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Retaliating against cyber-attacks: a decision-taking framework for policy-makers and enforcers of international and cybersecurity law
Cyber warfare is a reality taking on increasing importance. Governments, state-sponsored actors, and non-state sponsored actors have used...
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Iot traffic-based DDoS attacks detection mechanisms: A comprehensive review
The Internet of Things (IoT) has emerged as an inevitable part of human life, that includes online learning, smart homes, smart cars, smart grids,...
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A multi-layered security model to counter social engineering attacks: a learning-based approach
Social engineering is a malicious technique that leverages deception and manipulation to exploit the cognitive biases and heuristics of human...
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Ambiguity attacks on the digital image watermarking using discrete wavelet transform and singular value decomposition
In this paper, we present two ambiguity attacks on a watermarking algorithm based on discrete wavelet transform (DWT) and singular value...
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Trans-IFFT-FGSM: a novel fast gradient sign method for adversarial attacks
Deep neural networks (DNNs) are popular in image processing but are vulnerable to adversarial attacks, which makes their deployment in...
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Potential cyber threats of adversarial attacks on autonomous driving models
Autonomous Vehicles (CAVs) are currently seen as a viable alternative to traditional vehicles. However, CAVs will face serious cyber threats because...
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An integrated SDN framework for early detection of DDoS attacks in cloud computing
Cloud computing is a rapidly advancing technology with numerous benefits, such as increased availability, scalability, and flexibility. Relocating...
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Design optimization-based software-defined networking scheme for detecting and preventing attacks
In this paper, we design a Spider Monkey-based Elman Spike Neural Network (SM-ESNN) to identify intrusion threats in Software Defined Networks (SDN)....
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A systematic analysis of deep learning methods and potential attacks in internet-of-things surfaces
The usage of intelligent IoT devices is exponentially rising, and so the possibility of attacks in the IoT surfaces. The deep leaning algorithms are...
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Two-stage advanced persistent threat (APT) attack on an IEC 61850 power grid substation
Advanced Persistent Threats (APTs) are stealthy, multi-step attacks tailored to a specific target. Often described as ’low and slow’, APTs remain...
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GaTeBaSep: game theory-based security protocol against ARP spoofing attacks in software-defined networks
Nowadays, the growth of internet users has led to a significant increase in identity fraud security risks. One of the common forms of identity fraud...
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SDDA-IoT: storm-based distributed detection approach for IoT network traffic-based DDoS attacks
In the world of connected devices, there is huge growth of less secure Internet of Things (IoT) devices, and the ease of performing sophisticated...
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Towards the universal defense for query-based audio adversarial attacks on speech recognition system
Recently, studies show that deep learning-based automatic speech recognition (ASR) systems are vulnerable to adversarial examples (AEs), which add a...
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Formal verification for security and attacks in IoT physical layer
IoT devices are more important than ever. In a connected world, IoT devices have many uses. They are no longer merely used at work; they are part of...
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SeBROP: blind ROP attacks without returns
Currently, security-critical server programs are well protected by various defense techniques, such as Address Space Layout Randomization(ASLR),...
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Detection of cyber-attacks on smart grids using improved VGG19 deep neural network architecture and Aquila optimizer algorithm
This study introduces an innovative smart grid (SG) intrusion detection system, integrating Game Theory, swarm intelligence, and deep learning (DL)...
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Adversarial attacks against mouse- and keyboard-based biometric authentication: black-box versus domain-specific techniques
Adversarial attacks have recently gained popularity due to their simplicity, impact, and applicability to a wide range of machine learning scenarios....
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Vulnerabilities and attacks assessments in blockchain 1.0, 2.0 and 3.0: tools, analysis and countermeasures
Nowadays, blockchain has become increasingly popular due to its promise of supporting critical business services in various areas. Blockchain...
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Safety-critical computer vision: an empirical survey of adversarial evasion attacks and defenses on computer vision systems
Considering the growing prominence of production-level AI and the threat of adversarial attacks that can poison a machine learning model against a...
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A cyber defense system against phishing attacks with deep learning game theory and LSTM-CNN with African vulture optimization algorithm (AVOA)
Phishing attacks pose a significant threat to online security, utilizing fake websites to steal sensitive user information. Deep learning techniques,...
