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academic papers algorithms backdoors Cryptanalysis Encryption Intelwars

Intentional Flaw in GPRS Encryption Algorithm GEA-1

General Packet Radio Service (GPRS) is a mobile data standard that was widely used in the early 2000s. The first encryption algorithm for that standard was GEA-1, a stream cipher built on three linear-feedback shift registers and a non-linear combining function. Although the algorithm has a 64-bit key, the effective key length is only 40 bits, due to “an exceptional interaction of the deployed LFSRs and the key initialization, which is highly unlikely to occur by chance.”

GEA-1 was designed by the European Telecommunications Standards Institute in 1998. ETSI was — and maybe still is — under the auspices of SOGIS: the Senior Officials Group, Information Systems Security. That’s basically the intelligence agencies of the EU countries.

Details are in the paper: “Cryptanalysis of the GPRS Encryption Algorithms GEA-1 and GEA-2.” GEA-2 does not have the same flaw, although the researchers found a practical attack with enough keystream.

Hacker News thread.

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academic papers deep fake Intelwars tamper detection

Detecting Deepfake Picture Editing

“Markpainting” is a clever technique to watermark photos in such a way that makes it easier to detect ML-based manipulation:

An image owner can modify their image in subtle ways which are not themselves very visible, but will sabotage any attempt to inpaint it by adding visible information determined in advance by the markpainter.

One application is tamper-resistant marks. For example, a photo agency that makes stock photos available on its website with copyright watermarks can markpaint them in such a way that anyone using common editing software to remove a watermark will fail; the copyright mark will be markpainted right back. So watermarks can be made a lot more robust.

Here’s the paper: “Markpainting: Adversarial Machine Learning Meets Inpainting,” by David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, and Ross Anderson.

Abstract: Inpainting is a learned interpolation technique that is based on generative modeling and used to populate masked or missing pieces in an image; it has wide applications in picture editing and retouching. Recently, inpainting started being used for watermark removal, raising concerns. In this paper we study how to manipulate it using our markpainting technique. First, we show how an image owner with access to an inpainting model can augment their image in such a way that any attempt to edit it using that model will add arbitrary visible information. We find that we can target multiple different models simultaneously with our technique. This can be designed to reconstitute a watermark if the editor had been trying to remove it. Second, we show that our markpainting technique is transferable to models that have different architectures or were trained on different datasets, so watermarks created using it are difficult for adversaries to remove. Markpainting is novel and can be used as a manipulation alarm that becomes visible in the event of inpainting.

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academic papers DISINFORMATION Intelwars national security policy

Information Flows and Democracy

Henry Farrell and I published a paper on fixing American democracy: “Rechanneling Beliefs: How Information Flows Hinder or Help Democracy.”

It’s much easier for democratic stability to break down than most people realize, but this doesn’t mean we must despair over the future. It’s possible, though very difficult, to back away from our current situation towards one of greater democratic stability. This wouldn’t entail a restoration of a previous status quo. Instead, it would recognize that the status quo was less stable than it seemed, and a major source of the tensions that have started to unravel it. What we need is a dynamic stability, one that incorporates new forces into American democracy rather than trying to deny or quash them.

This paper is our attempt to explain what this might mean in practice. We start by analyzing the problem and explaining more precisely why a breakdown in public consensus harms democracy. We then look at how these beliefs are being undermined by three feedback loops, in which anti-democratic actions and anti-democratic beliefs feed on each other. Finally, we explain how these feedback loops might be redirected so as to sustain democracy rather than undermining it.

To be clear: redirecting these and other energies in more constructive ways presents enormous challenges, and any plausible success will at best be untidy and provisional. But, almost by definition, that’s true of any successful democratic reforms where people of different beliefs and values need to figure out how to coexist. Even when it’s working well, democracy is messy. Solutions to democratic breakdowns are going to be messy as well.

This is part of our series of papers looking at democracy as an information system. The first paper was “Common-Knowledge Attacks on Democracy.”

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academic papers Cameras Intelwars Squid

Friday Squid Blogging: Underwater Cameras for Observing Squid

Interesting research paper.

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.

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academic papers Hardware Intelwars patching vulnerabilities

New Spectre-Like Attacks

There’s new research that demonstrates security vulnerabilities in all of the AMD and Intel chips with micro-op caches, including the ones that were specifically engineered to be resistant to the Spectre/Meltdown attacks of three years ago.

