Entries Tagged "epidemiology"

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Thermal Imaging as Security Theater

Seems like thermal imaging is the security theater technology of today.

These features are so tempting that thermal cameras are being installed at an increasing pace. They’re used in airports and other public transportation centers to screen travelers, increasingly used by companies to screen employees and by businesses to screen customers, and even used in health care facilities to screen patients. Despite their prevalence, thermal cameras have many fatal limitations when used to screen for the coronavirus.

  • They are not intended for medical purposes.
  • Their accuracy can be reduced by their distance from the people being inspected.
  • They are “an imprecise method for scanning crowds” now put into a context where precision is critical.
  • They will create false positives, leaving people stigmatized, harassed, unfairly quarantined, and denied rightful opportunities to work, travel, shop, or seek medical help.
  • They will create false negatives, which, perhaps most significantly for public health purposes, “could miss many of the up to one-quarter or more people infected with the virus who do not exhibit symptoms,” as the New York Times recently put it. Thus they will abjectly fail at the core task of slowing or preventing the further spread of the virus.

Posted on May 28, 2020 at 6:50 AM • View Comments

Contact Tracing COVID-19 Infections via Smartphone Apps

Google and Apple have announced a joint project to create a privacy-preserving COVID-19 contact tracing app. (Details, such as we have them, are here.) It’s similar to the app being developed at MIT, and similar to others being described and developed elsewhere. It’s nice seeing the privacy protections; they’re well thought out.

I was going to write a long essay about the security and privacy concerns, but Ross Anderson beat me to it. (Note that some of his comments are UK-specific.)

First, it isn’t anonymous. Covid-19 is a notifiable disease so a doctor who diagnoses you must inform the public health authorities, and if they have the bandwidth they call you and ask who you’ve been in contact with. They then call your contacts in turn. It’s not about consent or anonymity, so much as being persuasive and having a good bedside manner.

I’m relaxed about doing all this under emergency public-health powers, since this will make it harder for intrusive systems to persist after the pandemic than if they have some privacy theater that can be used to argue that the whizzy new medi-panopticon is legal enough to be kept running.

Second, contact tracers have access to all sorts of other data such as public transport ticketing and credit-card records. This is how a contact tracer in Singapore is able to phone you and tell you that the taxi driver who took you yesterday from Orchard Road to Raffles has reported sick, so please put on a mask right now and go straight home. This must be controlled; Taiwan lets public-health staff access such material in emergencies only.

Third, you can’t wait for diagnoses. In the UK, you only get a test if you’re a VIP or if you get admitted to hospital. Even so the results take 1-3 days to come back. While the VIPs share their status on twitter or facebook, the other diagnosed patients are often too sick to operate their phones.

Fourth, the public health authorities need geographical data for purposes other than contact tracing – such as to tell the army where to build more field hospitals, and to plan shipments of scarce personal protective equipment. There are already apps that do symptom tracking but more would be better. So the UK app will ask for the first three characters of your postcode, which is about enough to locate which hospital you’d end up in.

Fifth, although the cryptographers – and now Google and Apple – are discussing more anonymous variants of the Singapore app, that’s not the problem. Anyone who’s worked on abuse will instantly realise that a voluntary app operated by anonymous actors is wide open to trolling. The performance art people will tie a phone to a dog and let it run around the park; the Russians will use the app to run service-denial attacks and spread panic; and little Johnny will self-report symptoms to get the whole school sent home.

I recommend reading his essay in full. Also worth reading are this EFF essay, and this ACLU white paper.

To me, the real problems aren’t around privacy and security. The efficacy of any app-based contact tracing is still unproven. A “contact” from the point of view of an app isn’t the same as an epidemiological contact. And the ratio of infections to contacts is high. We would have to deal with the false positives (being close to someone else, but separated by a partition or other barrier) and the false negatives (not being close to someone else, but contracting the disease through a mutually touched object). And without cheap, fast, and accurate testing, the information from any of these apps isn’t very useful. So I agree with Ross that this is primarily an exercise in that false syllogism: Something must be done. This is something. Therefore, we must do it. It’s techies proposing tech solutions to what is primarily a social problem.

EDITED TO ADD: Susan Landau on contact tracing apps and how they’re being oversold. And Farzad Mostashari, former coordinator for health IT at the Department of Health and Human Services, on contact tracing apps.

