Entries Tagged "academic papers"

Page 2 of 69

Interesting Attack on the EMV Smartcard Payment Standard

It’s complicated, but it’s basically a man-in-the-middle attack that involves two smartphones. The first phone reads the actual smartcard, and then forwards the required information to a second phone. That second phone actually conducts the transaction on the POS terminal. That second phone is able to convince the POS terminal to conduct the transaction without requiring the normally required PIN.

From a news article:

The researchers were able to demonstrate that it is possible to exploit the vulnerability in practice, although it is a fairly complex process. They first developed an Android app and installed it on two NFC-enabled mobile phones. This allowed the two devices to read data from the credit card chip and exchange information with payment terminals. Incidentally, the researchers did not have to bypass any special security features in the Android operating system to install the app.

To obtain unauthorized funds from a third-party credit card, the first mobile phone is used to scan the necessary data from the credit card and transfer it to the second phone. The second phone is then used to simultaneously debit the amount at the checkout, as many cardholders do nowadays. As the app declares that the customer is the authorized user of the credit card, the vendor does not realize that the transaction is fraudulent. The crucial factor is that the app outsmarts the card’s security system. Although the amount is over the limit and requires PIN verification, no code is requested.

The paper: “The EMV Standard: Break, Fix, Verify.”

Abstract: EMV is the international protocol standard for smartcard payment and is used in over 9 billion cards worldwide. Despite the standard’s advertised security, various issues have been previously uncovered, deriving from logical flaws that are hard to spot in EMV’s lengthy and complex specification, running over 2,000 pages.

We formalize a comprehensive symbolic model of EMV in Tamarin, a state-of-the-art protocol verifier. Our model is the first that supports a fine-grained analysis of all relevant security guarantees that EMV is intended to offer. We use our model to automatically identify flaws that lead to two critical attacks: one that defrauds the cardholder and another that defrauds the merchant. First, criminals can use a victim’s Visa contact-less card for high-value purchases, without knowledge of the card’s PIN. We built a proof-of-concept Android application and successfully demonstrated this attack on real-world payment terminals. Second, criminals can trick the terminal into accepting an unauthentic offline transaction, which the issuing bank should later decline, after the criminal has walked away with the goods. This attack is possible for implementations following the standard, although we did not test it on actual terminals for ethical reasons. Finally, we propose and verify improvements to the standard that prevent these attacks, as well as any other attacks that violate the considered security properties.The proposed improvements can be easily implemented in the terminals and do not affect the cards in circulation.

Posted on September 14, 2020 at 6:21 AMView Comments

Identifying People by Their Browsing Histories

Interesting paper: “Replication: Why We Still Can’t Browse in Peace: On the Uniqueness and Reidentifiability of Web Browsing Histories”:

We examine the threat to individuals’ privacy based on the feasibility of reidentifying users through distinctive profiles of their browsing history visible to websites and third parties. This work replicates and extends the 2012 paper Why Johnny Can’t Browse in Peace: On the Uniqueness of Web Browsing History Patterns[48]. The original work demonstrated that browsing profiles are highly distinctive and stable. We reproduce those results and extend the original work to detail the privacy risk posed by the aggregation of browsing histories. Our dataset consists of two weeks of browsing data from ~52,000 Firefox users. Our work replicates the original paper’s core findings by identifying 48,919 distinct browsing profiles, of which 99% are unique. High uniqueness hold seven when histories are truncated to just 100 top sites. We then find that for users who visited 50 or more distinct domains in the two-week data collection period, ~50% can be reidentified using the top 10k sites. Reidentifiability rose to over 80% for users that browsed 150 or more distinct domains. Finally, we observe numerous third parties pervasive enough to gather web histories sufficient to leverage browsing history as an identifier.

One of the authors of the original study comments on the replication.

Posted on August 25, 2020 at 6:28 AMView Comments

Using Disinformation to Cause a Blackout

Interesting paper: “How weaponizing disinformation can bring down a city’s power grid“:

Abstract: Social media has made it possible to manipulate the masses via disinformation and fake news at an unprecedented scale. This is particularly alarming from a security perspective, as humans have proven to be one of the weakest links when protecting critical infrastructure in general, and the power grid in particular. Here, we consider an attack in which an adversary attempts to manipulate the behavior of energy consumers by sending fake discount notifications encouraging them to shift their consumption into the peak-demand period. Using Greater London as a case study, we show that such disinformation can indeed lead to unwitting consumers synchronizing their energy-usage patterns, and result in blackouts on a city-scale if the grid is heavily loaded. We then conduct surveys to assess the propensity of people to follow-through on such notifications and forward them to their friends. This allows us to model how the disinformation may propagate through social networks, potentially amplifying the attack impact. These findings demonstrate that in an era when disinformation can be weaponized, system vulnerabilities arise not only from the hardware and software of critical infrastructure, but also from the behavior of the consumers.

I’m not sure the attack is practical, but it’s an interesting idea.

Posted on August 18, 2020 at 10:03 AMView Comments

UAE Hack and Leak Operations

Interesting paper on recent hack-and-leak operations attributed to the UAE:

Abstract: Four hack-and-leak operations in U.S. politics between 2016 and 2019, publicly attributed to the United Arab Emirates (UAE), Qatar, and Saudi Arabia, should be seen as the “simulation of scandal” ­– deliberate attempts to direct moral judgement against their target. Although “hacking” tools enable easy access to secret information, they are a double-edged sword, as their discovery means the scandal becomes about the hack itself, not about the hacked information. There are wider consequences for cyber competition in situations of constraint where both sides are strategic partners, as in the case of the United States and its allies in the Persian Gulf.