Details:

The new line of attacks exploits the micro-op cache: an on-chip structure that speeds up computing by storing simple commands and allowing the processor to fetch them quickly and early in the speculative execution process, as the team explains in a writeup from the University of Virginia. Even though the processor quickly realizes its mistake and does a U-turn to go down the right path, attackers can get at the private data while the processor is still heading in the wrong direction.

It seems really difficult to exploit these vulnerabilities. We’ll need some more analysis before we understand what we have to patch and how.

More news.

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academic papers Intelwars sensors Wi-Fi wireless

Wi-Fi Devices as Physical Object Sensors

The new 802.11bf standard will turn Wi-Fi devices into object sensors:

In three years or so, the Wi-Fi specification is scheduled to get an upgrade that will turn wireless devices into sensors capable of gathering data about the people and objects bathed in their signals.

“When 802.11bf will be finalized and introduced as an IEEE standard in September 2024, Wi-Fi will cease to be a communication-only standard and will legitimately become a full-fledged sensing paradigm,” explains Francesco Restuccia, assistant professor of electrical and computer engineering at Northeastern University, in a paper summarizing the state of the Wi-Fi Sensing project (SENS) currently being developed by the Institute of Electrical and Electronics Engineers (IEEE).

SENS is envisioned as a way for devices capable of sending and receiving wireless data to use Wi-Fi signal interference differences to measure the range, velocity, direction, motion, presence, and proximity of people and objects.

More detail in the article. Security and privacy controls are still to be worked out, which means that there probably won’t be any.

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academic papers Intelwars keys locks physical security Smartphones

Determining Key Shape from Sound

It’s not yet very accurate or practical, but under ideal conditions it is possible to figure out the shape of a house key by listening to it being used.

Listen to Your Key: Towards Acoustics-based Physical Key Inference

Abstract: Physical locks are one of the most prevalent mechanisms for securing objects such as doors. While many of these locks are vulnerable to lock-picking, they are still widely used as lock-picking requires specific training with tailored instruments, and easily raises suspicion. In this paper, we propose SpiKey, a novel attack that significantly lowers the bar for an attacker as opposed to the lock-picking attack, by requiring only the use of a smartphone microphone to infer the shape of victim’s key, namely bittings(or cut depths) which form the secret of a key. When a victim inserts his/her key into the lock, the emitted sound is captured by the attacker’s microphone.SpiKey leverages the time difference between audible clicks to ultimately infer the bitting information, i.e., shape of the physical key. As a proof-of-concept, we provide a simulation, based on real-world recordings, and demonstrate a significant reduction in search spacefrom a pool of more than 330 thousand keys to three candidate keys for the most frequent case.

Scientific American podcast:

The strategy is a long way from being viable in the real world. For one thing, the method relies on the key being inserted at a constant speed. And the audio element also poses challenges like background noise.

Boing Boing post.

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academic papers Apple Bluetooth Crowdsourcing de-anonymization Intelwars privacy reverse-engineering security analysis tracking

Security Analysis of Apple’s “Find My…” Protocol

Interesting research: “Who Can Find My Devices? Security and Privacy of Apple’s Crowd-Sourced Bluetooth Location Tracking System“:

Abstract: Overnight, Apple has turned its hundreds-of-million-device ecosystem into the world’s largest crowd-sourced location tracking network called offline finding (OF). OF leverages online finder devices to detect the presence of missing offline devices using Bluetooth and report an approximate location back to the owner via the Internet. While OF is not the first system of its kind, it is the first to commit to strong privacy goals. In particular, OF aims to ensure finder anonymity, untrackability of owner devices, and confidentiality of location reports. This paper presents the first comprehensive security and privacy analysis of OF. To this end, we recover the specifications of the closed-source OF protocols by means of reverse engineering. We experimentally show that unauthorized access to the location reports allows for accurate device tracking and retrieving a user’s top locations with an error in the order of 10 meters in urban areas. While we find that OF’s design achieves its privacy goals, we discover two distinct design and implementation flaws that can lead to a location correlation attack and unauthorized access to the location history of the past seven days, which could deanonymize users. Apple has partially addressed the issues following our responsible disclosure. Finally, we make our research artifacts publicly available.

