Bio-inspired computational methods have gained popularity recently. These methods mimic the seemingly complex behavior of organisms to tackle difficult and often overwhelming problems. For example, algorithms have been inspired by honeybees’ flight patterns when searching for nectar, ants’ social foraging strategies, the evasive murmurations of birds and fish, and even the growth patterns of slime molds. By modeling these natural processes mathematically, researchers can develop innovative solutions to complex challenges.Bio-inspired computational methods have gained popularity recently. These methods mimic the seemingly complex behavior of organisms to tackle difficult and often overwhelming problems. For example, algorithms have been inspired by honeybees’ flight patterns when searching for nectar, ants’ social foraging strategies, the evasive murmurations of birds and fish, and even the growth patterns of slime molds. By modeling these natural processes mathematically, researchers can develop innovative solutions to complex challenges.[#item_full_content]

A team of faculty and students from George Mason University recently discovered a vulnerability in a widely used anonymization tool. They presented their findings last week in Taiwan at the Association for Computing Machinery Conference on Computer and Communications Security (ACM CCS 2025). The paper is available on the arXiv preprint server.A team of faculty and students from George Mason University recently discovered a vulnerability in a widely used anonymization tool. They presented their findings last week in Taiwan at the Association for Computing Machinery Conference on Computer and Communications Security (ACM CCS 2025). The paper is available on the arXiv preprint server.[#item_full_content]