Rethinking mesh networks for crowded environments

A decentralized networking technology originally created for battlefields and Burning Man is being reinvented from the ground up today.

Mesh networks—named for their fishnet-like connections—have emerged over the past few decades as rigorous, mathematical Research Keeping data flowing even when fractions of a system failureBut theory doesn’t always match reality. real world mesh network have proven sensitive to shutdowns in some absolutely settingsAs such they must be good at handling certain types of large crowds.

So researchers at Johns Hopkins University, Harvard, and the City College of New York recently created a prototype mesh networking system that is hardened for some of the most challenging and hostile environments around: political protests.

one in paper Presented at ACM last week Conference on Computer and Communications Security In Taipei, researchers announced a prototype mesh network called Amigo. For starters, Amigo is designed to work in environments where the internet has been shut down, as was seen during the unrest India, Iraq and Syriaamong other countries.

“Shutting down the internet during times of great civil protest is a way to prevent people from organizing and coming together,” says Tushar JoisAssistant Professor of Electrical Engineering at City College. “That’s what we’re designing our technology specifically for.”

Amigo has proposed at least three ways to strengthen the more traditional approach to mesh networks. Recent Scholarship Mesh outages in conflict scenarios lead to problems such as network messages not being delivered, appearing out of order, and putting users at risk of being traced – even when nodes in the network (e.g. phones running Mesh apps) are right next to each other. The researchers found that digging beneath the high-level, encrypted communications and nuts-and-bolts Wi-Fi operations of mesh networks has revealed opportunities that previous mesh networks had failed to capture.

“The story is that cryptography alone will not save us,” says Joyce. Joyce and colleagues presented version of his amigo paper earlier this year Real World Cryptography Conference In Sofia, Bulgaria.

Why does political opposition matter in mesh networks?

amigo key lessons learned from a set of studies A series of recent political protests over mesh networking—including Hong Kong’s pro-democracy activities in 2019 and ’20,

For example, how previous mesh networks handled the routing of their messages could lead to an area being accidentally flooded. Multiple nodes in a stressed network may pump unnecessary messages into the network, disrupting communications. In contrast, Amigo creates what researchers call dynamic “cliques” – where only designated leader nodes exchange messages with each other, while regular nodes only talk to their leader. Researchers say this technology significantly reduces message traffic, reducing the chances of being captured by the network.

“We’re one of the people that figured out that we found this blind spot in secure mesh messaging,” says Joyce. “So we proposed some new algorithms that help address this blind spot. Dynamic click routing basically allows groups of nodes to self-organize routing units across a geographic area based on GPS.”

Another example is Amigo’s approach to cryptography and anonymity. Previous mesh environments did not provide any easy way to remove members from encrypted groups. (For example, in a protest setting, it may be necessary to delete a group because a device or its user has been captured by authorities.) Older mesh standards also leaked metadata that could reveal other members of the group. Amigo aims to fix both problems.

“One thing we talk about is the anonymity of outsiders,” says Joyce. “People who are outside your group don’t know the group exists.” He says Amigo adds new algorithms to ensure anonymity and removal of outsiders to the group. Joyce says Amigo aims to achieve these goals while maintaining the security of existing encrypted-messaging networks like WhatsApp and Signal.

Traditionally, encrypted messaging offers some important features, says Joyce. One feature includes protection of previous messages: “through”further confidentiality“Even if the keys are stolen today, past messages are still protected. The second involves the protection of future messages: via “post-agreement security“Even a compromised system can be recovered by generating new keys and thus locking an intruder out of future communications. Amigo retains both features.

“We add (our new security) to classic forward privacy and post-compromise security,” says Joyce. “But maybe from a security standpoint we need even more properties. So I think it would be fun to add all of those.”

diogo bardasan assistant professor of computer science at the University of Waterloo in Canada, says Amigo may find applications beyond political protest.

“Another scenario where such crowd dynamics are of particular interest includes natural disaster scenarios – such as floods, fires and earthquakes – where Internet communications may be unavailable,” says Baradas, who is not on the Amigo team. “And affected citizens, first-responders and volunteers must coordinate to ensure an appropriate response.”

The developers built the Amigo Mesh network around a mathematical model of crowds that is based on studies of real-world crowds. Cora Ruiz

Today’s mesh networks know nothing about congestion

A final, real-world reality check on mesh standards has emerged from a new study of how mesh networks handle congestion.

Cora Ruiz Joyce is a graduate student at Security, Privacy and Cryptographic Engineering Lab In City College. She is investigating a “random walk” style approach to modeling congestion in most mesh network environments.

Like the nitrogen and oxygen molecules in an air sample, today individual mesh nodes are typically Each trace visualized the random path Whose motions are uncorrelated with those of nearby nodes. If this is the case, Ruiz says, then how do mesh networks mathematically model the behavior of crowds? no surprise Mesh networks become pervasive in some real-world environments.

“There’s really no understanding of the way protesters are physically moving in these large civic protests,” Ruiz says of the traditional trap model of crowd behavior. “And without an understanding of what makes people move and what drives movement, what it looks like at any level, it will be almost impossible to develop truly tailored solutions.”

So instead, Ruiz is looking for ways to bring models of what she calls psychological crowds into mesh network algorithms.

She says, “Psychological crowding is a gathering of people in one place who have a certain shared sense of self.” “And that shared sense of self can directly impact the way people move. They move closer to each other. They don’t tolerate much distance between each other. They move slower.”

Joyce says that developing more realistic mathematical models of psychological crowds is an interdisciplinary effort. It’s one part mathematics, and it’s one part sociology and group psychology. He says, “[Ruiz’s]current work is about going to protest activists and journalists to determine communication dynamics and (group) dynamics – in these places where Internet shutdowns are common – and finding out what their needs are.”

“Since Mesh is so heavily influenced by physical activity and traffic patterns,” Ruiz says, “it is important to have a strong understanding of what Amigo and other future Mesh messaging tools can do moving forward.”

Joyce says Amigo served as inspiration for his crowd models document Created in 2019 by Hong Kong pro-democracy protesters, advising fellow activists to march and gather. more than that further studies he can Help develop mathematical models Of Real-world crowd activitiesJoyce says Amigo represents an important next step toward bringing mesh networks into the real world.

“Our results show that some fundamental functions are essential in mesh networking,” says Joyce. “We can stand up in our academic spaces and say, ‘Oh OK, this is what we think is necessary.’ “But until we get it from the source, we don’t know.”