There is also code available on GitHub, which allows arbitrary Bluetooth devices to be tracked via Apple’s Find My network.

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academic papers Intelwars Metadata security analysis

Metadata Left in Security Agency PDFs

Really interesting research:

“Exploitation and Sanitization of Hidden Data in PDF Files”

Abstract: Organizations publish and share more and more electronic documents like PDF files. Unfortunately, most organizations are unaware that these documents can compromise sensitive information like authors names, details on the information system and architecture. All these information can be exploited easily by attackers to footprint and later attack an organization. In this paper, we analyze hidden data found in the PDF files published by an organization. We gathered a corpus of 39664 PDF files published by 75 security agencies from 47 countries. We have been able to measure the quality and quantity of information exposed in these PDF files. It can be effectively used to find weak links in an organization: employees who are running outdated software. We have also measured the adoption of PDF files sanitization by security agencies. We identified only 7 security agencies which sanitize few of their PDF files before publishing. Unfortunately, we were still able to find sensitive information within 65% of these sanitized PDF files. Some agencies are using weak sanitization techniques: it requires to remove all the hidden sensitive information from the file and not just to remove the data at the surface. Security agencies need to change their sanitization methods.

Short summary: no one is doing great.

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academic papers Fortuna Intelwars random numbers

Fast Random Bit Generation

Science has a paper (and commentary) on generating 250 random terabits per second with a laser. I don’t know how cryptographically secure they are, but that can be cleaned up with something like Fortuna.

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academic papers Adobe hacking Intelwars signatures

Hacking Digitally Signed PDF Files

Interesting paper: “Shadow Attacks: Hiding and Replacing Content in Signed PDFs“:

Abstract: Digitally signed PDFs are used in contracts and invoices to guarantee the authenticity and integrity of their content. A user opening a signed PDF expects to see a warning in case of any modification. In 2019, Mladenov et al. revealed various parsing vulnerabilities in PDF viewer implementations.They showed attacks that could modify PDF documents without invalidating the signature. As a consequence, affected vendors of PDF viewers implemented countermeasures preventing all attacks.

This paper introduces a novel class of attacks, which we call shadow attacks. The shadow attacks circumvent all existing countermeasures and break the integrity protection of digitally signed PDFs. Compared to previous attacks, the shadow attacks do not abuse implementation issues in a PDF viewer. In contrast, shadow attacks use the enormous flexibility provided by the PDF specification so that shadow documents remain standard-compliant. Since shadow attacks abuse only legitimate features,they are hard to mitigate.

Our results reveal that 16 (including Adobe Acrobat and Foxit Reader) of the 29 PDF viewers tested were vulnerable to shadow attacks. We introduce our tool PDF-Attacker which can automatically generate shadow attacks. In addition, we implemented PDF-Detector to prevent shadow documents from being signed or forensically detect exploits after being applied to signed PDFs.

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academic papers browsers Intelwars tracking

Browser Tracking Using Favicons

Interesting research on persistent web tracking using favicons. (For those who don’t know, favicons are those tiny icons that appear in browser tabs next to the page name.)

Abstract: The privacy threats of online tracking have garnered considerable attention in recent years from researchers and practitioners alike. This has resulted in users becoming more privacy-cautious and browser vendors gradually adopting countermeasures to mitigate certain forms of cookie-based and cookie-less tracking. Nonetheless, the complexity and feature-rich nature of modern browsers often lead to the deployment of seemingly innocuous functionality that can be readily abused by adversaries. In this paper we introduce a novel tracking mechanism that misuses a simple yet ubiquitous browser feature: favicons. In more detail, a website can track users across browsing sessions by storing a tracking identifier as a set of entries in the browser’s dedicated favicon cache, where each entry corresponds to a specific subdomain. In subsequent user visits the website can reconstruct the identifier by observing which favicons are requested by the browser while the user is automatically and rapidly redirected through a series of subdomains. More importantly, the caching of favicons in modern browsers exhibits several unique characteristics that render this tracking vector particularly powerful, as it is persistent (not affected by users clearing their browser data), non-destructive (reconstructing the identifier in subsequent visits does not alter the existing combination of cached entries), and even crosses the isolation of the incognito mode. We experimentally evaluate several aspects of our attack, and present a series of optimization techniques that render our attack practical. We find that combining our favicon-based tracking technique with immutable browser-fingerprinting attributes that do not change over time allows a website to reconstruct a 32-bit tracking identifier in 2 seconds. Furthermore,our attack works in all major browsers that use a favicon cache, including Chrome and Safari. Due to the severity of our attack we propose changes to browsers’ favicon caching behavior that can prevent this form of tracking, and have disclosed our findings to browser vendors who are currently exploring appropriate mitigation strategies.

