Entries Tagged "privacy"

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Security Applications of Time-Reversed Acoustics

I simply don’t have the science to evaluate this claim:

Since conventional sound waves disperse when traveling through a medium, the possibility of focusing sound waves could have applications in several areas. In cryptography, for example, when sending a secret message, the sender could ensure that only one location would receive the message. Interceptors at other locations would only pick up noise due to unfocused waves. Other potential uses include antisubmarine warfare and underwater communications that benefit from targeted signaling.

Posted on April 5, 2006 at 1:06 PM • View Comments

80 Cameras for 2,400 People

This story is about the remote town of Dillingham, Alaska, which is probably the most watched town in the country. There are 80 surveillance cameras for the 2,400 people, which translates to one camera for every 30 people.

The cameras were bought, I assume, because the town couldn’t think of anything else to do with the $202,000 Homeland Security grant they received. (One of the problems of giving this money out based on political agenda, rather than by where the actual threats are.)

But they got the money, and they spent it. And now they have to justify the expense. Here’s the movie-plot threat the Dillingham Police Chief uses to explain why the expense was worthwhile:

“Russia is about 800 miles that way,” he says, arm extending right.

“Seattle is about 1,200 miles back that way.” He points behind him.

“So if I have the math right, we’re closer to Russia than we are to Seattle.”

Now imagine, he says: What if the bad guys, whoever they are, manage to obtain a nuclear device in Russia, where some weapons are believed to be poorly guarded. They put the device in a container and then hire organized criminals, “maybe Mafiosi,” to arrange a tramp steamer to pick it up. The steamer drops off the container at the Dillingham harbor, complete with forged paperwork to ship it to Seattle. The container is picked up by a barge.

“Ten days later,” the chief says, “the barge pulls into the Port of Seattle.”

Thompson pauses for effect.

“Phoooom,” he says, his hands blooming like a flower.

The first problem with the movie plot is that it’s just plain silly. But the second problem, which you might have to look back to notice, is that those 80 cameras will do nothing to stop his imagined attack.

We are all security consumers. We spend money, and we expect security in return. This expenditure was a waste of money, and as a U.S. taxpayer, I am pissed that I’m getting such a lousy deal.

Posted on March 29, 2006 at 1:13 PM • View Comments

Firefox Bug Causes Relationship to Break Up

A couple—living together, I assume—and engaged to be married, shared a computer. He used Firefox to visit a bunch of dating sites, being smart enough not to have the browser save his password. But Firefox did save the names of the sites it was told never to save the password for. She happened to stumble on this list. The details are left to the imagination, but they broke up.

Most bug reports aren’t this colorful.

Posted on March 27, 2006 at 7:53 AM • View Comments

DHS Privacy and Integrity Report

Last year, the Department of Homeland Security finally got around to appointing its DHS Data Privacy and Integrity Advisory Committee. It was mostly made up of industry insiders instead of anyone with any real privacy experience. (Lance Hoffman from George Washington University was the most notable exception.)

And now, we have something from that committee. On March 7th they published their “Framework for Privacy Analysis of Programs, Technologies, and Applications.”

This document sets forth a recommended framework for analyzing programs, technologies, and applications in light of their effects on privacy and related interests. It is intended as guidance for the Data Privacy and Integrity Advisory Committee (the Committee) to the U.S. Department of Homeland Security (DHS). It may also be useful to the DHS Privacy Office, other DHS components, and other governmental entities that are seeking to reconcile personal data-intensive programs and activities with important social and human values.

It’s surprisingly good.

I like that it is a series of questions a program manager has to answer: about the legal basis for the program, its efficacy against the threat, and its effects on privacy. I am particularly pleased that their questions on pages 3-4 are very similar to the “five steps” I wrote about in Beyond Fear. I am thrilled that the document takes a “trade-off” approach; the last question asks: “Should the program proceed? Do the benefits of the program…justify the costs to privacy interests….?”

I think this is a good starting place for any technology or program with respect to security and privacy. And I hope the DHS actually follows the recommendations in this report.

Posted on March 21, 2006 at 3:07 PM • View Comments

Data Mining for Terrorists

In the post 9/11 world, there’s much focus on connecting the dots. Many believe that data mining is the crystal ball that will enable us to uncover future terrorist plots. But even in the most wildly optimistic projections, data mining isn’t tenable for that purpose. We’re not trading privacy for security; we’re giving up privacy and getting no security in return.

Most people first learned about data mining in November 2002, when news broke about a massive government data mining program called Total Information Awareness. The basic idea was as audacious as it was repellent: suck up as much data as possible about everyone, sift through it with massive computers, and investigate patterns that might indicate terrorist plots. Americans across the political spectrum denounced the program, and in September 2003, Congress eliminated its funding and closed its offices.

