Tag Archives: academic papers

Remotely Controlling Touchscreens

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/06/remotely-controlling-touchscreens.html

Researchers have demonstrated controlling touchscreens at a distance, at least in a laboratory setting:

The core idea is to take advantage of the electromagnetic signals to execute basic touch events such as taps and swipes into targeted locations of the touchscreen with the goal of taking over remote control and manipulating the underlying device.

The attack, which works from a distance of up to 40mm, hinges on the fact that capacitive touchscreens are sensitive to EMI, leveraging it to inject electromagnetic signals into transparent electrodes that are built into the touchscreen so as to register them as touch events.

The experimental setup involves an electrostatic gun to generate a strong pulse signal that’s then sent to an antenna to transmit an electromagnetic field to the phone’s touchscreen, thereby causing the electrodes ­ which act as antennas themselves ­ to pick up the EMI.

Paper: “GhostTouch: Targeted Attacks on Touchscreens without Physical Touch“:

Abstract: Capacitive touchscreens have become the primary human-machine interface for personal devices such as smartphones and tablets. In this paper, we present GhostTouch, the first active contactless attack against capacitive touchscreens. GhostTouch uses electromagnetic interference (EMI) to inject fake touch points into a touchscreen without the need to physically touch it. By tuning the parameters of the electromagnetic signal and adjusting the antenna, we can inject two types of basic touch events, taps and swipes, into targeted locations of the touchscreen and control them to manipulate the underlying device. We successfully launch the GhostTouch attacks on nine smartphone models. We can inject targeted taps continuously with a standard deviation of as low as 14.6 x 19.2 pixels from the target area, a delay of less than 0.5s and a distance of up to 40mm. We show the real-world impact of the GhostTouch attacks in a few proof-of-concept scenarios, including answering an eavesdropping phone call, pressing the button, swiping up to unlock, and entering a password. Finally, we discuss potential hardware and software countermeasures to mitigate the attack.

The Limits of Cyber Operations in Wartime

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/05/the-limits-of-cyber-operations-in-wartime.html

Interesting paper by Lennart Maschmeyer: “The Subversive Trilemma: Why Cyber Operations Fall Short of Expectations“:

Abstract: Although cyber conflict has existed for thirty years, the strategic utility of cyber operations remains unclear. Many expect cyber operations to provide independent utility in both warfare and low-intensity competition. Underlying these expectations are broadly shared assumptions that information technology increases operational effectiveness. But a growing body of research shows how cyber operations tend to fall short of their promise. The reason for this shortfall is their subversive mechanism of action. In theory, subversion provides a way to exert influence at lower risks than force because it is secret and indirect, exploiting systems to use them against adversaries. The mismatch between promise and practice is the consequence of the subversive trilemma of cyber operations, whereby speed, intensity, and control are negatively correlated. These constraints pose a trilemma for actors because a gain in one variable tends to produce losses across the other two variables. A case study of the Russo-Ukrainian conflict provides empirical support for the argument. Qualitative analysis leverages original data from field interviews, leaked documents, forensic evidence, and local media. Findings show that the subversive trilemma limited the strategic utility of all five major disruptive cyber operations in this conflict.

Manipulating Machine-Learning Systems through the Order of the Training Data

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/05/manipulating-machine-learning-systems-through-the-order-of-the-training-data.html

Yet another adversarial ML attack:

Most deep neural networks are trained by stochastic gradient descent. Now “stochastic” is a fancy Greek word for “random”; it means that the training data are fed into the model in random order.

So what happens if the bad guys can cause the order to be not random? You guessed it—all bets are off. Suppose for example a company or a country wanted to have a credit-scoring system that’s secretly sexist, but still be able to pretend that its training was actually fair. Well, they could assemble a set of financial data that was representative of the whole population, but start the model’s training on ten rich men and ten poor women drawn from that set ­ then let initialisation bias do the rest of the work.