Another researcher has implemented this proof of concept:

Strehle has set up a website that demonstrates how easy it is to track a user online using a favicon. He said it’s for research purposes, has released his source code online, and detailed a lengthy explanation of how supercookies work on his website.

The scariest part of the favicon vulnerability is how easily it bypasses traditional methods people use to keep themselves private online. According to Strehle, the supercookie bypasses the “private” mode of Chrome, Safari, Edge, and Firefox. Clearing your cache, surfing behind a VPN, or using an ad-blocker won’t stop a malicious favicon from tracking you.

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academic papers Intelwars Squid

Friday Squid Blogging: Squids Don’t Like Pile-Driving Noises

New research:

Pile driving occurs during construction of marine platforms, including offshore windfarms, producing intense sounds that can adversely affect marine animals. We quantified how a commercially and economically important squid (Doryteuthis pealeii: Lesueur 1821) responded to pile driving sounds recorded from a windfarm installation within this species’ habitat. Fifteen-minute portions of these sounds were played to 16 individual squid. A subset of animals (n = 11) received a second exposure after a 24-h rest period. Body pattern changes, inking, jetting, and startle responses were observed and nearly all squid exhibited at least one response. These responses occurred primarily during the first 8 impulses and diminished quickly, indicating potential rapid, short-term habituation. Similar response rates were seen 24-h later, suggesting squid re-sensitized to the noise. Increased tolerance of anti-predatory alarm responses may alter squids’ ability to deter and evade predators. Noise exposure may also disrupt normal intraspecific communication and ecologically relevant responses to sound.

Press release.

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.

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academic papers Cryptography cyberattack Cybersecurity Data Protection Intelwars

Extracting Personal Information from Large Language Models Like GPT-2

Researchers have been able to find all sorts of personal information within GPT-2. This information was part of the training data, and can be extracted with the right sorts of queries.

Paper: “Extracting Training Data from Large Language Models.”

Abstract: It has become common to publish large (billion parameter) language models that have been trained on private datasets. This paper demonstrates that in such settings, an adversary can perform a training data extraction attack to recover individual training examples by querying the language model.

We demonstrate our attack on GPT-2, a language model trained on scrapes of the public Internet, and are able to extract hundreds of verbatim text sequences from the model’s training data. These extracted examples include (public) personally identifiable information (names, phone numbers, and email addresses), IRC conversations, code, and 128-bit UUIDs. Our attack is possible even though each of the above sequences are included in just one document in the training data.

We comprehensively evaluate our extraction attack to understand the factors that contribute to its success. For example, we find that larger models are more vulnerable than smaller models. We conclude by drawing lessons and discussing possible safeguards for training large language models.

From a blog post:

We generated a total of 600,000 samples by querying GPT-2 with three different sampling strategies. Each sample contains 256 tokens, or roughly 200 words on average. Among these samples, we selected 1,800 samples with abnormally high likelihood for manual inspection. Out of the 1,800 samples, we found 604 that contain text which is reproduced verbatim from the training set.

The rest of the blog post discusses the types of data they found.

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academic papers Eavesdropping Intelwars privacy side-channel attacks Surveillance

Eavesdropping on Phone Taps from Voice Assistants

The microphones on voice assistants are very sensitive, and can snoop on all sorts of data:

In Hey Alexa what did I just type? we show that when sitting up to half a meter away, a voice assistant can still hear the taps you make on your phone, even in presence of noise. Modern voice assistants have two to seven microphones, so they can do directional localisation, just as human ears do, but with greater sensitivity. We assess the risk and show that a lot more work is needed to understand the privacy implications of the always-on microphones that are increasingly infesting our work spaces and our homes.

