This year WiSec continues the effort pioneered in 2017, towards supporting greater “reproducibility” in mobile and wireless security experimental research. The goal of this process is to increase the impact of mobile and wireless security research, enable dissemination of research results, code and experimental setups, and to enable the research community to build on prior experimental results. We recognize papers whose experimental results were replicated by an independent committee and provide a “replicability label” accordance to the terminology defined by ACM.
Authors of accepted papers can participate in this voluntary process by submitting supporting evidence of their experiments’ replicability, following the instructions below. Authors are encouraged to plan ahead when running their experiments, in order to minimise the overhead of applying for this label.
To apply for the Replicability label, the authors must:
- Prepare a VirtualBox VM with all data/tools installed. It is expected that the authors include within this VM raw data (without any pre-processing) and all the scripts used for pre-processing.
- For each graph/table, provide a directory (Fig_XXX, Table_XXX) which contains a script that enables the committee to regenerate that object.
- Include in the home directory a readme file, according to the following format. The authors can use the following script to generate information about the configuration of the machine that was used for the experiments.
- Provide a link to downloading the VM (e.g, google drive or dropbox), or request credentials to upload the VM to the conference storage system.
- Submit a request on easychair and include a link within the abstract to your VM. [Deadline: April 9, 2019 AOE]
If the committee can verify that all relevant data sets were included and the graphs/tables can be regenerated based on this, the committee will grant a Replicability Label and also provide a report on the regeneration process.
2019 Replicability Committee:
Aanjhan Ranganathan (co-chair), Northeastern
Giovanni Camurati, EURECOM
Guevara Noubir, Northeastern
Hongyu Jin, KTH
Mohammad Khodaei, KTH
Panos Papadimatros (co-chair), KTH
Paul Patras, University of Edinburg
Sashank Narain, Northeastern
The authors uploaded a VM containing all the necessary data and code required to replicate the results. This year, we asked at least two reviewers to replicate the results for each submission. We ensured that the VMs are self contained to the maximum extent possible to eliminate any future version deprecation and backward compatibility issues. The reviewers clarified any issues directly with the authors and in some cases resulted in code updates.
The 2019 VMs will be made available as always on wisecdata.ccs.neu.edu by end of the month.
- Jiska Classen and Matthias Hollick. Inside Job: Diagnosing Bluetooth Lower Layers Using Off-the-Shelf Devices
- Raveen Wijewickrama, Anindya Maiti and Murtuza Jadliwala. deWristified: Handwriting Inference Using Wrist-Based Motion Sensors Revisited
- Mohammad Khodaei, Hamid Noroozi and Panos Papadimitratos. Scaling Pseudonymous Authentication for Large Mobile Systems