As long as 1) every contact does not result in an infection, and 2) a large percentage of people with the disease are asymptomatic and don’t realize they have it, I can’t see how this sort of app is valuable. If we had cheap, fast, and accurate testing for everyone on demand…maybe. But I still don’t think so.

EDITED TO ADD (4/15): More details from Apple and Google.

EDITED TO ADD (4/19): Apple and Google have strengthened the security and privacy of their system.

Posted on April 13, 2020 at 6:48 AM • View Comments

Emergency Surveillance During COVID-19 Crisis

Israel is using emergency surveillance powers to track people who may have COVID-19, joining China and Iran in using mass surveillance in this way. I believe pressure will increase to leverage existing corporate surveillance infrastructure for these purposes in the US and other countries. With that in mind, the EFF has some good thinking on how to balance public safety with civil liberties:

Thus, any data collection and digital monitoring of potential carriers of COVID-19 should take into consideration and commit to these principles:

  • Privacy intrusions must be necessary and proportionate. A program that collects, en masse, identifiable information about people must be scientifically justified and deemed necessary by public health experts for the purpose of containment. And that data processing must be proportionate to the need. For example, maintenance of 10 years of travel history of all people would not be proportionate to the need to contain a disease like COVID-19, which has a two-week incubation period.
  • Data collection based on science, not bias. Given the global scope of communicable diseases, there is historical precedent for improper government containment efforts driven by bias based on nationality, ethnicity, religion, and race­—rather than facts about a particular individual’s actual likelihood of contracting the virus, such as their travel history or contact with potentially infected people. Today, we must ensure that any automated data systems used to contain COVID-19 do not erroneously identify members of specific demographic groups as particularly susceptible to infection.
  • Expiration. As in other major emergencies in the past, there is a hazard that the data surveillance infrastructure we build to contain COVID-19 may long outlive the crisis it was intended to address. The government and its corporate cooperators must roll back any invasive programs created in the name of public health after crisis has been contained.
  • Transparency. Any government use of “big data” to track virus spread must be clearly and quickly explained to the public. This includes publication of detailed information about the information being gathered, the retention period for the information, the tools used to process that information, the ways these tools guide public health decisions, and whether these tools have had any positive or negative outcomes.
  • Due Process. If the government seeks to limit a person’s rights based on this “big data” surveillance (for example, to quarantine them based on the system’s conclusions about their relationships or travel), then the person must have the opportunity to timely and fairly challenge these conclusions and limits.

Posted on March 20, 2020 at 6:25 AM • View Comments

Work-from-Home Security Advice

SANS has made freely available its “Work-from-Home Awareness Kit.”

When I think about how COVID-19’s security measures are affecting organizational networks, I see several interrelated problems:

One, employees are working from their home networks and sometimes from their home computers. These systems are more likely to be out of date, unpatched, and unprotected. They are more vulnerable to attack simply because they are less secure.

Two, sensitive organizational data will likely migrate outside of the network. Employees working from home are going to save data on their own computers, where they aren’t protected by the organization’s security systems. This makes the data more likely to be hacked and stolen.

Three, employees are more likely to access their organizational networks insecurely. If the organization is lucky, they will have already set up a VPN for remote access. If not, they’re either trying to get one quickly or not bothering at all. Handing people VPN software to install and use with zero training is a recipe for security mistakes, but not using a VPN is even worse.

Four, employees are being asked to use new and unfamiliar tools like Zoom to replace face-to-face meetings. Again, these hastily set-up systems are likely to be insecure.

Five, the general chaos of “doing things differently” is an opening for attack. Tricks like business email compromise, where an employee gets a fake email from a senior executive asking him to transfer money to some account, will be more successful when the employee can’t walk down the hall to confirm the email’s validity—and when everyone is distracted and so many other things are being done differently.

Worrying about network security seems almost quaint in the face of the massive health risks from COVID-19, but attacks on infrastructure can have effects far greater than the infrastructure itself. Stay safe, everyone, and help keep your networks safe as well.

Posted on March 19, 2020 at 6:49 AM • View Comments

Security of Health Information

The world is racing to contain the new COVID-19 virus that is spreading around the globe with alarming speed. Right now, pandemic disease experts at the World Health Organization (WHO), the US Centers for Disease Control and Prevention (CDC), and other public-health agencies are gathering information to learn how and where the virus is spreading. To do so, they are using a variety of digital communications and surveillance systems. Like much of the medical infrastructure, these systems are highly vulnerable to hacking and interference.

