Tracking People Without GPS

Interesting research: The trick in accurately tracking a person with this method is finding out what kind of activity they’re performing. Whether they’re walking, driving a car, or riding in a train or airplane, it’s pretty easy to figure out when you know what you’re looking for. The sensors can determine how fast a person is traveling and what kind…

Interesting research:

The trick in accurately tracking a person with this method is finding out what kind of activity they're performing. Whether they're walking, driving a car, or riding in a train or airplane, it's pretty easy to figure out when you know what you're looking for.

The sensors can determine how fast a person is traveling and what kind of movements they make. Moving at a slow pace in one direction indicates walking. Going a little bit quicker but turning at 90-degree angles means driving. Faster yet, we're in train or airplane territory. Those are easy to figure out based on speed and air pressure.

After the app determines what you're doing, it uses the information it collects from the sensors. The accelerometer relays your speed, the magnetometer tells your relation to true north, and the barometer offers up the air pressure around you and compares it to publicly available information. It checks in with The Weather Channel to compare air pressure data from the barometer to determine how far above sea level you are. Google Maps and data offered by the US Geological Survey Maps provide incredibly detailed elevation readings.

Once it has gathered all of this information and determined the mode of transportation you're currently taking, it can then begin to narrow down where you are. For flights, four algorithms begin to estimate the target's location and narrows down the possibilities until its error rate hits zero.

If you're driving, it can be even easier. The app knows the time zone you're in based on the information your phone has provided to it. It then accesses information from your barometer and magnetometer and compares it to information from publicly available maps and weather reports. After that, it keeps track of the turns you make. With each turn, the possible locations whittle down until it pinpoints exactly where you are.

To demonstrate how accurate it is, researchers did a test run in Philadelphia. It only took 12 turns before the app knew exactly where the car was.

This is a good example of how powerful synthesizing information from disparate data sources can be. We spend too much time worried about individual data collection systems, and not enough about analysis techniques of those systems.

Research paper.

from https://www.schneier.com/blog/

Security Vulnerabilities in Certificate Pinning

New research found that many banks offer certificate pinning as a security feature, but fail to authenticate the hostname. This leaves the systems open to man-in-the-middle attacks. From the paper: Abstract: Certificate verification is a crucial stage in the establishment of a TLS connection. A common security flaw in TLS implementations is the lack of certificate hostname verification but, in…

New research found that many banks offer certificate pinning as a security feature, but fail to authenticate the hostname. This leaves the systems open to man-in-the-middle attacks.

From the paper:

Abstract: Certificate verification is a crucial stage in the establishment of a TLS connection. A common security flaw in TLS implementations is the lack of certificate hostname verification but, in general, this is easy to detect. In security-sensitive applications, the usage of certificate pinning is on the rise. This paper shows that certificate pinning can (and often does) hide the lack of proper hostname verification, enabling MITM attacks. Dynamic (black-box) detection of this vulnerability would typically require the tester to own a high security certificate from the same issuer (and often same intermediate CA) as the one used by the app. We present Spinner, a new tool for black-box testing for this vulnerability at scale that does not require purchasing any certificates. By redirecting traffic to websites which use the relevant certificates and then analysing the (encrypted) network traffic we are able to determine whether the hostname check is correctly done, even in the presence of certificate pinning. We use Spinner to analyse 400 security-sensitive Android and iPhone apps. We found that 9 apps had this flaw, including two of the largest banks in the world: Bank of America and HSBC. We also found that TunnelBear, one of the most popular VPN apps was also vulnerable. These apps have a joint user base of tens of millions of users.

News article.

from https://www.schneier.com/blog/

Google’s Data on Login Thefts

This is interesting research and data: With Google accounts as a case-study, we teamed up with the University of California, Berkeley to better understand how hijackers attempt to take over accounts in the wild. From March 2016 to March 2017, we analyzed several black markets to see how hijackers steal passwords and other sensitive data. […] Our research tracked several…

This is interesting research and data:

With Google accounts as a case-study, we teamed up with the University of California, Berkeley to better understand how hijackers attempt to take over accounts in the wild. From March 2016 to March 2017, we analyzed several black markets to see how hijackers steal passwords and other sensitive data.

[...]

Our research tracked several black markets that traded third-party password breaches, as well as 25,000 blackhat tools used for phishing and keylogging. In total, these sources helped us identify 788,000 credentials stolen via keyloggers, 12 million credentials stolen via phishing, and 3.3 billion credentials exposed by third-party breaches.

