Abstract The adaptive educational systems within e-learning platforms are built in response to the fact that learning process is different for each and every learner. In order provide services study materials tailor-made learning, this type of approach seeks combine ability comprehend detect a person’s specific needs context with expertise required use appropriate pedagogy enhance process. Thus, it critical create accurate student profiles models based upon analysis their affective states,...

Recently Internet of Things (IoT) attains tremendous popularity, although this promising technology leads to a variety security obstacles. The conventional solutions do not suit the new dilemmas brought by IoT ecosystem. Conversely, Artificial Immune Systems (AIS) is intelligent and adaptive systems mimic human immune system which holds desirable properties for such dynamic environment provides an opportunity improve security. In work, we develop novel hybrid Deep Learning Dendritic Cell...

DDoS (Distributed Denial of Service) attacks have now become a serious risk to the integrity and confidentiality computer networks systems, which are essential assets in today’s world. Detecting is difficult task that must be accomplished before any mitigation strategies can used. The identification has already been successfully implemented using machine learning/deep learning (ML/DL). However, due an inherent limitation ML/DL frameworks—so-called optimal feature selection—complete...

An SQL injection attack, usually occur when the attacker(s) modify, delete, read, and copy data from database servers are among most damaging of web application attacks. A successful attack can affect all aspects security, including confidentiality, integrity, availability. (structured query language) is used to represent queries management systems. Detection deterrence attacks, for which techniques different areas be applied improve detect ability not a new area research but it still...

Recently, cloud computing resources have become one of the trending technologies that permit user to manage diverse and a huge amount data in cloud. Task scheduling is considered most significant challenges ineffective management results performance degradation. It necessary schedule task effectively with maximum resource utilization minimum execution time. Therefore, this paper proposes novel technique for effective enhanced security environment. A convolutional neural network optimized...

This research presents a novel framework for distinguishing between actual and non-suicidal ideation in social media interactions using an ensemble technique. The prompt identification of sentiments on networking platforms is crucial timely intervention serving as key tactic suicide prevention efforts. However, conventional AI models often mask their decision-making processes primarily designed classification purposes. Our methodology, along with updated method, bridges the gap Explainable...

Abstract In recent years, accumulating evidences have shown that microRNA (miRNA) plays an important role in the exploration and treatment of diseases, so detection associations between miRNA disease has been drawn more attentions. However, traditional experimental methods limitations high cost time- consuming, a computational method can help us systematically effectively predict potential miRNA-disease associations. this work, we proposed novel network embedding-based heterogeneous...

As the amount of historical data available in legal arena has grown over time, industry specialists are driven to gather, compile, and analyze this order forecast court case rulings. However, predicting justifying rulings while using judicial facts is no easy task. Currently, previous research on forecasting outcomes small experimental datasets yielded a number unanticipated predictions utilizing machine learning (ML) models conventional methodologies for categorical feature encoding. The...

Wireless physical layer authentication has emerged as a promising approach to wireless security. The topic of node classification and recognition experienced significant advancements due the rapid development deep learning techniques. potential using address security issues should not be overlooked its considerable capabilities. Nevertheless, utilization this in nodes is impeded by lack available datasets. In study, we provide two models based on data-driven approach. First, used generative...

In Internet of Things (IoT) environments, privacy and security are among some the significant challenges. Recently, several studies have attempted to apply blockchain technology increase IoT network security. However, lightweight feature devices commonly fails meet computational intensive requirements for blockchain-based models. this work, we propose a mechanism address issue. We design an architecture store device identity information in distributed ledger. Blockchain (BCoT) Gateway...

The phenomenon of phishing has now been a common threat, since many individuals and webpages have observed to be attacked by phishers. purpose activities is obtain user’s personal information for illegitimate usage. Considering the growing intensity issue, this study aimed at developing new hybrid rule‐based solution incorporating six different algorithm models that may efficiently detect control issue. incorporates 37 features extracted from methods including black listed method, lexical...

Wireless sensor networking is being used extensively in agricultural activities to increase productivity and reduce losses various ways. The greenhouse simplifies the concept of planting, which has several benefits agriculture. In models, soil pH sensors gas are commonly used. These applicable Internet Things (IoT) integrated activities. paper discusses hardware design working proposed model. addition, models for evapotranspiration also explained. key factors such as congestion control...

Epilepsy is a nervous system disorder. Encephalography (EEG) generally utilized clinical approach for recording electrical activity in the brain. Although there are number of datasets available, most them imbalanced due to presence fewer epileptic EEG signals compared with non-epileptic signals. This research aims study possibility integrating local from an epilepsy center King Abdulaziz University hospital into CHB-MIT dataset by applying new compatibility framework data integration. The...

Adversarial machine learning is a recent area of study that explores both adversarial attack strategy and detection systems attacks, which are inputs specially crafted to outwit the classification or disrupt training process systems. In this research, we performed two scenarios, used Generative Network (GAN) generate synthetic intrusion traffic test influence these attacks on accuracy learning-based Intrusion Detection Systems(IDSs). We conducted experiments including poisoning evasion...

Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link environment robustness. Data Aggregation (DA) plays a key role in WSN, it helps minimize the Energy Consumption (EC). In order trustworthy DA with rate of high aggregation for WSNs, existing research works focused on Routing In-Network (DRINA). Yet, there is no accomplishment an...

SQL injection attacks are one of the most common types on Web applications. These exploit vulnerabilities in an application’s database access mechanisms, allowing attackers to execute unauthorized queries. In this study, we propose architecture for detecting using a recurrent neural network autoencoder. The proposed was trained publicly available dataset attacks. Then, it compared with several other machine learning models, including ANN, CNN, decision tree, naive Bayes, SVM, random forest,...

Vehicle-to-grid (V2G) technology is used in the modern eco-friendly environment for demand response management. It helps reducing carbon footprints environment. However, security and privacy of information exchange between different entities are significant concerns keeping view via an open channel, i.e., Internet among such as plug-in hybrid electric vehicles (PHEVs), charging stations (CSs), controllers V2G With exponential rise Electric (EVs) usage across globe, there a requirement...

Intelligent Crowd Monitoring and Management Systems (ICMMSs) have become effective resources for strengthening safety security along with enhancing early-warning capabilities to manage emergencies in crowded situations of smart cities massive gatherings events. The main advantage such systems is their ability detect multiple features associated the crowd gathering, as they enable multi-source sensors, multi-modal data, powerful intelligent analytical methods. Unlike traditional monitoring...