That vulnerability should be deeply concerning. Governments and intelligence agencies have long had an interest in manipulating health information, both in their own countries and abroad. They might do so to prevent mass panic, avert damage to their economies, or avoid public discontent (if officials made grave mistakes in containing an outbreak, for example). Outside their borders, states might use disinformation to undermine their adversaries or disrupt an alliance between other nations. A sudden epidemic­—when countries struggle to manage not just the outbreak but its social, economic, and political fallout­—is especially tempting for interference.

In the case of COVID-19, such interference is already well underway. That fact should not come as a surprise. States hostile to the West have a long track record of manipulating information about health issues to sow distrust. In the 1980s, for example, the Soviet Union spread the false story that the US Department of Defense bioengineered HIV in order to kill African Americans. This propaganda was effective: some 20 years after the original Soviet disinformation campaign, a 2005 survey found that 48 percent of African Americans believed HIV was concocted in a laboratory, and 15 percent thought it was a tool of genocide aimed at their communities.

More recently, in 2018, Russia undertook an extensive disinformation campaign to amplify the anti-vaccination movement using social media platforms like Twitter and Facebook. Researchers have confirmed that Russian trolls and bots tweeted anti-vaccination messages at up to 22 times the rate of average users. Exposure to these messages, other researchers found, significantly decreased vaccine uptake, endangering individual lives and public health.

Last week, US officials accused Russia of spreading disinformation about COVID-19 in yet another coordinated campaign. Beginning around the middle of January, thousands of Twitter, Facebook, and Instagram accounts­—many of which had previously been tied to Russia­—had been seen posting nearly identical messages in English, German, French, and other languages, blaming the United States for the outbreak. Some of the messages claimed that the virus is part of a US effort to wage economic war on China, others that it is a biological weapon engineered by the CIA.

As much as this disinformation can sow discord and undermine public trust, the far greater vulnerability lies in the United States’ poorly protected emergency-response infrastructure, including the health surveillance systems used to monitor and track the epidemic. By hacking these systems and corrupting medical data, states with formidable cybercapabilities can change and manipulate data right at the source.

Here is how it would work, and why we should be so concerned. Numerous health surveillance systems are monitoring the spread of COVID-19 cases, including the CDC’s influenza surveillance network. Almost all testing is done at a local or regional level, with public-health agencies like the CDC only compiling and analyzing the data. Only rarely is an actual biological sample sent to a high-level government lab. Many of the clinics and labs providing results to the CDC no longer file reports as in the past, but have several layers of software to store and transmit the data.

Potential vulnerabilities in these systems are legion: hackers exploiting bugs in the software, unauthorized access to a lab’s servers by some other route, or interference with the digital communications between the labs and the CDC. That the software involved in disease tracking sometimes has access to electronic medical records is particularly concerning, because those records are often integrated into a clinic or hospital’s network of digital devices. One such device connected to a single hospital’s network could, in theory, be used to hack into the CDC’s entire COVID-19 database.

In practice, hacking deep into a hospital’s systems can be shockingly easy. As part of a cybersecurity study, Israeli researchers at Ben-Gurion University were able to hack into a hospital’s network via the public Wi-Fi system. Once inside, they could move through most of the hospital’s databases and diagnostic systems. Gaining control of the hospital’s unencrypted image database, the researchers inserted malware that altered healthy patients’ CT scans to show nonexistent tumors. Radiologists reading these images could only distinguish real from altered CTs 60 percent of the time­—and only after being alerted that some of the CTs had been manipulated.

Another study directly relevant to public-health emergencies showed that a critical US biosecurity initiative, the Department of Homeland Security’s BioWatch program, had been left vulnerable to cyberattackers for over a decade. This program monitors more than 30 US jurisdictions and allows health officials to rapidly detect a bioweapons attack. Hacking this program could cover up an attack, or fool authorities into believing one has occurred.

Fortunately, no case of healthcare sabotage by intelligence agencies or hackers has come to light (the closest has been a series of ransomware attacks extorting money from hospitals, causing significant data breaches and interruptions in medical services). But other critical infrastructure has often been a target. The Russians have repeatedly hacked Ukraine’s national power grid, and have been probing US power plants and grid infrastructure as well. The United States and Israel hacked the Iranian nuclear program, while Iran has targeted Saudi Arabia’s oil infrastructure. There is no reason to believe that public-health infrastructure is in any way off limits.

Despite these precedents and proven risks, a detailed assessment of the vulnerability of US health surveillance systems to infiltration and manipulation has yet to be made. With COVID-19 on the verge of becoming a pandemic, the United States is at risk of not having trustworthy data, which in turn could cripple our country’s ability to respond.

