Paul Kelly and colleagues at Loughborough University found that a disulfur dinitride (S2N2) polymer turned exposed fingerprints brown, as the polymer reaction was initiated from the near-undetectable remaining residues.
Traces of inkjet printer ink can also initiate the polymer. The detection limit is so low that details of a printed letter previously in an envelope could be read off the inside of the envelope after being exposed to S2N2.
“A one-covers-all versatile system like this has obvious potential,” says Kelly.
“This work has demonstrated that it is possible to obtain fingerprints from surfaces that hitherto have been considered extremely difficult, if not impossible, to obtain,” says Colin Lewis, scientific advisor at the UK Ministry of Defence. “The method proposed has shown that this system could well provide capabilities which could significantly enhance the tools available to forensic scientists in the future.”
Entries Tagged "side-channel attacks"
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The researchers from the Security and Cryptography Laboratory at Ecole Polytechnique Federale de Lausanne are able to capture keystrokes by monitoring the electromagnetic radiation of PS/2, universal serial bus, or laptop keyboards. They’ve outline four separate attack methods, some that work at a distance of as much as 65 feet from the target.
In one video demonstration, researchers Martin Vuagnoux and Sylvain Pasini sniff out the the keystrokes typed into a standard keyboard using a large antenna that’s about 20 to 30 feet away in an adjacent room.
Traffic analysis works even through the encryption:
The new compression technique, called variable bitrate compression produces different size packets of data for different sounds.
That happens because the sampling rate is kept high for long complex sounds like “ow”, but cut down for simple consonants like “c”. This variable method saves on bandwidth, while maintaining sound quality.
VoIP streams are encrypted to prevent eavesdropping. However, a team from John Hopkins University in Baltimore, Maryland, US, has shown that simply measuring the size of packets without decoding them can identify whole words and phrases with a high rate of accuracy.
The technique isn’t good enough to decode entire conversations, but it’s pretty impressive.
Nice piece of research:
We show that disk encryption, the standard approach to protecting sensitive data on laptops, can be defeated by relatively simple methods. We demonstrate our methods by using them to defeat three popular disk encryption products: BitLocker, which comes with Windows Vista; FileVault, which comes with MacOS X; and dm-crypt, which is used with Linux.
The root of the problem lies in an unexpected property of today’s DRAM memories. DRAMs are the main memory chips used to store data while the system is running. Virtually everybody, including experts, will tell you that DRAM contents are lost when you turn off the power. But this isn’t so. Our research shows that data in DRAM actually fades out gradually over a period of seconds to minutes, enabling an attacker to read the full contents of memory by cutting power and then rebooting into a malicious operating system.
Interestingly, if you cool the DRAM chips, for example by spraying inverted cans of “canned air” dusting spray on them, the chips will retain their contents for much longer. At these temperatures (around -50 °C) you can remove the chips from the computer and let them sit on the table for ten minutes or more, without appreciable loss of data. Cool the chips in liquid nitrogen (-196 °C) and they hold their state for hours at least, without any power. Just put the chips back into a machine and you can read out their contents.
This is deadly for disk encryption products because they rely on keeping master decryption keys in DRAM. This was thought to be safe because the operating system would keep any malicious programs from accessing the keys in memory, and there was no way to get rid of the operating system without cutting power to the machine, which “everybody knew” would cause the keys to be erased.
Our results show that an attacker can cut power to the computer, then power it back up and boot a malicious operating system (from, say, a thumb drive) that copies the contents of memory. Having done that, the attacker can search through the captured memory contents, find any crypto keys that might be there, and use them to start decrypting hard disk contents. We show very effective methods for finding and extracting keys from memory, even if the contents of memory have faded somewhat (i.e., even if some bits of memory were flipped during the power-off interval). If the attacker is worried that memory will fade too quickly, he can chill the DRAM chips before cutting power.
There seems to be no easy fix for these problems. Fundamentally, disk encryption programs now have nowhere safe to store their keys. Today’s Trusted Computing hardware does not seem to help; for example, we can defeat BitLocker despite its use of a Trusted Platform Module.
