources (RES) to fu...
详细信息
It is well-known that lithium plating significantly reduces the capacity of Li-ion batteries, particularly at elevated charging rates, high state of charge (SoC), and low temperatures. This study presents a simplified...
详细信息
This paper presents an allowable-tolerance-based group search optimization(AT-GSO),which combines the robust GSO(R-GSO)and the external quality design planning of the Taguchi ***-GSO algorithm is used to optimize the ...
详细信息
This paper presents an allowable-tolerance-based group search optimization(AT-GSO),which combines the robust GSO(R-GSO)and the external quality design planning of the Taguchi ***-GSO algorithm is used to optimize the heat transfer area of the heat exchanger *** R-GSO algorithm integrates the GSO algorithm with the Taguchi method,utilizing the Taguchi method to determine the optimal producer in each iteration of the GSO algorithm to strengthen the robustness of the search process and the ability to find the global *** conventional parameter design optimization,it is typically assumed that the designed parameters can be applied accurately and consistently throughout ***,for systems that are sensitive to changes in design parameters,even minor inaccuracies can substantially reduce overall system ***,the permissible variations of the design parameters are considered in the tolerance-optimized design to ensure the robustness of the *** optimized design of the heat exchanger system assumes that the system’s operating temperature parameters are ***,fixing the systemoperating temperature parameters at a constant value is *** paper assumes that the system operating temperature parameters have an uncertainty error when optimizing the heat transfer area of the heat exchanger *** results show that the AT-GSO algorithm optimizes the heat exchanger system and finds the optimal operating temperature in the absence of tolerance and under three tolerance conditions.
Cloud computing (CC) is a cost-effective platform for users to store their data on the internet rather than investing in additional devices for storage. Data deduplication (DD) defines a process of eliminating redunda...
详细信息
This paper aims to develop a flexible power management approach to interconnect multiple energy resources based on an isolated, monolithic multiport DC-DC power converter. Specifically, a high efficiency, ultra-compac...
详细信息
作者：
Jyothsna, D.Chandra, G. Ramesh
Department of Computer Science and Engineering Jntuh Hyderabad India
Department of Computer Science and Engineering Hyderabad India
In recent years, LIDARs (Light Detection and Ranging) have gained a lot of insight into various fields such as agriculture, astronomy, robotics, autonomous driving, forestry, etc. Point Clouds obtained through LIDAR h...
详细信息
Environmental sound classification(ESC)involves the process of distinguishing an audio stream associated with numerous environmental *** common aspects such as the framework difference,overlapping of different sound e...
详细信息
Environmental sound classification(ESC)involves the process of distinguishing an audio stream associated with numerous environmental *** common aspects such as the framework difference,overlapping of different sound events,and the presence of various sound sources during recording make the ESC task much more complicated and *** research is to propose a deep learning model to improve the recognition rate of environmental sounds and reduce the model training time under limited computation *** this research,the performance of transformer and convolutional neural networks(CNN)are *** audio features,chromagram,Mel-spectrogram,tonnetz,Mel-Frequency Cepstral Coefficients(MFCCs),delta MFCCs,delta-delta MFCCs and spectral contrast,are extracted fromtheUrbanSound8K,ESC-50,and ESC-10,***,this research also employed three data enhancement methods,namely,white noise,pitch tuning,and time stretch to reduce the risk of overfitting issue due to the limited audio *** evaluation of various experiments demonstrates that the best performance was achieved by the proposed transformer model using seven audio features on enhanced *** UrbanSound8K,ESC-50,and ESC-10,the highest attained accuracies are 0.98,0.94,and 0.97 *** experimental results reveal that the proposed technique can achieve the best performance for ESC problems.
Recognizing a face is an intricate cognitive process that showcases the remarkable capabilities of the human brain in visual perception, a phenomenon deeply rooted in evolutionary biology. In an attempt to emulate thi...
详细信息
暂无评论