Posted on August 13, 2020 at 9:28 AMView Comments

Adversarial Machine Learning and the CFAA

I just co-authored a paper on the legal risks of doing machine learning research, given the current state of the Computer Fraud and Abuse Act:

Abstract: Adversarial Machine Learning is booming with ML researchers increasingly targeting commercial ML systems such as those used in Facebook, Tesla, Microsoft, IBM, Google to demonstrate vulnerabilities. In this paper, we ask, “What are the potential legal risks to adversarial ML researchers when they attack ML systems?” Studying or testing the security of any operational system potentially runs afoul the Computer Fraud and Abuse Act (CFAA), the primary United States federal statute that creates liability for hacking. We claim that Adversarial ML research is likely no different. Our analysis show that because there is a split in how CFAA is interpreted, aspects of adversarial ML attacks, such as model inversion, membership inference, model stealing, reprogramming the ML system and poisoning attacks, may be sanctioned in some jurisdictions and not penalized in others. We conclude with an analysis predicting how the US Supreme Court may resolve some present inconsistencies in the CFAA’s application in Van Buren v. United States, an appeal expected to be decided in 2021. We argue that the court is likely to adopt a narrow construction of the CFAA, and that this will actually lead to better adversarial ML security outcomes in the long term.

Medium post on the paper. News article, which uses our graphic without attribution.

Posted on July 23, 2020 at 6:03 AMView Comments

Fawkes: Digital Image Cloaking

Fawkes is a system for manipulating digital images so that they aren’t recognized by facial recognition systems.

At a high level, Fawkes takes your personal images, and makes tiny, pixel-level changes to them that are invisible to the human eye, in a process we call image cloaking. You can then use these “cloaked” photos as you normally would, sharing them on social media, sending them to friends, printing them or displaying them on digital devices, the same way you would any other photo. The difference, however, is that if and when someone tries to use these photos to build a facial recognition model, “cloaked” images will teach the model an highly distorted version of what makes you look like you. The cloak effect is not easily detectable, and will not cause errors in model training. However, when someone tries to identify you using an unaltered image of you (e.g. a photo taken in public), and tries to identify you, they will fail.

Research paper.

EDITED TO ADD (8/3): Kashmir Hill checks it out, and it’s got problems.

Another article.

Posted on July 22, 2020 at 9:12 AMView Comments

Hacking a Power Supply

This hack targets the firmware on modern power supplies. (Yes, power supplies are also computers.)

Normally, when a phone is connected to a power brick with support for fast charging, the phone and the power adapter communicate with each other to determine the proper amount of electricity that can be sent to the phone without damaging the device­ — the more juice the power adapter can send, the faster it can charge the phone.

However, by hacking the fast charging firmware built into a power adapter, Xuanwu Labs demonstrated that bad actors could potentially manipulate the power brick into sending more electricity than a phone can handle, thereby overheating the phone, melting internal components, or as Xuanwu Labs discovered, setting the device on fire.

Research paper, in Chinese.

Posted on July 21, 2020 at 6:09 AMView Comments

Securing the International IoT Supply Chain

Together with Nate Kim (former student) and Trey Herr (Atlantic Council Cyber Statecraft Initiative), I have written a paper on IoT supply chain security. The basic problem we try to solve is: How do you enforce IoT security regulations when most of the stuff is made in other countries? And our solution is: enforce the regulations on the domestic company that’s selling the stuff to consumers. There’s a lot of detail between here and there, though, and it’s all in the paper.

We also wrote a Lawfare post:

…we propose to leverage these supply chains as part of the solution. Selling to U.S. consumers generally requires that IoT manufacturers sell through a U.S. subsidiary or, more commonly, a domestic distributor like Best Buy or Amazon. The Federal Trade Commission can apply regulatory pressure to this distributor to sell only products that meet the requirements of a security framework developed by U.S. cybersecurity agencies. That would put pressure on manufacturers to make sure their products are compliant with the standards set out in this security framework, including pressuring their component vendors and original device manufacturers to make sure they supply parts that meet the recognized security framework.

News article.

Posted on July 1, 2020 at 9:31 AMView Comments

The Unintended Harms of Cybersecurity

Interesting research: “Identifying Unintended Harms of Cybersecurity Countermeasures“:

Abstract: Well-meaning cybersecurity risk owners will deploy countermeasures (technologies or procedures) to manage risks to their services or systems. In some cases, those countermeasures will produce unintended consequences, which must then be addressed. Unintended consequences can potentially induce harm, adversely affecting user behaviour, user inclusion, or the infrastructure itself (including other services or countermeasures). Here we propose a framework for preemptively identifying unintended harms of risk countermeasures in cybersecurity.The framework identifies a series of unintended harms which go beyond technology alone, to consider the cyberphysical and sociotechnical space: displacement, insecure norms, additional costs, misuse, misclassification, amplification, and disruption. We demonstrate our framework through application to the complex,multi-stakeholder challenges associated with the prevention of cyberbullying as an applied example. Our framework aims to illuminate harmful consequences, not to paralyze decision-making, but so that potential unintended harms can be more thoroughly considered in risk management strategies. The framework can support identification and preemptive planning to identify vulnerable populations and preemptively insulate them from harm. There are opportunities to use the framework in coordinating risk management strategy across stakeholders in complex cyberphysical environments.

Security is always a trade-off. I appreciate work that examines the details of that trade-off.

Posted on June 26, 2020 at 7:00 AMView Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.