But TIA didn’t die. According to The National Journal, it just changed its name and moved inside the Defense Department.

This shouldn’t be a surprise. In May 2004, the General Accounting Office published a report that listed 122 different federal government data mining programs that used people’s personal information. This list didn’t include classified programs, like the NSA’s eavesdropping effort, or state-run programs like MATRIX.

The promise of data mining is compelling, and convinces many. But it’s wrong. We’re not going to find terrorist plots through systems like this, and we’re going to waste valuable resources chasing down false alarms. To understand why, we have to look at the economics of the system.

Security is always a trade-off, and for a system to be worthwhile, the advantages have to be greater than the disadvantages. A national security data mining program is going to find some percentage of real attacks, and some percentage of false alarms. If the benefits of finding and stopping those attacks outweigh the cost—in money, liberties, etc.—then the system is a good one. If not, then you’d be better off spending that cost elsewhere.

Data mining works best when there’s a well-defined profile you’re searching for, a reasonable number of attacks per year, and a low cost of false alarms. Credit card fraud is one of data mining’s success stories: all credit card companies data mine their transaction databases, looking for spending patterns that indicate a stolen card. Many credit card thieves share a pattern—purchase expensive luxury goods, purchase things that can be easily fenced, etc.—and data mining systems can minimize the losses in many cases by shutting down the card. In addition, the cost of false alarms is only a phone call to the cardholder asking him to verify a couple of purchases. The cardholders don’t even resent these phone calls—as long as they’re infrequent—so the cost is just a few minutes of operator time.

Terrorist plots are different. There is no well-defined profile, and attacks are very rare. Taken together, these facts mean that data mining systems won’t uncover any terrorist plots until they are very accurate, and that even very accurate systems will be so flooded with false alarms that they will be useless.

All data mining systems fail in two different ways: false positives and false negatives. A false positive is when the system identifies a terrorist plot that really isn’t one. A false negative is when the system misses an actual terrorist plot. Depending on how you “tune” your detection algorithms, you can err on one side or the other: you can increase the number of false positives to ensure that you are less likely to miss an actual terrorist plot, or you can reduce the number of false positives at the expense of missing terrorist plots.

To reduce both those numbers, you need a well-defined profile. And that’s a problem when it comes to terrorism. In hindsight, it was really easy to connect the 9/11 dots and point to the warning signs, but it’s much harder before the fact. Certainly, there are common warning signs that many terrorist plots share, but each is unique, as well. The better you can define what you’re looking for, the better your results will be. Data mining for terrorist plots is going to be sloppy, and it’s going to be hard to find anything useful.

Data mining is like searching for a needle in a haystack. There are 900 million credit cards in circulation in the United States. According to the FTC September 2003 Identity Theft Survey Report, about 1% (10 million) cards are stolen and fraudulently used each year. Terrorism is different. There are trillions of connections between people and events—things that the data mining system will have to “look at”—and very few plots. This rarity makes even accurate identification systems useless.

Let’s look at some numbers. We’ll be optimistic. We’ll assume the system has a 1 in 100 false positive rate (99% accurate), and a 1 in 1,000 false negative rate (99.9% accurate).

Assume one trillion possible indicators to sift through: that’s about ten events—e-mails, phone calls, purchases, web surfings, whatever—per person in the U.S. per day. Also assume that 10 of them are actually terrorists plotting.

This unrealistically-accurate system will generate one billion false alarms for every real terrorist plot it uncovers. Every day of every year, the police will have to investigate 27 million potential plots in order to find the one real terrorist plot per month. Raise that false-positive accuracy to an absurd 99.9999% and you’re still chasing 2,750 false alarms per day—but that will inevitably raise your false negatives, and you’re going to miss some of those ten real plots.

This isn’t anything new. In statistics, it’s called the “base rate fallacy,” and it applies in other domains as well. For example, even highly accurate medical tests are useless as diagnostic tools if the incidence of the disease is rare in the general population. Terrorist attacks are also rare, any “test” is going to result in an endless stream of false alarms.

This is exactly the sort of thing we saw with the NSA’s eavesdropping program: the New York Times reported that the computers spat out thousands of tips per month. Every one of them turned out to be a false alarm.

And the cost was enormous: not just the cost of the FBI agents running around chasing dead-end leads instead of doing things that might actually make us safer, but also the cost in civil liberties. The fundamental freedoms that make our country the envy of the world are valuable, and not something that we should throw away lightly.

Data mining can work. It helps Visa keep the costs of fraud down, just as it helps Amazon.com show me books that I might want to buy, and Google show me advertising I’m more likely to be interested in. But these are all instances where the cost of false positives is low—a phone call from a Visa operator, or an uninteresting ad—and in systems that have value even if there is a high number of false negatives.