The report.

from https://www.schneier.com/blog/

New Research in Invisible Inks

It’s a lot more chemistry than I understand: Invisible inks based on "smart" fluorescent materials have been shining brightly (if only you could see them) in the data-encryption/decryption arena lately…. But some of the materials are costly or difficult to prepare, and many of these inks remain somewhat visible when illuminated with ambient or ultraviolet light. Liang Li and coworkers…

It's a lot more chemistry than I understand:

Invisible inks based on "smart" fluorescent materials have been shining brightly (if only you could see them) in the data-encryption/decryption arena lately.... But some of the materials are costly or difficult to prepare, and many of these inks remain somewhat visible when illuminated with ambient or ultraviolet light. Liang Li and coworkers at Shanghai Jiao Tong University may have come up with a way to get around those problems. The team prepared a colorless solution of an inexpensive lead-based metal-organic framework (MOF) compound and used it in an ink-jet printer to create completely invisible patterns on paper. Then they exposed the paper to a methylammonium bromide decryption solution...revealing the pattern.... They rendered the pattern invisible again by briefly treating the paper with a polar solvent....

Full paper.

from https://www.schneier.com/blog/

Heart Size: Yet Another Biometric

Turns out that heart size doesn’t change throughout your adult life, and you can use low-level Doppler radar to scan the size — even at a distance — as a biometric. Research paper (to be available soon)….

Turns out that heart size doesn't change throughout your adult life, and you can use low-level Doppler radar to scan the size -- even at a distance -- as a biometric.

Research paper (to be available soon).

from https://www.schneier.com/blog/

Attack on Old ANSI Random Number Generator

Almost 20 years ago, I wrote a paper that pointed to a potential flaw in the ANSI X9.17 RNG standard. Now, new research has found that the flaw exists in some implementations of the RNG standard. Here’s the research paper, the website — complete with cute logo — for the attack, and Matthew Green’s excellent blog post on the research….

Almost 20 years ago, I wrote a paper that pointed to a potential flaw in the ANSI X9.17 RNG standard. Now, new research has found that the flaw exists in some implementations of the RNG standard.

Here's the research paper, the website -- complete with cute logo -- for the attack, and Matthew Green's excellent blog post on the research.

from https://www.schneier.com/blog/

Friday Squid Blogging: Baby Ichthyosaurus Fed on Squid

New discovery: paper and article. As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered. Read my blog posting guidelines here….

New discovery: paper and article.

As usual, you can also use this squid post to talk about the security stories in the news that I haven't covered.

Read my blog posting guidelines here.

from https://www.schneier.com/blog/

Hacking Voice Assistant Systems with Inaudible Voice Commands

Turns out that all the major voice assistants — Siri, Google Now, Samsung S Voice, Huawei HiVoice, Cortana and Alexa — listen at audio frequencies the human ear can’t hear. Hackers can hijack those systems with inaudible commands that their owners can’t hear. News articles….

Turns out that all the major voice assistants -- Siri, Google Now, Samsung S Voice, Huawei
HiVoice, Cortana and Alexa -- listen at audio frequencies the human ear can't hear. Hackers can hijack those systems with inaudible commands that their owners can't hear.

News articles.

from https://www.schneier.com/blog/

New Techniques in Fake Reviews

Research paper: "Automated Crowdturfing Attacks and Defenses in Online Review Systems." Abstract: Malicious crowdsourcing forums are gaining traction as sources of spreading misinformation online, but are limited by the costs of hiring and managing human workers. In this paper, we identify a new class of attacks that leverage deep learning language models (Recurrent Neural Networks or RNNs) to automate the…

Research paper: "Automated Crowdturfing Attacks and Defenses in Online Review Systems."

Abstract: Malicious crowdsourcing forums are gaining traction as sources of spreading misinformation online, but are limited by the costs of hiring and managing human workers. In this paper, we identify a new class of attacks that leverage deep learning language models (Recurrent Neural Networks or RNNs) to automate the generation of fake online reviews for products and services. Not only are these attacks cheap and therefore more scalable, but they can control rate of content output to eliminate the signature burstiness that makes crowdsourced campaigns easy to detect.

Using Yelp reviews as an example platform, we show how a two phased review generation and customization attack can produce reviews that are indistinguishable by state-of-the-art statistical detectors. We conduct a survey-based user study to show these reviews not only evade human detection, but also score high on "usefulness" metrics by users. Finally, we develop novel automated defenses against these attacks, by leveraging the lossy transformation introduced by the RNN training and generation cycle. We consider countermeasures against our mechanisms, show that they produce unattractive cost-benefit tradeoffs for attackers, and that they can be further curtailed by simple constraints imposed by online service providers.

from https://www.schneier.com/blog/