Benny Pinkas (Bar-Ilan University); Eyal Ronen (Tel Aviv University)

In recent months multiple proposals for contact tracing schemes for combating the spread of COVID-19 have been published. Many of those proposals try to implement this functionality in a decentralized and privacy-preserving manner using Bluetooth Low Energy (BLE).

In this paper, we present “Hashomer”, our proposal for a contact tracing scheme tailored for the Israeli Ministry of Health’s (MoH) “Hamagen” application. The design is fully decentralized, and has the following properties:

- Message Unlinkability — Different BLE messages sent by the same user cannot be linked to each other (except for messages sent by COVID-19 positive users who give consent to tracing their contacts, and only for messages sent within a short time period).

- Explainability — To convince users that they were exposed to a COVID-19 positive person, we let them learn the approximate time of contact. This also implies that users can potentially learn, using the phone’s GPS information, the location of the exposure.

- Partial Disclosure and Coercion Prevention — Users and the MoH are able to redact tracing information and exposure notifications for specific time intervals.

- Prevention of Relay Attacks – The design prevents attacks where a malicious receiver relays BLE transmissions from one location to other locations.

- Proof of exposure to a COVID-19 positive person — To prevent false reports about exposure, we allow users who are notified by the application about an exposure to a COVID-19 positive person, to prove this fact to the server.

- Identity Commitment — To prevent malicious changing or replacing keys, we bind the BLE messages to a unique ID in a privacy-preserving way.

- Performance — BLE payload size is limited to 16 bytes. The application uses only symmetric key cryptography (AES and HMAC). To reduce bandwidth, contact updates from the MoH are of limited size. Moreover, the local search for exposure is linear in the number of messages and number of COVID-19 positive persons

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 51 [1] => 47 ) ) ) [post__not_in] => Array ( [0] => 7347 ) )

Towards Understanding and Detecting Cyberbullying in Real-world Images

Nishant Vishwamitra (University at Buffalo), Hongxin Hu (University at Buffalo), Feng Luo (Clemson University), Long Cheng (Clemson University)

Read More

Ovid: Message-based Automatic Contact Tracing

Leonie Reichert and Samuel Brack (Humboldt University of Berlin); Björn Scheuermann (Humboldt-University of Berlin)

Read More

WINNIE : Fuzzing Windows Applications with Harness Synthesis and...

Jinho Jung (Georgia Institute of Technology), Stephen Tong (Georgia Institute of Technology), Hong Hu (Pennsylvania State University), Jungwon Lim (Georgia Institute of Technology), Yonghwi Jin (Georgia Institute of Technology), Taesoo Kim (Georgia Institute of Technology)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)