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Found 10 papers, 1 papers with code
Deep Learning-Based Speech and Vision Synthesis to Improve Phishing Attack Detection through a Multi-layer Adaptive Framework
The ever-evolving ways attacker continues to im prove their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of current approaches to detect complex phishing attack.
An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system.
LOCALINTEL: Generating Organizational Threat Intelligence from Global and Local Cyber Knowledge
In this work, we present LOCALINTEL, a novel automated knowledge contextualization system that, upon prompting, retrieves threat reports from the global threat repositories and uses its local knowledge database to contextualize them for a specific organization.
Use of Graph Neural Networks in Aiding Defensive Cyber Operations
In an increasingly interconnected world, where information is the lifeblood of modern society, regular cyber-attacks sabotage the confidentiality, integrity, and availability of digital systems and information.
Knowledge-enhanced Neuro-Symbolic AI for Cybersecurity and Privacy
Neuro-Symbolic Artificial Intelligence (AI) is an emerging and quickly advancing field that combines the subsymbolic strengths of (deep) neural networks and explicit, symbolic knowledge contained in knowledge graphs to enhance explainability and safety in AI systems.
Generating Fake Cyber Threat Intelligence Using Transformer-Based Models
We evaluate with traditional approaches and conduct a human evaluation study with cybersecurity professionals and threat hunters.
Independent Component Analysis for Trustworthy Cyberspace during High Impact Events: An Application to Covid-19
Social media has become an important communication channel during high impact events, such as the COVID-19 pandemic.
NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion
In this paper, we show that even if we build a classifier and train it with adversarial examples for network data, we can use adversarial attacks and successfully break the system.
RelExt: Relation Extraction using Deep Learning approaches for Cybersecurity Knowledge Graph Improvement
A cybersecurity knowledge graph can be paramount in aiding a security analyst to detect cyber threats because it stores a vast range of cyber threat information in the form of semantic triples which can be queried.
Kernelized Weighted SUSAN based Fuzzy C-Means Clustering for Noisy Image Segmentation
The paper proposes a novel Kernelized image segmentation scheme for noisy images that utilizes the concept of Smallest Univalue Segment Assimilating Nucleus (SUSAN) and incorporates spatial constraints by computing circular colour map induced weights.
