Mesh Network Rethink for Crowded Environments

Decentralized network technology originally created for battlefields and burning man today it is being rethought from scratch.

Mesh networks– named for their fishnet-like connections – have emerged over the past few decades as a result of rigorous mathematical research about maintaining the data flow, even if parts system failure. But the theory did not always correspond to reality. Real world mesh networks found themselves vulnerable to outages in some the same settingsfor example, with certain types of large crowds, they must cope well with them.

So researchers from Johns Hopkins University, Harvardand City College of New York recently built a prototype mesh network a system that has been strengthened for some of the most challenging and hostile environments: political protests.

IN paper presented last week at ACM Conference on Computer and Communications Security V Taipeiresearchers announced a prototype mesh network called Friend. First, Amigo was designed to work in environments where Internet was disabled, as was seen during the riots in India, Iraq and Syriaamong other countries.

“Switching off the Internet during large civil protests is a way to prevent people from organizing and coming together,” says Tushar Joisassociate professor of the department electrical engineering at City College. “This is exactly what we are tailoring our technology for.”

Amigo offers at least three ways to support more traditional approaches to mesh networks. Recent Scholarship during network outages in protest scenarios, identifies issues such as network messages not being delivered, appearing out of order, and putting users at risk of being tracked, even when nodes in the network (such as phones running a mesh app) are close to each other. Researchers have found that penetrating high-level encrypted communications of a mesh network and at critical moments WiFi The operations identified opportunities that previous mesh networks had failed to take advantage of.

“History is cryptography We can’t be saved alone,” says Joyce. Joyce and his colleagues presented Amigo version of their article earlier this year on Real World Cryptography Conference in Sofia, Bulgaria.

Why political protests matter in mesh networks

Amigo learned key lessons from kit research about mesh networks in a number of recent political protests, including Hong Kong's pro-democracy activities in 2019 and 20.

For example, the way previous mesh networks handled the routing of their messages could inadvertently cause an area to become congested. Multiple nodes in a busy network may pump redundant messages into the network, causing communications to fail. In contrast, Amigo forms what researchers call dynamic “cliques”—where only designated leader nodes exchange messages with each other, while regular nodes simply talk to their leader. According to the researchers, this method significantly reduces message traffic, reducing the likelihood of network hang-ups.

“We're one of the people who discovered that we have this blind spot when it comes to secure messaging in a mesh network,” Joyce says. “So we proposed several new algorithms that will help eliminate this blind spot. Dynamic multicast routing essentially allows groups of nodes to independently organize routing units in a geographic area based on GPS.”

Another example is Amigo's approach to cryptography and anonymity. Previous mesh environments did not provide an easy way to remove members from encrypted groups. (Under protest, the group may need to be removed, for example because the device or its user has been detained by authorities.) Old grid standards have also leaked. metadata this may expose other group members. Amigo aims to correct both problems.

“One thing we talk about is the anonymity of outsiders,” Joyce says. “People outside your group don’t know the group exists.” Amigo is adding new algorithms to ensure the anonymity of outsiders and remove groups, he said. Joyce adds that Amigo aims to achieve these goals while maintaining the security of existing encrypted messaging networks such as WhatsApp and Signal.

Traditionally, Joyce adds, encrypted messages provide several important features. One of the functions involves protecting past messages: through “forward secrecy“, even if the keys are stolen today, past messages will still be safe. Another involves protecting future messages: through “security after compromise“, even a compromised system can be cured by generating new keys and thus depriving the attacker of the possibility of further communication. Amigo retains both functions.

“We are adding [our new protections] to classic forward secrecy and post-compromise security,” says Joyce. “But perhaps there are other properties that we need from a security point of view. So I guess juggling it will all be fun.”

Diogo BaradasAssociate Professor of Computer Science at the University of Waterloo Canadaadds that Amigo could have uses beyond political protests.

“Another scenario where these crowd dynamics are of particular interest include natural disaster scenarios such as floods, fires and earthquakes, where internet connectivity may become unavailable,” says Baradas, who is not part of the Amigo team. “And affected citizens, first responders and volunteers must coordinate to ensure an appropriate response.”

The developers built the Amigo mesh network using mathematical crowd models based on studies of real crowds. Cora Ruiz

Today's mesh networks know nothing about crowds

The latest real-world test of mesh networking standards comes from new research into how mesh networks handle crowds.

Cora Ruiz is a graduate student of Joyce Security, Privacy and Cryptography Lab at City College. She explored a random walk approach to crowd simulation in most mesh network environments.

Like the nitrogen and oxygen molecules in a sample of air, individual network nodes are now commonly everyone was assumed to follow random paths whose movements are not correlated with nearby nodes. If this is how mesh networks mathematically model crowd behavior, according to Ruiz, then no wonder Mesh networks are blocked in certain real-world environments.

“There’s really no understanding of how protesters physically move during these massive civil protests,” Ruiz says of traditional grid patterns of crowd behavior. “And without understanding how people move and what drives that movement, what that looks like at any level, it will be nearly impossible to develop a truly customized solution.”

So instead, Ruiz is exploring ways to embed models of what she calls psychological crowds into mesh network algorithms.

“A psychological crowd is a collection of people in one place who have a certain shared sense of self,” she says. “And this overall sense of self can directly influence how people move. They tend to move closer to each other. They don't tolerate as much distance between them. They move slower.”

Joyce says developing more realistic mathematical models of psychological crowds is an interdisciplinary effort. It's part math, part sociology and group activities. psychology. “[Ruiz’s] ongoing work aims to determine the dynamics of communication and [group] dynamics, going to protests of activists and journalists – to those places where internet shutdown are shared—and figure out what their needs are,” he says.

“Because the mesh is so heavily influenced by physical movement and traffic patterns,” adds Ruiz, “a deep understanding is key to the development of Amigo and other future mesh messaging tools.”

Joyce adds that Amigo took inspiration for its models from the crowd. document created in 2019 by Hong Kong pro-democracy protesters advising fellow activists on how to march and gather. From this and other studies it could help develop mathematical models from real crowd movementsAccording to Joyce, Amigo represents an important next step in bringing mesh networking to the real world.

“Our results show that some fundamental work is needed to create mesh networks,” says Joyce. “We can stand in our academic spaces and say, 'Well, this is what we think is necessary.' But until we get it from the source, we won't know.”