Big Data+Small Bias
> Among experts it’s well understood that “big data” doesn’t solve problems of bias. But how much should one trust an estimate from a big but possibly biased data set compared to a much smaller random sample? In Statistical paradises and paradoxes in big data, Xiao-Li Meng provides some answers which are shocking, even to experts.
Ironies of automation
> The central irony (‘combination of circumstances, the result of which is the direct opposite of what might be expected’) referred to in this paper is that the more we automate, and the more sophisticated we make that automation, the more we become dependent on a highly skilled human operator.
DECO - A novel privacy-preserving oracle protocol
> DECO is a privacy-preserving oracle protocol. Using cryptographic techniques, it lets users prove facts about their web (TLS) sessions to oracles while hiding privacy-sensitive data.
SHA-1 is a Shambles
> We have computed the very first chosen-prefix collision for SHA-1. In a nutshell, this means a complete and practical break of the SHA-1 hash function, with dangerous practical implications if you are still using this hash function. To put it in another way: all attacks that are practical on MD5 are now also practical on SHA-1.
A brief history of liquid computers
> A substrate does not have to be solid to compute. It is possible to make a computer purely from a liquid. I demonstrate this using a variety of experimental prototypes where a liquid carries signals, actuates mechanical computing devices and hosts chemical reactions. We show hydraulic mathematical machines that compute functions based on mass transfer analogies. I discuss several prototypes of computing devices that employ fluid flows and jets. They are fluid mappers, where the fluid flow explores a geometrically constrained space to find an optimal way around, e.g. the shortest path in a maze, and fluid logic devices where fluid jet streams interact at the junctions of inlets and results of the computation are represented by fluid jets at selected outlets. Fluid mappers and fluidic logic devices compute continuously valued functions albeit discretized. There is also an opportunity to do discrete operation directly by representing information by droplets and liquid marbles (droplets coated by hydrophobic powder). There, computation is implemented at the sites, in time and space, where droplets collide one with another. The liquid computers mentioned above use liquid as signal carrier or actuator: the exact nature of the liquid is not that important. What is inside the liquid becomes crucial when reaction–diffusion liquid-phase computing devices come into play: there, the liquid hosts families of chemical species that interact with each other in a massive-parallel fashion. I shall illustrate a range of computational tasks, including computational geometry, implementable by excitation wave fronts in nonlinear active chemical medium. The overview will enable scientists and engineers to understand how vast is the variety of liquid computers and will inspire them to design their own experimental laboratory prototypes.
Too Much Crypto
> We show that many symmetric cryptography primitives would not be less safe with significantly fewer rounds. To support this claim, we review the cryptanalysis progress in the last 20 years, examine the reasons behind the current number of rounds, and analyze the risk of doing fewer rounds. Advocating a rational and scientific approach to round numbers selection, we propose revised number of rounds for AES, BLAKE2, ChaCha, and SHA-3, which offer more consistent security margins across primitives and make them much faster, without increasing the security risk.
Xor Filters: Faster and Smaller Than Bloom Filters
> Among other alternatives, Fan et al. introduced Cuckoo filters which use less space and are faster than Bloom filters. While implementing a Bloom filter is a relatively simple exercise, Cuckoo filters require a bit more engineering.
> Could we do even better while limiting the code to something you can hold in your head?
> It turns out that you can with xor filters. We just published a paper called Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters that will appear in the Journal of Experimental Algorithmics.
> Modern processors are being pushed to perform faster than ever before - and with this comes increases in heat and power consumption. To manage this, many chip manufacturers allow frequency and voltage to be adjusted as and when needed. But more than that, they offer the user the opportunity to modify the frequency and voltage through priviledged software interfaces. With Plundervolt we showed that these software interfaces can be exploited to undermine the system’s security. We were able to corrupt the integrity of Intel SGX on Intel Core processors by controling the voltage when executing enclave computations. This means that even Intel SGX’s memory encryption/authentication technology cannot protect against Plundervolt.
Not sure anyone should care about SGX anymore, all things considered, but for completeness, here’s another one.
TPM—Fail TPM meets Timing and Lattice Attacks
> We discovered timing leakage on Intel firmware-based TPM (fTPM) as well as in STMicroelectronics’ TPM chip. Both exhibit secret-dependent execution times during cryptographic signature generation. While the key should remain safely inside the TPM hardware, we show how this information allows an attacker to recover 256-bit private keys from digital signature schemes based on elliptic curves.
> This research shows that even rigorous testing as required by Common Criteria certification is not flawless and may miss attacks that have explicitly been checked for. The STMicroelectronics TPM chip is Common Criteria certified at EAL4+ for the TPM protection profiles and FIPS 140-2 certified at level 2, while the Intel TPM is certified according to FIPS 140-2. However, the certification has failed to protect the product against an attack that is considered by the protection profile.
Snap: a microkernel approach to host networking
> This paper describes the networking stack, Snap, that has been running in production at Google for the last three years+. It’s been clear for a while that software designed explicitly for the data center environment will increasingly want/need to make different design trade-offs to e.g. general-purpose systems software that you might install on your own machines. But wow, I didn’t think we’d be at the point yet where we’d be abandoning TCP/IP! You need a lot of software engineers and the willingness to rewrite a lot of software to entertain that idea.