There is a general security problem illustrated here: it is very difficult to secure data when the attacker has physical control of the machine the data is stored on. I talk about the general problem here, and it’s a hard problem.
EDITED TO ADD (2/26): How-to, with pictures.
…despite the use of encryption, a passive eavesdropper can still learn private information about what someone is watching via their Slingbox Pro.
First, in order to conserve bandwidth, the Slingbox Pro uses something called variable bitrate (VBR) encoding. VBR is a standard approach for compressing streaming multimedia. At a very abstract level, the idea is to only transmit the differences between frames. This means that if a scene changes rapidly, the Slingbox Pro must still transmit a lot of data. But if the scene changes slowly, the Slingbox Pro will only have to transmit a small amount of data—a great bandwidth saver.
Now notice that different movies have different visual effects (e.g., some movies have frequent and rapid scene changes, others don’t). The use of VBR encodings therefore means that the amount data transmitted over time can serve as a fingerprint for a movie. And, since encryption alone won’t fully conceal the number of bytes transmitted, this fingerprint can survive encryption!
We experimented with fingerprinting encrypted Slingbox Pro movie transmissions in our lab. We took 26 of our favorite movies (we tried to pick movies from the same director, or multiple movies in a series), and we played them over our Slingbox Pro. Sometimes we streamed them to a laptop attached to a wired network, and sometimes we streamed them to a laptop connected to an 802.11 wireless network. In all cases the laptop was one hop away.
We trained our system on some of those traces. We then took new query traces for these movies and tried to match them to our database. For over half of the movies, we were able to correctly identify the movie over 98% of the time. This is well above the less than 4% accuracy that one would get by random chance.
More details in the paper.
Consider two different security problems. In the first, you store your valuables in a safe in your basement. The threat is burglars, of course. But the safe is yours, and the house is yours, too. You control access to the safe, and probably have an alarm system.
The second security problem is similar, but you store your valuables in someone else’s safe. Even worse, it’s someone you don’t trust. He doesn’t know the combination, but he controls access to the safe. He can try to break in at his leisure. He can transport the safe anyplace he needs to. He can use whatever tools he wants. In the first case, the safe needs to be secure, but it’s still just a part of your overall home security. In the second case, the safe is the only security device you have.
This second security problem might seem contrived, but it happens regularly in our information society: Data controlled by one person is stored on a device controlled by another. Think of a stored-value smart card: If the person owning the card can break the security, he can add money to the card. Think of a DRM system: Its security depends on the person owning the computer not being able to get at the insides of the DRM security. Think of the RFID chip on a passport. Or a postage meter. Or SSL traffic being sent over a public network.
These systems are difficult to secure, and not just because you give your attacker the device and let him utilize whatever time, equipment and expertise he needs to break it. It’s difficult to secure because breaks are generally “class breaks.” The expert who figures out how to do it can build hardware—or write software—to do it automatically. Only one person needs to break a given DRM system; the software can break every other device in the same class.
This means that the security needs to be secure not against the average attacker, but against the smartest, most motivated and best funded attacker.
I was reminded of this problem earlier this month, when researchers announced a new attack (.pdf) against implementations of the RSA cryptosystem. The attack exploits the fact that different operations take different times on modern CPUs. By closely monitoring—and actually affecting—the CPU during an RSA operation, an attacker can recover the key. The most obvious applications for this attack are DRM systems that try to use a protected partition in the CPU to prevent the computer’s owner from learning the DRM system’s cryptographic keys.
These sorts of attacks are not new. In 1995, researchers discovered they could recover cryptographic keys by comparing relative timings on chips. In later years, both power and radiation were used to break cryptosystems. I called these “side-channel attacks,” because they made use of information other than the plaintext and ciphertext. And where are they most useful? To recover secrets from smart cards.
Whenever I see security systems with this data/device separation, I try to solve the security problem by removing the separation. This means completely redesigning the system and the security assumptions behind it.
Compare a stored-value card with a debit card. In the former case, the card owner can create money by changing the value on the card. For this system to be secure, the card needs to be protected by a variety of security countermeasures. In the latter case, there aren’t any secrets on the card. Your bank doesn’t care that you can read the account number off the front of the card, or the data off the magnetic stripe off the back—the real data, and the security, are in the bank’s databases.