Under normal conditions, there is plenty of time for health officials to notice unusual patterns in the data and track down wrong information­—if necessary, using the old-fashioned method of giving the lab a call. But during an epidemic, when there are tens of thousands of cases to track and analyze, it would be easy for exhausted disease experts and public-health officials to be misled by corrupted data. The resulting confusion could lead to misdirected resources, give false reassurance that case numbers are falling, or waste precious time as decision makers try to validate inconsistent data.

In the face of a possible global pandemic, US and international public-health leaders must lose no time assessing and strengthening the security of the country’s digital health systems. They also have an important role to play in the broader debate over cybersecurity. Making America’s health infrastructure safe requires a fundamental reorientation of cybersecurity away from offense and toward defense. The position of many governments, including the United States’, that Internet infrastructure must be kept vulnerable so they can better spy on others, is no longer tenable. A digital arms race, in which more countries acquire ever more sophisticated cyberattack capabilities, only increases US vulnerability in critical areas such as pandemic control. By highlighting the importance of protecting digital health infrastructure, public-health leaders can and should call for a well-defended and peaceful Internet as a foundation for a healthy and secure world.

This essay was co-authored with Margaret Bourdeaux; a slightly different version appeared in Foreign Policy.

EDITED TO ADD: On last week’s squid post, there was a big conversation regarding the COVID-19. Many of the comments straddled the line between what are and aren’t the the core topics. Yesterday I deleted a bunch for being off-topic. Then I reconsidered and republished some of what I deleted.

Going forward, comments about the COVID-19 will be restricted to the security and risk implications of the virus. This includes cybersecurity, security, risk management, surveillance, and containment measures. Comments that stray off those topics will be removed. By clarifying this, I hope to keep the conversation on-topic while also allowing discussion of the security implications of current events.

Thank you for your patience and forbearance on this.

Posted on March 5, 2020 at 6:10 AM • View Comments

When Biology Becomes Software

All of life is based on the coordinated action of genetic parts (genes and their controlling sequences) found in the genomes (the complete DNA sequence) of organisms.

Genes and genomes are based on code—just like the digital language of computers. But instead of zeros and ones, four DNA letters—A, C, T, G—encode all of life. (Life is messy, and there are actually all sorts of edge cases, but ignore that for now.) If you have the sequence that encodes an organism, in theory, you could recreate it. If you can write new working code, you can alter an existing organism or create a novel one.

If this sounds to you a lot like software coding, you’re right. As synthetic biology looks more like computer technology, the risks of the latter become the risks of the former. Code is code, but because we’re dealing with molecules—and sometimes actual forms of life—the risks can be much greater.

Imagine a biological engineer trying to increase the expression of a gene that maintains normal gene function in blood cells. Even though it’s a relatively simple operation by today’s standards, it’ll almost certainly take multiple tries to get it right. Were this computer code, the only damage those failed tries would do is to crash the computer they’re running on. With a biological system, the code could instead increase the likelihood of multiple types of leukemias and wipe out cells important to the patient’s immune system.

We have known the mechanics of DNA for some 60-plus years. The field of modern biotechnology began in 1972 when Paul Berg joined one virus gene to another and produced the first “recombinant” virus. Synthetic biology arose in the early 2000s when biologists adopted the mindset of engineers; instead of moving single genes around, they designed complex genetic circuits.

In 2010, Craig Venter and his colleagues recreated the genome of a simple bacterium. More recently, researchers at the Medical Research Council Laboratory of Molecular Biology in Britain created a new, more streamlined version of E. coli. In both cases, the researchers created what could arguably be called new forms of life.

This is the new bioengineering, and it will only get more powerful. Today you can write DNA code in the same way a computer programmer writes computer code. Then you can use a DNA synthesizer or order DNA from a commercial vendor, and then use precision editing tools such as CRISPR to “run” it in an already existing organism, from a virus to a wheat plant to a person.

In the future, it may be possible to build an entire complex organism such as a dog or cat, or recreate an extinct mammoth (currently underway). Today, biotech companies are developing new gene therapies, and international consortia are addressing the feasibility and ethics of making changes to human genomes that could be passed down to succeeding generations.

Within the biological science community, urgent conversations are occurring about “cyberbiosecurity,” an admittedly contested term that exists between biological and information systems where vulnerabilities in one can affect the other. These can include the security of DNA databanks, the fidelity of transmission of those data, and information hazards associated with specific DNA sequences that could encode novel pathogens for which no cures exist.

