Distributed denial of service attack prediction: Challenges, open issues and opportunities
Abstract Distributed Denial of Service (DDoS) attack is one of the biggest cyber threats.
DDoS attacks have evolved in quantity and volume to evade detection and increase …
DDoS attacks have evolved in quantity and volume to evade detection and increase …
Event prediction in the big data era: A systematic survey
L Zhao - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …
either our society or the nature, such as earthquakes, civil unrest, system failures …
LSTM-BA: DDoS detection approach combining LSTM and Bayes
Y Li, Y Lu - … international conference on advanced cloud and …, 2019 - ieeexplore.ieee.org
The development of cyberspace brings both opportunities and threats, among which
Distributed Denial of Service (DDoS) is one of the most destructive attacks. A mass of DDoS …
Distributed Denial of Service (DDoS) is one of the most destructive attacks. A mass of DDoS …
Introducing a new dataset for event detection in cybersecurity texts
HMD Trong, DT Le, APB Veyseh… - Proceedings of the …, 2020 - aclanthology.org
Detecting cybersecurity events is necessary to keep us informed about the fast growing
number of such events reported in text. In this work, we focus on the task of event detection …
number of such events reported in text. In this work, we focus on the task of event detection …
[HTML][HTML] A social network of crime: A review of the use of social networks for crime and the detection of crime
Social media is used to commit and detect crimes. With automated methods, it is possible to
scale both crime and detection of crime to a large number of people. The ability of criminals …
scale both crime and detection of crime to a large number of people. The ability of criminals …
Review of NLP-based systems in digital forensics and cybersecurity
DO Ukwen, M Karabatak - 2021 9th International symposium …, 2021 - ieeexplore.ieee.org
Over the years, there is an increase in the use of Artificial Intelligence (AI) by digital forensics
and cybersecurity professionals to combat cybercrime. Natural Language Processing (NLP) …
and cybersecurity professionals to combat cybercrime. Natural Language Processing (NLP) …
Differentiating and predicting cyberattack behaviors using lstm
I Perry, L Li, C Sweet, SH Su, FY Cheng… - … IEEE Conference on …, 2018 - ieeexplore.ieee.org
Classifying and predicting cyberattack behaviors are outstanding challenges due to the
changing and broad attack surfaces as attackers penetrate into enterprise networks. The rise …
changing and broad attack surfaces as attackers penetrate into enterprise networks. The rise …
[PDF][PDF] A comprehensive tutorial and survey of applications of deep learning for cyber security
A Comprehensive Tutorial and Survey of Applications of Deep Learning for Cyber Security
Page 1 P osted on 5 Jan 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech rxiv.11473377.v1 …
Page 1 P osted on 5 Jan 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech rxiv.11473377.v1 …
Event evolution model for cybersecurity event mining in tweet streams
X Liu, J Fu, Y Chen - Information Sciences, 2020 - Elsevier
The rich source of online reports and discussions on social media can be leveraged to
investigate the widespread cyber-attacks. In this paper, we study the problem of …
investigate the widespread cyber-attacks. In this paper, we study the problem of …
[PDF][PDF] Event Prediction in Big Data Era: A Systematic Survey. arXiv preprint
L Zhao - ArXivorg, 2020 - par.nsf.gov
Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …
either our society or the nature, such as earthquakes, civil unrest, system failures …