From the paper:

Abstract: Voice assistants are now ubiquitous and listen in on our everyday lives. Ever since they became commercially available, privacy advocates worried that the data they collect can be abused: might private conversations be extracted by third parties? In this paper we show that privacy threats go beyond spoken conversations and include sensitive data typed on nearby smartphones. Using two different smartphones and a tablet we demonstrate that the attacker can extract PIN codes and text messages from recordings collected by a voice assistant located up to half a meter away. This shows that remote keyboard-inference attacks are not limited to physical keyboards but extend to virtual keyboards too. As our homes become full of always-on microphones, we need to work through the implications.

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academic papers Intelwars Squid

Friday Squid Blogging: Newly Identified Ichthyosaur Species Probably Ate Squid

This is a deep-diving species that “fed on small prey items such as squid.”

Academic paper.

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.

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academic papers anonymity DNS https Intelwars Protocols

Oblivious DNS-over-HTTPS

This new protocol, called Oblivious DNS-over-HTTPS (ODoH), hides the websites you visit from your ISP.

Here’s how it works: ODoH wraps a layer of encryption around the DNS query and passes it through a proxy server, which acts as a go-between the internet user and the website they want to visit. Because the DNS query is encrypted, the proxy can’t see what’s inside, but acts as a shield to prevent the DNS resolver from seeing who sent the query to begin with.

IETF memo.

The paper:

Abstract: The Domain Name System (DNS) is the foundation of a human-usable Internet, responding to client queries for host-names with corresponding IP addresses and records. Traditional DNS is also unencrypted, and leaks user information to network operators. Recent efforts to secure DNS using DNS over TLS (DoT) and DNS over HTTPS (DoH) havebeen gaining traction, ostensibly protecting traffic and hiding content from on-lookers. However, one of the criticisms ofDoT and DoH is brought to bear by the small number of large-scale deployments (e.g., Comcast, Google, Cloudflare): DNS resolvers can associate query contents with client identities in the form of IP addresses. Oblivious DNS over HTTPS (ODoH) safeguards against this problem. In this paper we ask what it would take to make ODoH practical? We describe ODoH, a practical DNS protocol aimed at resolving this issue by both protecting the client’s content and identity. We implement and deploy the protocol, and perform measurements to show that ODoH has comparable performance to protocols like DoH and DoT which are gaining widespread adoption,while improving client privacy, making ODoH a practical privacy enhancing replacement for the usage of DNS.

Slashdot thread.

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academic papers Cryptography Encryption Intelwars

Indistinguishability Obfuscation

Quanta magazine recently published a breathless article on indistinguishability obfuscation — calling it the “‘crown jewel’ of cryptography” — and saying that it had finally been achieved, based on a recently published paper. I want to add some caveats to the discussion.

Basically, obfuscation makes a computer program “unintelligible” by performing its functionality. Indistinguishability obfuscation is more relaxed. It just means that two different programs that perform the same functionality can’t be distinguished from each other. A good definition is in this paper.

This is a pretty amazing theoretical result, and one to be excited about. We can now do obfuscation, and we can do it using assumptions that make real-world sense. The proofs are kind of ugly, but that’s okay — it’s a start. What it means in theory is that we have a fundamental theoretical result that we can use to derive a whole bunch of other cryptographic primitives.

But — and this is a big one — this result is not even remotely close to being practical. We’re talking multiple days to perform pretty simple calculations, using massively large blocks of computer code. And this is likely to remain true for a very long time. Unless researchers increase performance by many orders of magnitude, nothing in the real world will make use of this work anytime soon.

But but, consider fully homomorphic encryption. It, too, was initially theoretically interesting and completely impractical. And now, after decades of work, it seems to be almost just-barely maybe approaching practically useful. This could very well be on the same trajectory, and perhaps in twenty to thirty years we will be celebrating this early theoretical result as the beginning of a new theory of cryptography.

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academic papers Blockchain Cybersecurity Intelwars national security policy Voting

On Blockchain Voting

Blockchain voting is a spectacularly dumb idea for a whole bunch of reasons. I have generally quoted Matt Blaze:

Why is blockchain voting a dumb idea? Glad you asked.

For starters:

  • It doesn’t solve any problems civil elections actually have.
  • It’s basically incompatible with “software independence”, considered an essential property.
  • It can make ballot secrecy difficult or impossible.

I’ve also quoted this XKCD cartoon.

