[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions

R Kaur, D Gabrijelčič, T Klobučar - Information Fusion, 2023 - Elsevier
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …

Cyber threat intelligence mining for proactive cybersecurity defense: a survey and new perspectives

N Sun, M Ding, J Jiang, W Xu, X Mo… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Today's cyber attacks have become more severe and frequent, which calls for a new line of
security defenses to protect against them. The dynamic nature of new-generation threats …

Trustworthy LLMs: A survey and guideline for evaluating large language models' alignment

Y Liu, Y Yao, JF Ton, X Zhang, RGH Cheng… - arXiv preprint arXiv …, 2023 - arxiv.org
Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …

Data-driven cybersecurity incident prediction: A survey

N Sun, J Zhang, P Rimba, S Gao… - … surveys & tutorials, 2018 - ieeexplore.ieee.org
Driven by the increasing scale and high profile cybersecurity incidents related public data,
recent years we have witnessed a paradigm shift in understanding and defending against …

Survey of attack projection, prediction, and forecasting in cyber security

M Husák, J Komárková, E Bou-Harb… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
This paper provides a survey of prediction, and forecasting methods used in cyber security.
Four main tasks are discussed first, attack projection and intention recognition, in which …

A search engine backed by Internet-wide scanning

Z Durumeric, D Adrian, A Mirian, M Bailey… - Proceedings of the …, 2015 - dl.acm.org
Fast Internet-wide scanning has opened new avenues for security research, ranging from
uncovering widespread vulnerabilities in random number generators to tracking the evolving …

When does machine learning {FAIL}? generalized transferability for evasion and poisoning attacks

O Suciu, R Marginean, Y Kaya, H Daume III… - 27th USENIX Security …, 2018 - usenix.org
Recent results suggest that attacks against supervised machine learning systems are quite
effective, while defenses are easily bypassed by new attacks. However, the specifications for …

Application of ethnobotanical indices to document the use of plants in traditional medicines in Rawalpindi district, Punjab-Pakistan

H Zareef, MT Gul, R Qureshi, H Aati… - Ethnobotany …, 2023 - ethnobotanyjournal.org
Background. Ethnobotanical studies report the customary uses of plants used by the local
communities across the world. The goal of present study was to census the ethno-medicinal …

A survey on systems security metrics

M Pendleton, R Garcia-Lebron, JH Cho… - ACM Computing Surveys …, 2016 - dl.acm.org
Security metrics have received significant attention. However, they have not been
systematically explored based on the understanding of attack-defense interactions, which …

Tiresias: Predicting security events through deep learning

Y Shen, E Mariconti, PA Vervier… - Proceedings of the 2018 …, 2018 - dl.acm.org
With the increased complexity of modern computer attacks, there is a need for defenders not
only to detect malicious activity as it happens, but also to predict the specific steps that will …