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Detection and prevention of SQLI attacks and develo** compressive framework using machine learning and hybrid techniques
A web application is a software system that provides an interface to its users through a web browser on any operating system (OS). Despite their...
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The evolution of ransomware attacks in light of recent cyber threats. How can geopolitical conflicts influence the cyber climate?
This article aims to analyze the current unpredictable cyber climate. In particular, Russia’s invasion of Ukraine has heightened concerns about...
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Deceiving supervised machine learning models via adversarial data poisoning attacks: a case study with USB keyboards
Due to its plug-and-play functionality and wide device support, the universal serial bus (USB) protocol has become one of the most widely used...
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Provable Dual Attacks on Learning with Errors
Learning with Errors (LWE) is an important problem for post-quantum cryptography (PQC) that underlines the security of several NIST PQC selected...
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Review on Wi-Fi Attacks and Detection Methods
This work summarizes various attacks performed on Wi-Fi networks and their impacts of it with mitigations. Attacks are classified based on WPA2 and...
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Cryptanalysis Attacks and Techniques
This chapter covers the most important and useful cryptanalytic and cryptanalysis standards, validation methods, classification, and operations of...
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Detection of security vulnerabilities in cryptographic ICs against fault injection attacks based on compressed sensing and basis pursuit
Cryptographic integrated circuits (ICs) used to implement cryptographic algorithms have been widely applied to numerous security-critical...
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Strengthening KMS Security with Advanced Cryptography, Machine Learning, Deep Learning, and IoT Technologies
This paper presents an innovative approach to strengthening Key Management Systems (KMS) against the escalating landscape of cyber threats by...
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A hybrid approach based on PUF and ML to protect MQTT based IoT system from DDoS attacks
IoT application uses MQTT, an application layer protocol that facilitates machine-to-machine communication using a central entity called broker. The...
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Detecting Denial of Service attacks using machine learning algorithms
Currently, Distributed Denial of Service Attacks are the most dangerous cyber danger. By inhibiting the server's ability to provide resources to...
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SmartiPhish: a reinforcement learning-based intelligent anti-phishing solution to detect spoofed website attacks
Phishing, a well-known cyberattack that cannot be completely eradicated from the Internet, has increased dramatically since the COVID-19 pandemic....
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Impact Analysis to Detect and Mitigate Distributed Denial of Service Attacks with Ryu-SDN Controller: A Comparative Analysis of Four Different Machine Learning Classification Algorithms
Today, the Distributed Denial of Service (DDoS) attacks are progressed, which appears in different profiles besides dissimilar standards, in this...
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Detecting Sybil Attacks in VANET: Exploring Feature Diversity and Deep Learning Algorithms with Insights into Sybil Node Associations
Vehicular ad hoc networks (VANET) facilitate vehicle to everything (V2X) communication between vehicles and road side units (RSU) to exchange safety...
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New Records in Collision Attacks on SHA-2
The SHA-2 family including SHA-224, SHA-256, SHA-384, SHA-512, SHA-512/224 and SHA512/256 is a U.S. federal standard published by NIST. Especially,...
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Event-based sliding mode control under denial-of-service attacks
This paper deals with the problem of estimator-based sliding mode control against denial-of-service (DoS) attacks and discrete events via a...
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Explaining predictions and attacks in federated learning via random forests
Artificial intelligence (AI) is used for various purposes that are critical to human life. However, most state-of-the-art AI algorithms are black-box...
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Assessment of data augmentation, dropout with L2 Regularization and differential privacy against membership inference attacks
Machine learning (ML) has revolutionized various industries, but concerns about privacy and security have emerged as significant challenges....
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A vector convolutional deep autonomous learning classifier for detection of cyber attacks
Nowadays with the exponential rise of traffic over large scale networks, Internet is vulnerable to increased number of cyber attacks. The cyber...
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Trust-based secure routing and message delivery protocol for signal processing attacks in IoT applications
Internet of Things (IoT) has a wide concentration in today’s technological world. It has a significant impact on smart infrastructure with a security...
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Digital image and video watermarking: methodologies, attacks, applications, and future directions
In recent years, internet technology has grown in advance, and multimedia data-sharing growth rates have skyrocketed. As a result, protecting...