Finding terrorism plots is not a problem that lends itself to data mining. It’s a needle-in-a-haystack problem, and throwing more hay on the pile doesn’t make that problem any easier. We’d be far better off putting people in charge of investigating potential plots and letting them direct the computers, instead of putting the computers in charge and letting them decide who should be investigated.

This essay originally appeared on Wired.com.

Posted on March 9, 2006 at 7:44 AM • View Comments

The Analog Hole

Nice essay on the human dimension of the problem of securing information. “Analog hole” is a good name for it.

Along the same lines, here’s a story about the security risks of talking loudly:

About four seats away is a gentleman (on this occasion pronounced ‘fool’) with a BlackBerry mobile device and a very loud voice. He is obviously intent on selling a customer something and is briefing his team. It seems he is the leader as he defines the strategy and assigns each of his unseen team with specific tasks and roles.

Customer products, names, preferences, relationships and monies are being broadcast to everyone within earshot. The strategy for the conference call is discussed, and the specific customer now identified by name and company, and openly described as a BlackBerry nut!

Posted on March 8, 2006 at 12:48 PM • View Comments

The Future of Privacy

Over the past 20 years, there’s been a sea change in the battle for personal privacy.

The pervasiveness of computers has resulted in the almost constant surveillance of everyone, with profound implications for our society and our freedoms. Corporations and the police are both using this new trove of surveillance data. We as a society need to understand the technological trends and discuss their implications. If we ignore the problem and leave it to the “market,” we’ll all find that we have almost no privacy left.

Most people think of surveillance in terms of police procedure: Follow that car, watch that person, listen in on his phone conversations. This kind of surveillance still occurs. But today’s surveillance is more like the NSA’s model, recently turned against Americans: Eavesdrop on every phone call, listening for certain keywords. It’s still surveillance, but it’s wholesale surveillance.

Wholesale surveillance is a whole new world. It’s not “follow that car,” it’s “follow every car.” The National Security Agency can eavesdrop on every phone call, looking for patterns of communication or keywords that might indicate a conversation between terrorists. Many airports collect the license plates of every car in their parking lots, and can use that database to locate suspicious or abandoned cars. Several cities have stationary or car-mounted license-plate scanners that keep records of every car that passes, and save that data for later analysis.

More and more, we leave a trail of electronic footprints as we go through our daily lives. We used to walk into a bookstore, browse, and buy a book with cash. Now we visit Amazon, and all of our browsing and purchases are recorded. We used to throw a quarter in a toll booth; now EZ Pass records the date and time our car passed through the booth. Data about us are collected when we make a phone call, send an e-mail message, make a purchase with our credit card, or visit a website.

Much has been written about RFID chips and how they can be used to track people. People can also be tracked by their cell phones, their Bluetooth devices, and their WiFi-enabled computers. In some cities, video cameras capture our image hundreds of times a day.

The common thread here is computers. Computers are involved more and more in our transactions, and data are byproducts of these transactions. As computer memory becomes cheaper, more and more of these electronic footprints are being saved. And as processing becomes cheaper, more and more of it is being cross-indexed and correlated, and then used for secondary purposes.

Information about us has value. It has value to the police, but it also has value to corporations. The Justice Department wants details of Google searches, so they can look for patterns that might help find child pornographers. Google uses that same data so it can deliver context-sensitive advertising messages. The city of Baltimore uses aerial photography to surveil every house, looking for building permit violations. A national lawn-care company uses the same data to better market its services. The phone company keeps detailed call records for billing purposes; the police use them to catch bad guys.

In the dot-com bust, the customer database was often the only salable asset a company had. Companies like Experian and Acxiom are in the business of buying and reselling this sort of data, and their customers are both corporate and government.

Computers are getting smaller and cheaper every year, and these trends will continue. Here’s just one example of the digital footprints we leave:

It would take about 100 megabytes of storage to record everything the fastest typist input to his computer in a year. That’s a single flash memory chip today, and one could imagine computer manufacturers offering this as a reliability feature. Recording everything the average user does on the Internet requires more memory: 4 to 8 gigabytes a year. That’s a lot, but “record everything” is Gmail’s model, and it’s probably only a few years before ISPs offer this service.

The typical person uses 500 cell phone minutes a month; that translates to 5 gigabytes a year to save it all. My iPod can store 12 times that data. A “life recorder” you can wear on your lapel that constantly records is still a few generations off: 200 gigabytes/year for audio and 700 gigabytes/year for video. It’ll be sold as a security device, so that no one can attack you without being recorded. When that happens, will not wearing a life recorder be used as evidence that someone is up to no good, just as prosecutors today use the fact that someone left his cell phone at home as evidence that he didn’t want to be tracked?