But now I have this excellent paper from MIT:

“Going from Bad to Worse: From Internet Voting to Blockchain Voting,” by Sunoo Park, Harvard Michael Specter, Neha Narula, and Ronald L. Rivest

Abstract: Voters are understandably concerned about election security. News reports of possible election interference by foreign powers, of unauthorized voting, of voter disenfranchisement, and of technological failures call into question the integrity of elections worldwide.

This article examines the suggestions that “voting over the Internet” or “voting on the blockchain” would increase election security, and finds such claims to be wanting and misleading. While current election systems are far from perfect, Internet- and blockchain-based voting would greatly increase the risk of undetectable, nation-scale election failures.

Online voting may seem appealing: voting from a computer or smart phone may seem convenient and accessible. However, studies have been inconclusive, showing that online voting may have little to no effect on turnout in practice, and it may even increase disenfranchisement. More importantly: given the current state of computer security, any turnout increase derived from with Internet- or blockchain-based voting would come at the cost of losing meaningful assurance that votes have been counted as they were cast, and not undetectably altered or discarded. This state of affairs will continue as long as standard tactics such as malware, zero days, and denial-of-service attacks continue to be effective.

This article analyzes and systematizes prior research on the security risks of online and electronic voting, and show that not only do these risks persist in blockchain-based voting systems, but blockchains may introduce additional problems for voting systems. Finally, we suggest questions for critically assessing security risks of new voting system proposals.

You may have heard of Voatz, which uses blockchain for voting. It’s an insecure mess. And this is my general essay on blockchain. Short summary: it’s completely useless.

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academic papers behavioral detection e-mail Intelwars Phishing Scams

Detecting Phishing Emails

Research paper: Rick Wash, “How Experts Detect Phishing Scam Emails“:

Abstract: Phishing scam emails are emails that pretend to be something they are not in order to get the recipient of the email to undertake some action they normally would not. While technical protections against phishing reduce the number of phishing emails received, they are not perfect and phishing remains one of the largest sources of security risk in technology and communication systems. To better understand the cognitive process that end users can use to identify phishing messages, I interviewed 21 IT experts about instances where they successfully identified emails as phishing in their own inboxes. IT experts naturally follow a three-stage process for identifying phishing emails. In the first stage, the email recipient tries to make sense of the email, and understand how it relates to other things in their life. As they do this, they notice discrepancies: little things that are “off” about the email. As the recipient notices more discrepancies, they feel a need for an alternative explanation for the email. At some point, some feature of the email — usually, the presence of a link requesting an action — triggers them to recognize that phishing is a possible alternative explanation. At this point, they become suspicious (stage two) and investigate the email by looking for technical details that can conclusively identify the email as phishing. Once they find such information, then they move to stage three and deal with the email by deleting it or reporting it. I discuss ways this process can fail, and implications for improving training of end users about phishing.

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academic papers Intelwars side-channel attacks Video

Determining What Video Conference Participants Are Typing from Watching Shoulder Movements

Accuracy isn’t great, but that it can be done at all is impressive.

Murtuza Jadiwala, a computer science professor heading the research project, said his team was able to identify the contents of texts by examining body movement of the participants. Specifically, they focused on the movement of their shoulders and arms to extrapolate the actions of their fingers as they typed.

Given the widespread use of high-resolution web cams during conference calls, Jadiwala was able to record and analyze slight pixel shifts around users’ shoulders to determine if they were moving left or right, forward or backward. He then created a software program that linked the movements to a list of commonly used words. He says the “text inference framework that uses the keystrokes detected from the video … predict[s] words that were most likely typed by the target user. We then comprehensively evaluate[d] both the keystroke/typing detection and text inference frameworks using data collected from a large number of participants.”

In a controlled setting, with specific chairs, keyboards and webcam, Jadiwala said he achieved an accuracy rate of 75 percent. However, in uncontrolled environments, accuracy dropped to only one out of every five words being correctly identified.

Other factors contribute to lower accuracy levels, he said, including whether long sleeve or short sleeve shirts were worn, and the length of a user’s hair. With long hair obstructing a clear view of the shoulders, accuracy plummeted.

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academic papers business of security Courts Intelwars Risk Assessment risks

The Legal Risks of Security Research

Sunoo Park and Kendra Albert have published “A Researcher’s Guide to Some Legal Risks of Security Research.”