These risks have occupied not only learned bodies—the National Academies of Sciences, Engineering, and Medicine published at least a half dozen reports on biosecurity risks and how to address them proactively—but have made it to mainstream media: genome editing was a major plot element in Netflix’s Season 3 of “Designated Survivor.”

Our worries are more prosaic. As synthetic biology “programming” reaches the complexity of traditional computer programming, the risks of computer systems will transfer to biological systems. The difference is that biological systems have the potential to cause much greater, and far more lasting, damage than computer systems.

Programmers write software through trial and error. Because computer systems are so complex and there is no real theory of software, programmers repeatedly test the code they write until it works properly. This makes sense, because both the cost of getting it wrong and the ease of trying again is so low. There are even jokes about this: a programmer would diagnose a car crash by putting another car in the same situation and seeing if it happened again.

Even finished code still has problems. Again due to the complexity of modern software systems, “works properly” doesn’t mean that it’s perfectly correct. Modern software is full of bugs—thousands of software flaws—that occasionally affect performance or security. That’s why any piece of software you use is regularly updated; the developers are still fixing bugs, even after the software is released.

Bioengineering will be largely the same: writing biological code will have these same reliability properties. Unfortunately, the software solution of making lots of mistakes and fixing them as you go doesn’t work in biology.

In nature, a similar type of trial and error is handled by “the survival of the fittest” and occurs slowly over many generations. But human-generated code from scratch doesn’t have that kind of correction mechanism. Inadvertent or intentional release of these newly coded “programs” may result in pathogens of expanded host range (just think swine flu) or organisms that wreck delicate ecological balances.

Unlike computer software, there’s no way so far to “patch” biological systems once released to the wild, although researchers are trying to develop one. Nor are there ways to “patch” the humans (or animals or crops) susceptible to such agents. Stringent biocontainment helps, but no containment system provides zero risk.

Opportunities for mischief and malfeasance often occur when expertise is siloed, fields intersect only at the margins, and when the gathered knowledge of small, expert groups doesn’t make its way into the larger body of practitioners who have important contributions to make.

Good starts have been made by biologists, security agencies, and governance experts. But these efforts have tended to be siloed, in either the biological and digital spheres of influence, classified and solely within the military, or exchanged only among a very small set of investigators.

What we need is more opportunities for integration between the two disciplines. We need to share information and experiences, classified and unclassified. We have tools among our digital and biological communities to identify and mitigate biological risks, and those to write and deploy secure computer systems.

Those opportunities will not occur without effort or financial support. Let’s find those resources, public, private, philanthropic, or any combination. And then let’s use those resources to set up some novel opportunities for digital geeks and bionerds—as well as ethicists and policy makers—to share experiences and concerns, and come up with creative, constructive solutions to these problems that are more than just patches.

These are overarching problems; let’s not let siloed thinking or funding get in the way of breaking down barriers between communities. And let’s not let technology of any kind get in the way of the public good.

This essay previously appeared on CNN.com.

EDITED TO ADD (9/23): Commentary.

Posted on September 13, 2019 at 11:40 AM • View Comments

President Obama Talks About AI Risk, Cybersecurity, and More

Interesting interview:

Obama: Traditionally, when we think about security and protecting ourselves, we think in terms of armor or walls. Increasingly, I find myself looking to medicine and thinking about viruses, antibodies. Part of the reason why cybersecurity continues to be so hard is because the threat is not a bunch of tanks rolling at you but a whole bunch of systems that may be vulnerable to a worm getting in there. It means that we’ve got to think differently about our security, make different investments that may not be as sexy but may actually end up being as important as anything.

What I spend a lot of time worrying about are things like pandemics. You can’t build walls in order to prevent the next airborne lethal flu from landing on our shores. Instead, what we need to be able to do is set up systems to create public health systems in all parts of the world, click triggers that tell us when we see something emerging, and make sure we’ve got quick protocols and systems that allow us to make vaccines a lot smarter. So if you take a public health model, and you think about how we can deal with, you know, the problems of cybersecurity, a lot may end up being really helpful in thinking about the AI threats.

Posted on October 20, 2016 at 6:16 AM • View Comments

Violence as a Contagious Disease

This is fascinating:

Intuitively we understand that people surrounded by violence are more likely to be violent themselves. This isn’t just some nebulous phenomenon, argue Slutkin and his colleagues, but a dynamic that can be rigorously quantified and understood.

