A systematic literature review on phishing email detection using natural language processing techniques

S Salloum, T Gaber, S Vadera, K Shaalan - IEEE Access, 2022 - ieeexplore.ieee.org
Every year, phishing results in losses of billions of dollars and is a major threat to the Internet
economy. Phishing attacks are now most often carried out by email. To better comprehend …

[HTML][HTML] A systematic review on deep-learning-based phishing email detection

K Thakur, ML Ali, MA Obaidat, A Kamruzzaman - Electronics, 2023 - mdpi.com
Phishing attacks are a growing concern for individuals and organizations alike, with the
potential to cause significant financial and reputational damage. Traditional methods for …

A new English/Arabic parallel corpus for phishing emails

S Salloum, T Gaber, S Vadera, K Shaalan - ACM Transactions on Asian …, 2023 - dl.acm.org
Phishing involves malicious activity whereby phishers, in the disguise of legitimate entities,
obtain illegitimate access to the victims' personal and private information, usually through …

[HTML][HTML] The impact of artificial intelligence on organizational justice and project performance: A systematic literature and science mapping review

X Zhang, MF Antwi-Afari, Y Zhang, X Xing - Buildings, 2024 - mdpi.com
By adopting a systematic literature and science mapping review, this paper aims to explore
the impact of artificial intelligence (AI) on organizational justice and project performance. A …

[HTML][HTML] Data-driven comparison of federated learning and model personalization for electric load forecasting

F Widmer, S Nowak, B Bowler, P Huber… - Energy and AI, 2023 - Elsevier
Residential short-term electric load forecasting is essential in modern decentralized power
systems. Load forecasting methods mostly rely on neural networks and require access to …

An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach

MA Uddin, IH Sarker - arXiv preprint arXiv:2402.13871, 2024 - arxiv.org
Phishing email is a serious cyber threat that tries to deceive users by sending false emails
with the intention of stealing confidential information or causing financial harm. Attackers …

[PDF][PDF] Towards performance of NLP transformers on URL-based phishing detection for mobile devices

H Shirazi, K Hayne - International journal of ubiquitous systems and …, 2022 - par.nsf.gov
Hackers are increasingly launching phishing attacks via SMS and social media. Games and
dating apps introduce yet another attack vector. However, current deep learning-based …

Privacy-preserving spam filtering using homomorphic and functional encryption

T Nguyen, N Karunanayake, S Wang… - Computer …, 2023 - Elsevier
Conventional spam classification requires the end-users to reveal the content of incoming
emails to a classifier so that text analysis can be performed. On the other hand, new …

Federated phish bowl: LSTM-based decentralized phishing email detection

Y Sun, N Chong, H Ochiai - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
With increasingly more sophisticated phishing campaigns in recent years, phishing emails
lure people using more legitimate-looking personal contexts. To tackle this problem, instead …

Phishing Email Detection Using Inputs From Artificial Intelligence

M Paul, G Bartlett, J Mirkovic, M Freedman - arXiv preprint arXiv …, 2024 - arxiv.org
Enterprise security is increasingly being threatened by social engineering attacks, such as
phishing, which deceive employees into giving access to enterprise data. To protect both the …