In a sense, we’re living in a unique time in history. Identification checks are common, but they still require us to whip out our ID. Soon it’ll happen automatically, either through an RFID chip in our wallet or face-recognition from cameras. And those cameras, now visible, will shrink to the point where we won’t even see them.

We’re never going to stop the march of technology, but we can enact legislation to protect our privacy: comprehensive laws regulating what can be done with personal information about us, and more privacy protection from the police. Today, personal information about you is not yours; it’s owned by the collector. There are laws protecting specific pieces of personal data—videotape rental records, health care information—but nothing like the broad privacy protection laws you find in European countries. That’s really the only solution; leaving the market to sort this out will result in even more invasive wholesale surveillance.

Most of us are happy to give out personal information in exchange for specific services. What we object to is the surreptitious collection of personal information, and the secondary use of information once it’s collected: the buying and selling of our information behind our back.

In some ways, this tidal wave of data is the pollution problem of the information age. All information processes produce it. If we ignore the problem, it will stay around forever. And the only way to successfully deal with it is to pass laws regulating its generation, use and eventual disposal.

This essay was originally published in the Minneapolis Star-Tribune.

Posted on March 6, 2006 at 5:41 AM • View Comments

AT&T's 1.9-Trillion-Call Database

This whole article is worth reading, but I found this tidbit particularly interesting:

He was alluding to databases maintained at an AT&T data center in Kansas, which now contain electronic records of 1.92 trillion telephone calls, going back decades. The Electronic Frontier Foundation, a digital-rights advocacy group, has asserted in a lawsuit that the AT&T Daytona system, a giant storehouse of calling records and Internet message routing information, was the foundation of the N.S.A.’s effort to mine telephone records without a warrant.

An AT&T spokeswoman said the company would not comment on the claim, or generally on matters of national security or customer privacy.

But the mining of the databases in other law enforcement investigations is well established, with documented results. One application of the database technology, called Security Call Analysis and Monitoring Platform, or Scamp, offers access to about nine weeks of calling information. It currently handles about 70,000 queries a month from fraud and law enforcement investigators, according to AT&T documents.

A former AT&T official who had detailed knowledge of the call-record database said the Daytona system takes great care to make certain that anyone using the database – whether AT&T employee or law enforcement official with a subpoena – sees only information he or she is authorized to see, and that an audit trail keeps track of all users. Such information is frequently used to build models of suspects’ social networks.

The official, speaking on condition of anonymity because he was discussing sensitive corporate matters, said every telephone call generated a record: number called, time of call, duration of call, billing category and other details. While the database does not contain such billing data as names, addresses and credit card numbers, those records are in a linked database that can be tapped by authorized users.

New calls are entered into the database immediately after they end, the official said, adding, “I would characterize it as near real time.”

According to a current AT&T employee, whose identity is being withheld to avoid jeopardizing his job, the mining of the AT&T databases had a notable success in helping investigators find the perpetrators of what was known as the Moldovan porn scam.

In 1997 a shadowy group in Moldova, a former Soviet republic, was tricking Internet users by enticing them to a pornography Web site that would download a piece of software that disconnected the computer user from his local telephone line and redialed a costly 900 number in Moldova.

While another long-distance carrier simply cut off the entire nation of Moldova from its network, AT&T and the Moldovan authorities were able to mine the database to track the culprits.

Posted on March 3, 2006 at 11:45 AM • View Comments

More on Greek Wiretapping

Earlier this month I blogged about a wiretapping scandal in Greece.

Unknowns tapped the mobile phones of about 100 Greek politicians and offices, including the U.S. embassy in Athens and the Greek prime minister.

Details are sketchy, but it seems that a piece of malicious code was discovered by Ericsson technicians in Vodafone’s mobile phone software. The code tapped into the conference call system. It “conference called” phone calls to 14 prepaid mobile phones where the calls were recorded.

More details are emerging. It turns out that the “malicious code” was actually code designed into the system. It’s eavesdropping code put into the system for the police.

The attackers managed to bypass the authorization mechanisms of the eavesdropping system, and activate the “lawful interception” module in the mobile network. They then redirected about 100 numbers to 14 shadow numbers they controlled. (Here are translations of some of the press conferences with technical details. And here are details of the system used.)

There is an important security lesson here. I have long argued that when you build surveillance mechanisms into communication systems, you invite the bad guys to use those mechanisms for their own purposes. That’s exactly what happened here.

UPDATED TO ADD (3/2): From a reader: “I have an update. There is some news from the ‘Hellenic Authority for the Information and Communication Security and Privacy’ with a few facts and I got a rumor that there is a root backdoor in the telnetd of Ericssons AXE backdoor. (No, I can’t confirm the rumor.)”

Posted on March 1, 2006 at 8:04 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.