  Although online handwriting verification has made great progress recently,
the verification performances are still far behind the real usage owing to the
small scale of the datasets as well as the limited biometric mediums.
Therefore, this paper proposes a new handwriting verification benchmark dataset
named Multimodal Signature and Digit String (MSDS), which consists of two
subsets: MSDS-ChS (Chinese Signatures) and MSDS-TDS (Token Digit Strings),
contributed by 402 users, with 20 genuine samples and 20 skilled forgeries per
user per subset. MSDS-ChS consists of handwritten Chinese signatures, which, to
the best of our knowledge, is the largest publicly available Chinese signature
dataset for handwriting verification, at least eight times larger than existing
online datasets. Meanwhile, MSDS-TDS consists of handwritten Token Digit
Strings, i.e, the actual phone numbers of users, which have not been explored
yet. Extensive experiments with different baselines are respectively conducted
for MSDS-ChS and MSDS-TDS. Surprisingly, verification performances of
state-of-the-art methods on MSDS-TDS are generally better than those on
MSDS-ChS, which indicates that the handwritten Token Digit String could be a
more effective biometric than handwritten Chinese signature. This is a
promising discovery that could inspire us to explore new biometric traits. The
MSDS dataset is available at https://github.com/HCIILAB/MSDS.
