Intrusion detection system using k-means clustering algorithm

 Many researches nowadays working on increase the ability of the intrusion detection systems IDS, which depend on data mining techniques in their mechanism. Whereas cyber-attacks of all kinds have been evolving , that require more efforts to fill in the gaps in intrusion detection system, increase their accuracy or the their ability of detect any ...

Intrusion detection K-means Clustering Algorithm Algorithm for Clustering with Intrusion Detection CyberSecurity Artificial intelligent

MACHINE LEARNING BASED HEALTHCARE SYSTEM FOR INVESTIGATING THE.ASSOCIATION BETWEEN DEPRESSION AND QUALITY OF LIFE

 Machine learning (ML) algorithms are nowadays widely adopted in different contexts to perform autonomous decisions and predictions. Due to the high volume of data shared in the recent years, ML algorithms are more accurate and reliable since training and testing phases are more precise. An important concept to analyze when defining ML algorithms co...

MACHINE LEARNING HEALTHCARE SYSTEM

UNSUPERVISED ALGORITHMS TO DETECT ZERO-DAYATTACKS STRATEGY AND APPLICATION

 ? In the last decade, researchers, practitioners and companies struggled for devising mechanisms to detect cyber-security threats. Among others, those efforts originated rule-based, signature-based or supervised Machine Learning (ML) algorithms that were proven effective for detecting those intrusions that have already been encountered and characte...

DEEP LEARNING APPLICATION

UNSUPERVISED ALGORITHMS TO DETECT ZERO-DAY.ATTACKS STRATEGY AND APPLICATION

 ? In the last decade, researchers, practitioners and companies struggled for devising mechanisms to detect cyber-security threats. Among others, those efforts originated rule-based, signature-based or supervised Machine Learning (ML) algorithms that were proven effective for detecting those intrusions that have already been encountered and characte...

DEEP LEARNING ATTACKS STRATEGY AND APPLICATION

Sniffer mail

 One of the essential services on the internet is the Email Service. The Email server can be vulnerable to several types of cyber-attacks. This research aims to analyze and improve the Email service. This mail is the process of following the path and function performed by the receiver on the received mail. The development of this system serves as a ...

PPSF A Privacy-Preserving and Secure Framework using Blockchain-based Machine-Learning for IoT-driven Smart Cities

 With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of urbanization. IoT networks allow distributed smart devices to collect and process data within smart city infrastructure using an open channel, the Internet. Thus, challenges such as centralization, security, privacy (e.g., performing data poisoning and in...

A Transfer Learning Approach for Securing Resource-Constrained IoT Devices

 In recent years, Internet of Things (IoT) security has attracted significant interest by researchers due to new characteristics of IoT such as heterogeneity of devices, resource constraints, and new types of attacks targeting IoT. Intrusion detection, which is an indispensable part of a security system, is also included in these studies. In order t...

Timely Detection and Mitigation of Stealthy DDoS Attacks via IoT Networks

 Internet of Things (IoT) networks consist of sensors, actuators, mobile and wearable devices that can connect to the Internet. With billions of such devices already in the market which have significant vulnerabilities, there is a dangerous threat to the Internet services and also some cyber-physical systems that are also connected to the Internet. ...

Transfer Learning Promotes 6G Wireless Communications Recent Advances and Future Challenges

 In the coming 6G communications, network densification, high throughput, positioning accuracy, energy efficiency, and many other key performance indicator requirements are becoming increasingly strict. In the future, how to improve work efficiency while saving costs is one of the foremost research directions in wireless communications. Being able t...

Predictive Boundary Tracking based on Motion Behavior Learning for Continuous Objects in Industrial Wireless Sensor Networks

 The diffusion of toxic gas, biochemical material, and radio-active contamination, known as continuous objects, endangers the safe production of petrochemical and nuclear industry. Industrial wireless sensor networks are a new paradigm, which shows great potential in monitoring evolving hazardous phenomena in unfriendly industrial field. To prolong ...

Resilient Distributed Coordination Control of Multiarea Power Systems Under Hybrid Attacks

 Resilient distributed coordination control is studied on multiarea power systems with low inertia under hybrid attacks, including denial-of-service (DoS) attack and deception attack. The communication among various areas under the DoS attack is deteriorated to switching residual topologies whose time characteristic is modeled by model-dependent ave...

An Intrusion Detection Method Based on Machine Learning and State Observer for Train-Ground Communication Systems

 The communication-based train control (CBTC) system is a typical cyber physical system in urban rail transit.The train-ground communication system is a very important subsystem of the CBTC system and uses the wireless communication protocols to transmit control commands.However, it faces some potential information security risks.To ensure informati...

Survey of Network Intrusion Detection Methods from the Perspective of the Knowledge Discovery in Databases Process

 The identification of network attacks which target information and communication systems has been a focus of the research community for years. Network intrusion detection is a complex problem which presents a diverse number of challenges. Many attacks currently remain undetected, while newer ones emerge due to the proliferation of connected devices...

Research on Intrusion Data Mining Algorithm Based on Multiple Minimum Support

 The traditional single minimum support data mining algorithm has some problems, such as too much space occupied by data, resulting in insufficient accuracy of the algorithm, which is difficult to meet the needs of the development of the times. Therefore, an intrusion data mining algorithm based on multiple minimum support is proposed. First, the fe...

Cloud Intrusion Detection Method Based on Stacked Contractive Auto-Encoder and Support Vector Machine

 Security issues have resulted in severe damage to the cloud computing environment, adversely affecting the healthy and sustainable development of cloud computing. Intrusion detection is one of the technologies for protecting the cloud computing environment from malicious attacks. However, network traffic in the cloud computing environment is charac...