Does this generalise? Indeed it does. Previously, people had assumed that in order to poison a model or introduce backdoors, you needed to add adversarial samples to the training data. Our latest paper shows that’s not necessary at all. If an adversary can manipulate the order in which batches of training data are presented to the model, they can undermine both its integrity (by poisoning it) and its availability (by causing training to be less effective, or take longer). This is quite general across models that use stochastic gradient descent.

Research paper.

Websites that Collect Your Data as You Type

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/05/websites-that-collect-your-data-as-you-type.html

A surprising number of websites include JavaScript keyloggers that collect everything you type as you type it, not just when you submit a form.

Researchers from KU Leuven, Radboud University, and University of Lausanne crawled and analyzed the top 100,000 websites, looking at scenarios in which a user is visiting a site while in the European Union and visiting a site from the United States. They found that 1,844 websites gathered an EU user’s email address without their consent, and a staggering 2,950 logged a US user’s email in some form. Many of the sites seemingly do not intend to conduct the data-logging but incorporate third-party marketing and analytics services that cause the behavior.

After specifically crawling sites for password leaks in May 2021, the researchers also found 52 websites in which third parties, including the Russian tech giant Yandex, were incidentally collecting password data before submission. The group disclosed their findings to these sites, and all 52 instances have since been resolved.

“If there’s a Submit button on a form, the reasonable expectation is that it does something — that it will submit your data when you click it,” says Güneş Acar, a professor and researcher in Radboud University’s digital security group and one of the leaders of the study. “We were super surprised by these results. We thought maybe we were going to find a few hundred websites where your email is collected before you submit, but this exceeded our expectations by far.”

Research paper.

Friday Squid Blogging: Squid Filmed Changing Color for Camouflage Purposes

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/05/friday-squid-blogging-squid-filmed-changing-color-for-camouflage-purposes.html

Video of oval squid (Sepioteuthis lessoniana) changing color in reaction to their background. The research paper claims this is the first time this has been documented.

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.

Using Pupil Reflection in Smartphone Camera Selfies

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/05/using-pupil-reflection-in-smartphone-camera-selfies.html

Researchers are using the reflection of the smartphone in the pupils of faces taken as selfies to infer information about how the phone is being used:

For now, the research is focusing on six different ways a user can hold a device like a smartphone: with both hands, just the left, or just the right in portrait mode, and the same options in horizontal mode.

It’s not a lot of information, but it’s a start. (It’ll be a while before we can reproduce these results from Blade Runner.)

Research paper.

Video Conferencing Apps Sometimes Ignore the Mute Button

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/04/video-conferencing-apps-sometimes-ignore-the-mute-button.html

New research: “Are You Really Muted?: A Privacy Analysis of Mute Buttons in Video Conferencing Apps“:

Abstract: In the post-pandemic era, video conferencing apps (VCAs) have converted previously private spaces — bedrooms, living rooms, and kitchens — into semi-public extensions of the office. And for the most part, users have accepted these apps in their personal space, without much thought about the permission models that govern the use of their personal data during meetings. While access to a device’s video camera is carefully controlled, little has been done to ensure the same level of privacy for accessing the microphone. In this work, we ask the question: what happens to the microphone data when a user clicks the mute button in a VCA? We first conduct a user study to analyze users’ understanding of the permission model of the mute button. Then, using runtime binary analysis tools, we trace raw audio in many popular VCAs as it traverses the app from the audio driver to the network. We find fragmented policies for dealing with microphone data among VCAs — some continuously monitor the microphone input during mute, and others do so periodically. One app transmits statistics of the audio to its telemetry servers while the app is muted. Using network traffic that we intercept en route to the telemetry server, we implement a proof-of-concept background activity classifier and demonstrate the feasibility of inferring the ongoing background activity during a meeting — cooking, cleaning, typing, etc. We achieved 81.9% macro accuracy on identifying six common background activities using intercepted outgoing telemetry packets when a user is muted.

The paper will be presented at PETS this year.

News article.