According to their theory, exposure to violence is conceptually similar to exposure to, say, cholera or tuberculosis. Acts of violence are the germs. Instead of wracking intestines or lungs, they lodge in the brain. When people, in particular children and young adults whose brains are extremely plastic, repeatedly experience or witness violence, their neurological function is altered.

Cognitive pathways involving anger are more easily activated. Victimized people also interpret reality through perceptual filters in which violence seems normal and threats are enhanced. People in this state of mind are more likely to behave violently. Instead of through a cough, the disease spreads through fights, rapes, killings, suicides, perhaps even media, the researchers argue.

[…]

Not everybody becomes infected, of course. As with an infectious disease, circumstance is key. Social circumstance, especially individual or community isolation ­—people who feel there’s no way out for them, or disconnected from social norms ­—is what ultimately allows violence to spread readily, just as water sources fouled by sewage exacerbate cholera outbreaks.

At a macroscopic population level, these interactions produce geographic patterns of violence that sometimes resemble maps of disease epidemics. There are clusters, hotspots, epicenters. Isolated acts of violence are followed by others, which are followed by still more, and so on.

There are telltale incidence patterns formed as an initial wave of cases recedes, then is followed by successive waves that result from infected individuals reaching new, susceptible populations. “The epidemiology of this is very clear when you look at the math,” said Slutkin. “The density maps of shootings in Kansas City or New York or Detroit look like cholera case maps from Bangladesh.”

I am reminded of this paper on the effects of bystanders on escalating and de-escalating potentially violent situations.

Posted on January 28, 2013 at 6:07 AM • View Comments

Emotional Epidemiology

This, from The New England Journal of Medicine, sounds familiar:

This is the story line for most headline-grabbing illnesses—HIV, Ebola virus, SARS, typhoid. These diseases capture our imagination and ignite our fears in ways that more prosaic illnesses do not. These dramatic stakes lend themselves quite naturally to thriller books and movies; Dustin Hoffman hasn’t starred in any blockbusters about emphysema or dysentery.

When the inoculum of dramatic illness is first introduced into society, the public psyche rapidly becomes infected. Almost like an IgE-mediated histamine release, there is an immediate flooding of fear, even if the illness—like Ebola—is infinitely less likely to cause death than, say, a run-in with the Second Avenue bus. This immediate fear of the unknown was what had all my patients demanding the as-yet-unproduced H1N1 vaccine last spring.

As the novel disease establishes itself within society, a certain amount of emotional tolerance is created. H1N1 infection waxed and waned over the summer, and my patients grew less anxious. There was, of course, no medical basis for this decreased vigilance. Unusual risk groups and atypical seasonality should, in fact, have raised concern. By late summer, the perceived mysteriousness of H1N1 had receded, and the number of messages on my clinic phone followed suit.

But emotional epidemiology does not remain static. As autumn rolled around, I sensed a peeved expectation from my patients that this swine flu problem should have been solved already. The fact that it wasn’t “solved,” that the medical profession seemed somehow to be dithering, created an uneasy void. Not knowing whether to succumb to panic or to indifference, patients instead grew suspicious.

Posted on December 9, 2009 at 6:43 AM • View Comments

Computer Virus Epidemiology

“WiFi networks and malware epidemiology,” by Hao Hu, Steven Myers, Vittoria Colizza, and Alessandro Vespignani.

Abstract

In densely populated urban areas WiFi routers form a tightly interconnected proximity network that can be exploited as a substrate for the spreading of malware able to launch massive fraudulent attacks. In this article, we consider several scenarios for the deployment of malware that spreads over the wireless channel of major urban areas in the US. We develop an epidemiological model that takes into consideration prevalent security flaws on these routers. The spread of such a contagion is simulated on real-world data for georeferenced wireless routers. We uncover a major weakness of WiFi networks in that most of the simulated scenarios show tens of thousands of routers infected in as little as 2 weeks, with the majority of the infections occurring in the first 24–48 h. We indicate possible containment and prevention measures and provide computational estimates for the rate of encrypted routers that would stop the spreading of the epidemics by placing the system below the percolation threshold.

Honestly, I’m not sure I understood most of the article. And I don’t think that their model is all that great. But I like to see these sorts of methods applied to malware and infection rates.

EDITED TO ADD (3/13): Earlier—but free—version of the paper.

Posted on February 18, 2009 at 5:53 AM • View Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.