most citedAuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms

4 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

ClearMark: Intuitive and Robust Model Watermarking via Transposed Model Training

Torsten Krauß, Jasper Stang, Alexandra Dmitrienko

Due to costly efforts during data acquisition and model training, Deep Neural Networks (DNNs) belong to the intellectual property of the model creator. Hence, unauthorized use, the…

cs.CR2023

TorMult: Introducing a Novel Tor Bandwidth Inflation Attack

Christoph Sendner, Jasper Stang, Alexandra Dmitrienko +2

The Tor network is the most prominent system for providing anonymous communication to web users, with a daily user base of 2 million users. However, since its inception, it has bee…

cs.CR20234 cited

G-Scan: Graph Neural Networks for Line-Level Vulnerability Identification in Smart Contracts

Christoph Sendner, Ruisi Zhang, Alexander Hefter +2

Due to the immutable and decentralized nature of Ethereum (ETH) platform, smart contracts are prone to security risks that can result in financial loss. While existing machine lear…

cs.CR20231 cited

Metadata-based Malware Detection on Android using Machine Learning

Alexander Hefter, Christoph Sendner, Alexandra Dmitrienko

In the digitized world, smartphones and their apps play an important role. To name just a few examples, some apps offer possibilities for entertainment, others for online banking,…

cs.CR20234 cited

AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms

Hossein Fereidooni, Jan König, Phillip Rieger +5

Mobile applications are widely used for online services sharing a large amount of personal data online. One-time authentication techniques such as passwords and physiological biome…