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This paper presents an intrusion response system created using deep reinforcement learning, trained within an emulation environment. The emulation environment aims to represent a networked IT-OT system found within an aircraft. The goal of this paper’s ...

Vehicular networks are vulnerable to Distributed Denial of Service (DDoS), an extension of a Denial of Service (DoS) attack. The existing solutions for DDoS detection in vehicular networks use various Machine Learning (ML) algorithms. However, ...

The rapid expansion of Internet of Things (IoT) devices has introduced a new phase of inter connectivity and convenience, while also presenting notable security obstacles. This research paper investigates novel methodologies for enhancing the security ...

The rapid proliferation of the Internet of Things (IoT) has led to a significant surge in interconnected devices across diverse domains, ranging from smart homes and healthcare systems to industrial automation and smart cities. However, this ...

Due to the fast advancement of technology, cybercrime is also increasing in frequency and complexity. Since a variety of attacks evolves regularly with complex patterns and varied signatures the task of securing cyberspace becomes more and more difficult ...

Software-Defined Networking (SDN) is a contemporary network strategy utilized instead of a traditional network structure. It provides significantly more administrative efficiency and ease than traditional networks. However, the centralized control ...

• The general operation of the physical process can nevertheless be affected, and system failure is caused by specific traditional measures designed to anticipate CPS cyber-attacks.
• Also, as the system appears to be extremely complicated ...

Applications of Cyber-Physical Systems (CPSs) greatly influenceseveral industrial sectors. Treating security-related concerns with utmost seriousness is necessary for the CPS to work correctly. Although CPS supervises the manufacturing process, ...

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• Optimal features: PIGNUS is the first hybrid model to use Auto Encoder (AE) for the intrusion detection. AE is an unsupervised data compression technique that provides the encoded format of data for further processing. The method generates ...

The heterogeneous nature of the Industrial Internet of Thing (IIoT) has a considerable impact on the development of an effective Intrusion Detection System (IDS). The proliferation of linked devices results in multiple inputs from industrial ...

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One of the most effective methods of training a model for intrusion detection requires a very good selection of features from the data and efficient and robust training algorithms to facilitate a better prediction model. Choosing features scoring ...

The remarkable ability to separate and identify self and non-self in a given problem space, makes negative selection a fascinating concept of artificial immune system. Therefore, negative selection has attracted research interest and is studied ...

• Covers and discuss different negative selection taxonomies, representations and matching techniques.
• Makes an effort to survey the major works in NSA based anomaly detection with extensive comparisons.
• Mentions NSA impacts in ...

• Improved heap optimization (IHO) removed unwanted data for data quality.
• Intrusion detection systems (IDS) for cloud computing environments detected known abnormalities with minimal false alarms.
• A chaotic red deer optimization (...

Users have been urged to embrace a cloud-based environment by recent technologies and advancements. Because of the dispersed nature of cloud solutions, security is a major problem. Because it is highly exposed to intruders for any kind of assault,...

With advancements in technology, an important issue is ensuring the security of self-driving cars. Unfortunately, hackers have been developing increasingly complex and harmful cyberattacks, making them difficult to detect. Furthermore, due to the ...

In this paper, we propose a smart and robust home security system. This is for intrusion detection along with a proprietary Android application. Intruder-Spi makes use of relatively low cost but effective wireless sensors network that makes it an ...

With the rising number of data breaches, denial of service attacks and general malicious activity facing modern computer networks, there is an increasing need to quickly and effectively respond to attacks. Intrusion Detection Systems ...

To protect a network security, a good network IDS is essential. With the advancement of science and technology, present intrusion detection technology is unable to manage today's complex and volatile network abnormal traffic without taking into ...

While Vehicular Ad-hoc Network (VANET) is developed to enable effective vehicle communication and traffic information exchange, VANET is also vulnerable to different security attacks, such as DOS attacks. The usage of an intrusion detection system ...

The mainstream computing technology is not efficient in managing massive data and detecting network traffic intrusions, often including big data. The intrusions present in sustained network traffic and the massive host log event data ...

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• The feature selection is carried out by performing the proposed ensemble Support Vector Machine (ESVM) algorithm.

Finding the security vulnerabilities and solving the issues in Wireless Sensor Networks (WSN) are mandatory tasks for providing secure data transmission. Attackers or intruders are rising with various types of network harming activities. Due to ...

Cyber-surveillance and connected devices can be misused to monitor, harass, isolate, and otherwise, harm individuals. In particular, these devices gather high volumes of personal data such as account details with shared passwords, person’s ...

In today's era, the Internet's complexity, accessi- bility, and openness has greatly enhanced the security risk of information systems. The Internet's popularity entails many threats of network attacks. Detection of intrusion is one of the major ...