Or compare a DRM system with a financial model that doesn’t care about copying. The former is impossible to secure, the latter easy.
While common in digital systems, this kind of security problem isn’t limited to them. Last month, the province of Ontario started investigating insider fraud in their scratch-and-win lottery systems, after the CBC aired allegations that people selling the tickets are able to figure out which tickets are winners, and not sell them. It’s the same problem: the owners of the data on the tickets—the lottery commission—tried to keep that data secret from those who had physical control of the tickets. And they failed.
Compare that with a traditional drawing-at-the-end-of-the-week lottery system. The attack isn’t possible, because there are no secrets on the tickets for an attacker to learn.
Separating data ownership and device ownership doesn’t mean that security is impossible, only much more difficult. You can buy a safe so strong that you can lock your valuables in it and give it to your attacker—with confidence. I’m not so sure you can design a smart card that keeps secrets from its owner, or a DRM system that works on a general-purpose computer—especially because of the problem of class breaks. But in all cases, the best way to solve the security problem is not to have it in the first place.
This essay originally appeared on Wired.com.
EDITED TO ADD (12/1): I completely misunderstood the lottery problem in Ontario. The frauds reported were perpetrated by lottery machine operators at convenience stores and the like stealing end-of-week draw tickets from unsuspecting customers. The customer would hand their ticket over the counter to be scanned to see if it was a winner. The clerk (knowing what the winning numbers actually were) would palm a non-winning ticket into the machine, inform the customer “sorry better luck next time” and claim the prize on their own at a later date.
Nice scam, but nothing to do with the point of this essay.
A new paper describes a timing attack against RSA, one that bypasses existing security measures against these sorts of attacks. The attack described is optimized for the Pentium 4, and is particularly suited for applications like DRM.
Meta moral: If Alice controls the device, and Bob wants to control secrets inside the device, Bob has a very difficult security problem. These “side-channel” attacks—timing, power, radiation, etc.—allow Alice to mount some very devastating attacks against Bob’s secrets.
This is great work by Yossi Oren and Adi Shamir:
We show the first power analysis attack on passive RFID tags. Compared to standard power analysis attacks, this attack is unique in that it requires no physical contact with the device under attack. While the specific attack described here requires the attacker to actually transmit data to the tag under attack, the power analysis part itself requires only a receive antenna. This means that a variant of this attack can be devised such that the attacker is completely passive while it is acquiring the data, making the attack very hard to detect. As a proof of concept, we describe a password extraction attack on Class 1 Generation 1 EPC tags operating in the UHF frequency range. The attack presented below lets an adversary discover the kill password of such a tag and, then, disable it. The attack can be readily adapted to finding the access and kill passwords of Gen 2 tags. The main significance of our attack is in its implications any cryptographic functionality built into tags needs to be designed to be resistant to power analysis, and achieving this resistance is an undertaking which has an effect both on the price and on the read range of tags.
My guess of the industry’s response: downplay the results and pretend it’s not a problem.
Nice timing attack against AES.
For those of you who don’t know, timing attacks are an example of side-channel cryptanalysis: cryptanalysis using additional information about the inner workings of the cryptographic algorithm. I wrote about them here.
What’s the big idea here?
There are two ways to look at a cryptographic primitive: block cipher, digital signature function, whatever. The first is as a chunk of math. The second is a physical (or software) implementation of that math.
Traditionally, cryptanalysis has been directed solely against the math. Differential and linear cryptanalysis are good examples of this: high-powered mathematical tools that can be used to break different block ciphers.
On the other hand, timing attacks, power analysis, and fault analysis all makes assumptions about implementation, and uses additional information garnered from attacking those implementations. Failure analysis assumes a one-bit feedback from the implementation—was the message successfully decrypted—in order to break the underlying cryptographic primitive. Timing attacks assumes that an attacker knows how long a particular encryption operation takes.
Sidebar photo of Bruce Schneier by Joe MacInnis.