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The winner of the Best Paper Award at Crypto this year was a significant improvement to lattice-based cryptanalysis.
This is important, because a bunch of NIST’s post-quantum options base their security on lattice problems.
I worry about standard…
Over on Lawfare, Jim Dempsey published a really interesting proposal for software liability: “Standard for Software Liability: Focus on the Product for Liability, Focus on the Process for Safe Harbor.”
Section 1 of this paper sets the stage by briefly describing the problem to be solved. Section 2 canvasses the different fields of law (warranty, negligence, products liability, and certification) that could provide a starting point for what would have to be legislative action establishing a system of software liability. The conclusion is that all of these fields would face the same question: How buggy is too buggy? Section 3 explains why existing software development frameworks do not provide a sufficiently definitive basis for legal liability. They focus on process, while a liability regime should begin with a focus on the product—that is, on outcomes. Expanding on the idea of building codes for building code, Section 4 shows some examples of product-focused standards from other fields. Section 5 notes that already there have been definitive expressions of software defects that can be drawn together to form the minimum legal standard of security. It specifically calls out the list of common software weaknesses tracked by the MITRE Corporation under a government contract. Section 6 considers how to define flaws above the minimum floor and how to limit that liability with a safe harbor…
TikTok seems to be skewing things in the interests of the Chinese Communist Party. (This is a serious analysis, and the methodology looks sound.)
Conclusion: Substantial Differences in Hashtag Ratios Raise
Concerns about TikTok’s ImpartialityGiven the research above, we assess a strong possibility that content on TikTok is either amplified or suppressed based on its alignment with the interests of the Chinese Government. Future research should aim towards a more comprehensive analysis to determine the potential influence of TikTok on popular public narratives. This research should determine if and how TikTok might be utilized for furthering national/regional or international objectives of the Chinese Government…
This is interesting:
For the first time, researchers have demonstrated that a large portion of cryptographic keys used to protect data in computer-to-server SSH traffic are vulnerable to complete compromise when naturally occurring computational errors occur while the connection is being established.
[…]
The vulnerability occurs when there are errors during the signature generation that takes place when a client and server are establishing a connection. It affects only keys using the RSA cryptographic algorithm, which the researchers found in roughly a third of the SSH signatures they examined. That translates to roughly 1 billion signatures out of the 3.2 billion signatures examined. Of the roughly 1 billion RSA signatures, about one in a million exposed the private key of the host…
Experimental result:
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected 350,757 coin flips to test the counterintuitive prediction from a physics model of human coin tossing developed by Persi Diaconis. The model asserts that when people flip an ordinary coin, it tends to land on the same side it started—Diaconis estimated the probability of a same-side outcome to be about 51%.
And the final paragraph:
Could future coin tossers use the same-side bias to their advantage? The magnitude of the observed bias can be illustrated using a betting scenario. If you bet a dollar on the outcome of a coin toss (i.e., paying 1 dollar to enter, and winning either 0 or 2 dollars depending on the outcome) and repeat the bet 1,000 times, knowing the starting position of the coin toss would earn you 19 dollars on average. This is more than the casino advantage for 6 deck blackjack against an optimal-strategy player, where the casino would make 5 dollars on a comparable bet, but less than the casino advantage for single-zero roulette, where the casino would make 27 dollars on average. These considerations lead us to suggest that when coin flips are used for high-stakes decision-making, the starting position of the coin is best concealed…
Adi Shamir et al. have a new model extraction attack on neural networks:
Polynomial Time Cryptanalytic Extraction of Neural Network Models
Abstract: Billions of dollars and countless GPU hours are currently spent on training Deep Neural Networks (DNNs) for a variety of tasks. Thus, it is essential to determine the difficulty of extracting all the parameters of such neural networks when given access to their black-box implementations. Many versions of this problem have been studied over the last 30 years, and the best current attack on ReLU-based deep neural networks was presented at Crypto’20 by Carlini, Jagielski, and Mironov. It resembles a differential chosen plaintext attack on a cryptosystem, which has a secret key embedded in its black-box implementation and requires a polynomial number of queries but an exponential amount of time (as a function of the number of neurons)…
Jake Appelbaum’s PhD thesis contains several new revelations from the classified NSA documents provided to journalists by Edward Snowden. Nothing major, but a few more tidbits.
Kind of amazing that that all happened ten years ago. At this point, …
Interesting research:
Shedding Light on CVSS Scoring Inconsistencies: A User-Centric Study on Evaluating Widespread Security Vulnerabilities
Abstract: The Common Vulnerability Scoring System (CVSS) is a popular method for evaluating the severity of vulnerabilities in vulnerability management. In the evaluation process, a numeric score between 0 and 10 is calculated, 10 being the most severe (critical) value. The goal of CVSS is to provide comparable scores across different evaluators. However, previous works indicate that CVSS might not reach this goal: If a vulnerability is evaluated by several analysts, their scores often differ. This raises the following questions: Are CVSS evaluations consistent? Which factors influence CVSS assessments? We systematically investigate these questions in an online survey with 196 CVSS users. We show that specific CVSS metrics are inconsistently evaluated for widespread vulnerability types, including Top 3 vulnerabilities from the ”2022 CWE Top 25 Most Dangerous Software Weaknesses” list. In a follow-up survey with 59 participants, we found that for the same vulnerabilities from the main study, 68% of these users gave different severity ratings. Our study reveals that most evaluators are aware of the problematic aspects of CVSS, but they still see CVSS as a useful tool for vulnerability assessment. Finally, we discuss possible reasons for inconsistent evaluations and provide recommendations on improving the consistency of scoring…
Interesting research: “An Empirical Study & Evaluation of Modern CAPTCHAs“:
Abstract: For nearly two decades, CAPTCHAS have been widely used as a means of protection against bots. Throughout the years, as their use grew, techniques to defeat or bypass CAPTCHAS have continued to improve. Meanwhile, CAPTCHAS have also evolved in terms of sophistication and diversity, becoming increasingly difficult to solve for both bots (machines) and humans. Given this long-standing and still-ongoing arms race, it is critical to investigate how long it takes legitimate users to solve modern CAPTCHAS, and how they are perceived by those users…
Researchers are trying to use AI to detect “social norms violations.” Feels a little sketchy right now, but this is the sort of thing that AIs will get better at. (Like all of these systems, anything but a very low false positive rate makes…