Published By: Phys.org, 1/30/2017 (university press release)

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Summary

Researchers from Tel Aviv University and Ben-Gurion University have developed new software that will allow smartwatches to verify handwritten signatures. This software monitors the movement of the entire wrist in order to catch attempts at forgery, by identifying movements that do not match the movements of the original owner. The goal of this software is to reduce acts of forgery.

Flesch-Kincaid Grade Level of Article: 12

Extended Discussion Questions

• In practice, do you think this type of signature-verification technology will live up to the researchers’ expectations?
  • How complex would it be to use in a real-world transaction? (Prompts: Who would provide the smartwatch? How? Could there be security problems if the data comes from the customer’s smartwatch?)
  • How are these complexities different from using a tablet by itself?
  • How could using this technology in practice be simplified?
• What do you think the public reaction might be to this new signature verification method?
• What are some other potential issues or limitations for this new software?
  • Do you think it could ever be 100% reliable? What errors or problems might occur?
  • Is there any way it could do more harm than good? Why or why not?
• In addition to fighting forgery, are there other benefits that could arise from this new technology?

Relating This Story to the CSP Curriculum Framework

Global Impact Learning Objectives:

• LO 7.3.1 Analyze the beneficial and harmful effects of computing.
• LO 7.4.1 Explain the connections between computing and real-world contexts, including economic, social, and cultural contexts.

Global Impact Essential Knowledge:

• EK 7.3.1A Innovations enabled by computing raise legal and ethical concerns.
• EK 7.3.1G Privacy and security concerns arise in the development and use of computational systems and artifacts.

Banner Image: “Network Visualization – Violet – Offset Crop”, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0