> Light Commands is a vulnerability of MEMS microphones that allows attackers to remotely inject inaudible and invisible commands into voice assistants, such as Google assistant, Amazon Alexa, Facebook Portal, and Apple Siri using light.
> In our paper we demonstrate this effect, successfully using light to inject malicious commands into several voice controlled devices such as smart speakers, tablets, and phones across large distances and through glass windows.
An analysis of performance evolution of Linux’s core operations
> When you get into the details I found it hard to come away with any strongly actionable takeaways though. Perhaps the most interesting lesson/reminder is this: it takes a lot of effort to tune a Linux kernel. For example:
> “Red Hat and Suse normally required 6-18 months to optimise the performance an an upstream Linux kernel before it can be released as an enterprise distribution”, and
> “Google’s data center kernel is carefully performance tuned for their workloads. This task is carried out by a team of over 100 engineers, and for each new kernel, the effort can also take 6-18 months.”
Research based on the .NET Runtime
> Over the last few years, I’ve come across more and more research papers based, in some way, on the ‘Common Language Runtime’ (CLR). So armed with Google Scholar and ably assisted by Semantic Scholar, I put together the list below.
Minerva: Lattice attacks strike again
> This page describes our discovery of a group of side-channel vulnerabilities in implementations of ECDSA/EdDSA in programmable smart cards and cryptographic software libraries. Our attack allows for practical recovery of the long-term private key. We have found implementations which leak the bit-length of the scalar during scalar multiplication on an elliptic curve. This leakage might seem minuscule as the bit-length presents a very small amount of information present in the scalar. However, in the case of ECDSA/EdDSA signature generation, the leaked bit-length of the random nonce is enough for full recovery of the private key used after observing a few hundreds to a few thousands of signatures on known messages, due to the application of lattice techniques.
USENIX Security '19 Technical Sessions
> The full Proceedings published by USENIX for the conference are available for download below. Individual papers can also be downloaded from the presentation page.
50 ways to leak your data: an exploration of apps’ circumvention of the Android permissions system
> This paper is a study of Android apps in the wild that leak permission protected data (identifiers which can be used for tracking, and location information), where those apps should not have been able to see such data due to a lack of granted permissions. By detecting such leakage and analysing the responsible apps, the authors uncover a number of covert and side channels in real-world use.
The secret-sharer: evaluating and testing unintended memorization in neural networks
> This is a really important paper for anyone working with language or generative models, and just in general for anyone interested in understanding some of the broader implications and possible unintended consequences of deep learning. There’s also a lovely sense of the human drama accompanying the discoveries that just creeps through around the edges.
> Disclosure of secrets is of particular concern in neural network models that classify or predict sequences of natural language text… even if sensitive or private training data text is very rare, one should assume that well-trained models have paid attention to its precise details…. The users of such models may discover— either by accident or on purpose— that entering certain text prefixes causes the models to output surprisingly revealing text completions.
Final Report on the August 14, 2003 Blackout
> We are pleased to submit the Final Report of the U.S.-Canada Power System Outage Task Force. As directed by you, the Task Force has completed a thorough investigation of the causes of the August 14, 2003 blackout and has recommended actions to minimize the likelihood and scope of similar events in the future.
> The report makes clear that this blackout could have been prevented and that immediate actions must be taken in both the United States and Canada to ensure that our electric system is more reliable. First and foremost, compliance with reliability rules must be made mandatory with substantial penalties for non-compliance.
The Legitimate Vulnerability Market
> Trading of 0-day computer exploits between hackers has been taking place for as long as computer exploits have existed. A black market for these exploits has developed around their illegal use. Recently, a trend has developed toward buying and selling these exploits as a source of legitimate income for security researchers. However, this emerging “0-day market” has some unique aspects that make this particularly difficult to accomplish in a fair manner. These problems, along with possible solutions will be discussed. These issues will be illustrated by following two case studies of attempted sales of 0-day exploits.
> May 6, 2007
3D Ken Burns Effect from a Single Image
> In this paper, we introduce a framework that synthesizes the 3D Ken Burns effect from a single image, supporting both a fully automatic mode and an interactive mode with the user controlling the camera. Our framework first leverages a depth prediction pipeline, which estimates scene depth that is suitable for view synthesis tasks. To address the limitations of existing depth estimation methods such as geometric distortions, semantic distortions, and inaccurate depth boundaries, we develop a semantic-aware neural network for depth prediction, couple its estimate with a segmentation-based depth adjustment process, and employ a refinement neural network that facilitates accurate depth predictions at object boundaries. According to this depth estimate, our framework then maps the input image to a point cloud and synthesizes the resulting video frames by rendering the point cloud from the corresponding camera positions. To address disocclusions while maintaining geometrically and temporally coherent synthesis results, we utilize context-aware color- and depth-inpainting to fill in the missing information in the extreme views of the camera path, thus extending the scene geometry of the point cloud.