102 citations
- Wuhan UniversityCN2 papers
- Aalto UniversityFI1 paper
- Brown UniversityUS1 paper
- Concordia UniversityCA1 paper
- George Mason UniversityUS1 paper
- Guy's and St Thomas' NHS Foundation TrustGB1 paper
- Health TrustUS1 paper
- Imperial College Healthcare NHS TrustGB1 paper
- Indian Institute of Science BangaloreIN1 paper
- Institut National des Sciences Appliquées de ToulouseFR1 paper
- King's College Hospital NHS Foundation TrustGB1 paper
- King's College LondonGB1 paper
7 papers
Measuring Modern Phishing Tactics: A Quantitative Study of Body Obfuscation Prevalence, Co-occurrence, and Filter Impact
Antony Dalmiere, Zheng Zhou, Guillaume Auriol +2
Phishing attacks frequently use email body obfuscation to bypass detection filters, but quantitative insights into how techniques are combined and their impact on filter scores rem…
Retrofitting XoM for Stripped Binaries without Embedded Data Relocation
Chenke Luo, Jiang Ming, Mengfei Xie +2
In this paper, we present PXoM, a practical technique to seamlessly retrofit XoM into stripped binaries on the x86-64 platform. As handling the mixture of code and data is a well-k…
Localized synchronous patterns in weakly coupled bistable oscillators
Erik Bergland, Jason J Bramburger, Bjorn Sandstede
Motivated by numerical continuation studies of coupled mechanical oscillators, we investigate branches of localized time-periodic solutions of one-dimensional chains of coupled osc…
From Hardware Fingerprint to Access Token: Enhancing the Authentication on IoT Devices
Yue Xiao, Yi He, Xiaoli Zhang +5
The proliferation of consumer IoT products in our daily lives has raised the need for secure device authentication and access control. Unfortunately, these resource-constrained dev…
Bin Packing under Random-Order: Breaking the Barrier of 3/2
Anish Hebbar, Arindam Khan, K. V. N. Sreenivas
Best-Fit is one of the most prominent and practically used algorithms for the bin packing problem, where a set of items with associated sizes needs to be packed in the minimum numb…
Machine learning and glioma imaging biomarkers
Thomas Booth, Matthew Williams, Aysha Luis +3
Aim: To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring. Materials an…