By Kevin Lee, Ben Kaiser, Jonathan Mayer, and Arvind Narayanan In January, we released a study showing the ease of SIM swaps at five U.S. prepaid carriers. These attacks—in which an adversary tricks telecoms into moving the victim’s phone number to a new SIM card under the attacker’s control—divert calls and SMS text messages away […]
Building a Bridge with Concrete… Examples
Thanks to Annette Zimmermann and Arvind Narayanan for their helpful feedback on this post. Algorithmic bias is currently generating a lot of lively public and scholarly debate, especially amongst computer scientists and philosophers. But do these two groups really speak the same language—and if not, how can they start to do so? I noticed at […]
The CheapBit of Fitness Trackers Apps
Yan Shvartzshnaider (@ynotez) and Madelyn Sanfilippo (@MrsMRS_PhD) Fitness trackers are “[devices] that you can wear that records your daily physical activity, as well as other information about your health, such as your heart rate” [Oxford Dictionary]. The increasing popularity of wearable devices offered by Apple, Google, Nike inadvertently led cheaper versions to flood the market, […]
Ballot-level comparison audits: BMD
In my previous posts, I’ve been discussing ballot-level comparison audits, a form of risk-limiting audit. Ballots are imprinted with serial numbers (after they leave the voter’s hands); during the audit, a person must find a particular numbered ballot in a batch of a thousand (more or less). With CCOS (central-count optical scan) this works fine: […]
Finding a randomly numbered ballot
In my previous posts, I’ve been discussing ballot-level comparison audits, a form of risk-limiting audit. Ballots are imprinted with serial numbers (after they leave the voter’s hands); during the audit, a person must find a particular numbered ballot in a batch of a thousand (more or less). If the ballot papers are numbered consecutively, that’s […]