From a summary:

Such risk extends beyond anti-hacking laws, implicating copyright law and anti-circumvention provisions (DMCA §1201), electronic privacy law (ECPA), and cryptography export controls, as well as broader legal areas such as contract and trade secret law.

Our Guide gives the most comprehensive presentation to date of this landscape of legal risks, with an eye to both legal and technical nuance. Aimed at researchers, the public, and technology lawyers alike, its aims both to provide pragmatic guidance to those navigating today’s uncertain legal landscape, and to provoke public debate towards future reform.

Comprehensive, and well worth reading.

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academic papers cars Intelwars machine learning spoofing

Split-Second Phantom Images Fool Autopilots

Researchers are tricking autopilots by inserting split-second images into roadside billboards.

Researchers at Israel’s Ben Gurion University of the Negev … previously revealed that they could use split-second light projections on roads to successfully trick Tesla’s driver-assistance systems into automatically stopping without warning when its camera sees spoofed images of road signs or pedestrians. In new research, they’ve found they can pull off the same trick with just a few frames of a road sign injected on a billboard’s video. And they warn that if hackers hijacked an internet-connected billboard to carry out the trick, it could be used to cause traffic jams or even road accidents while leaving little evidence behind.

[…]

In this latest set of experiments, the researchers injected frames of a phantom stop sign on digital billboards, simulating what they describe as a scenario in which someone hacked into a roadside billboard to alter its video. They also upgraded to Tesla’s most recent version of Autopilot known as HW3. They found that they could again trick a Tesla or cause the same Mobileye device to give the driver mistaken alerts with just a few frames of altered video.

The researchers found that an image that appeared for 0.42 seconds would reliably trick the Tesla, while one that appeared for just an eighth of a second would fool the Mobileye device. They also experimented with finding spots in a video frame that would attract the least notice from a human eye, going so far as to develop their own algorithm for identifying key blocks of pixels in an image so that a half-second phantom road sign could be slipped into the “uninteresting” portions.

The paper:

Abstract: In this paper, we investigate “split-second phantom attacks,” a scientific gap that causes two commercial advanced driver-assistance systems (ADASs), Telsa Model X (HW 2.5 and HW 3) and Mobileye 630, to treat a depthless object that appears for a few milliseconds as a real obstacle/object. We discuss the challenge that split-second phantom attacks create for ADASs. We demonstrate how attackers can apply split-second phantom attacks remotely by embedding phantom road signs into an advertisement presented on a digital billboard which causes Tesla’s autopilot to suddenly stop the car in the middle of a road and Mobileye 630 to issue false notifications. We also demonstrate how attackers can use a projector in order to cause Tesla’s autopilot to apply the brakes in response to a phantom of a pedestrian that was projected on the road and Mobileye 630 to issue false notifications in response to a projected road sign. To counter this threat, we propose a countermeasure which can determine whether a detected object is a phantom or real using just the camera sensor. The countermeasure (GhostBusters) uses a “committee of experts” approach and combines the results obtained from four lightweight deep convolutional neural networks that assess the authenticity of an object based on the object’s light, context, surface, and depth. We demonstrate our countermeasure’s effectiveness (it obtains a TPR of 0.994 with an FPR of zero) and test its robustness to adversarial machine learning attacks.

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academic papers Authentication Intelwars Passwords Risk Assessment risks usability

On Risk-Based Authentication

Interesting usability study: “More Than Just Good Passwords? A Study on Usability and Security Perceptions of Risk-based Authentication“:

Abstract: Risk-based Authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional features during login, and when observed feature values differ significantly from previously seen ones, users have to provide additional authentication factors such as a verification code. RBA has the potential to offer more usable authentication, but the usability and the security perceptions of RBA are not studied well.

We present the results of a between-group lab study (n=65) to evaluate usability and security perceptions of two RBA variants, one 2FA variant, and password-only authentication. Our study shows with significant results that RBA is considered to be more usable than the studied 2FA variants, while it is perceived as more secure than password-only authentication in general and comparably se-cure to 2FA in a variety of application types. We also observed RBA usability problems and provide recommendations for mitigation.Our contribution provides a first deeper understanding of the users’perception of RBA and helps to improve RBA implementations for a broader user acceptance.

Paper’s website. I’ve blogged about risk-based authentication before.

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