Friday Squid Blogging: Squid Skin–Inspired Insulating Material

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/04/friday-squid-blogging-squid-skin-inspired-insulating-material.html

Interesting:

Drawing inspiration from cephalopod skin, engineers at the University of California, Irvine invented an adaptive composite material that can insulate beverage cups, restaurant to-go bags, parcel boxes and even shipping containers.

[…]

“The metal islands in our composite material are next to one another when the material is relaxed and become separated when the material is stretched, allowing for control of the reflection and transmission of infrared light or heat dissipation,” said Gorodetsky. “The mechanism is analogous to chromatophore expansion and contraction in a squid’s skin, which alters the reflection and transmission of visible light.”

Chromatophore size changes help squids communicate and camouflage their bodies to evade predators and hide from prey. Gorodetsky said by mimicking this approach, his team has enabled “tunable thermoregulation” in their material, which can lead to improved energy efficiency and protect sensitive fingers from hot surfaces.

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.

Undetectable Backdoors in Machine-Learning Models

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/04/undetectable-backdoors-in-machine-learning-models.html

New paper: “Planting Undetectable Backdoors in Machine Learning Models“:

Abstract: Given the computational cost and technical expertise required to train machine learning models, users may delegate the task of learning to a service provider. We show how a malicious learner can plant an undetectable backdoor into a classifier. On the surface, such a backdoored classifier behaves normally, but in reality, the learner maintains a mechanism for changing the classification of any input, with only a slight perturbation. Importantly, without the appropriate “backdoor key”, the mechanism is hidden and cannot be detected by any computationally-bounded observer. We demonstrate two frameworks for planting undetectable backdoors, with incomparable guarantees.

First, we show how to plant a backdoor in any model, using digital signature schemes. The construction guarantees that given black-box access to the original model and the backdoored version, it is computationally infeasible to find even a single input where they differ. This property implies that the backdoored model has generalization error comparable with the original model. Second, we demonstrate how to insert undetectable backdoors in models trained using the Random Fourier Features (RFF) learning paradigm or in Random ReLU networks. In this construction, undetectability holds against powerful white-box distinguishers: given a complete description of the network and the training data, no efficient distinguisher can guess whether the model is “clean” or contains a backdoor.

Our construction of undetectable backdoors also sheds light on the related issue of robustness to adversarial examples. In particular, our construction can produce a classifier that is indistinguishable from an “adversarially robust” classifier, but where every input has an adversarial example! In summary, the existence of undetectable backdoors represent a significant theoretical roadblock to certifying adversarial robustness.

EDITED TO ADD (4/20): Cory Doctorow wrote about this as well.

Friday Squid Blogging: Squid Migration and Climate Change

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/04/friday-squid-blogging-squid-migration-and-climate-change.html

New research on the changing migration of the Doryteuthis opalescens as a result of climate change.

News article:

Stanford researchers have solved a mystery about why a species of squid native to California has been found thriving in the Gulf of Alaska about 1,800 miles north of its expected range: climate change.

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.

Friday Squid Blogging: Unexpectedly Low Squid Population in the Arctic

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/03/friday-squid-blogging-unexpectedly-low-squid-population-in-the-arctic.html

Research:

Abstract: The retreating ice cover of the Central Arctic Ocean (CAO) fuels speculations on future fisheries. However, very little is known about the existence of harvestable fish stocks in this 3.3 million­–square kilometer ecosystem around the North Pole. Crossing the Eurasian Basin, we documented an uninterrupted 3170-kilometer-long deep scattering layer (DSL) with zooplankton and small fish in the Atlantic water layer at 100- to 500-meter depth. Diel vertical migration of this central Arctic DSL was lacking most of the year when daily light variation was absent. Unexpectedly, the DSL also contained low abundances of Atlantic cod, along with lanternfish, armhook squid, and Arctic endemic ice cod. The Atlantic cod originated from Norwegian spawning grounds and had lived in Arctic water temperature for up to 6 years. The potential fish abundance was far below commercially sustainable levels and is expected to remain so because of the low productivity of the CAO.

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.

Friday Squid Blog: 328-million-year-old Vampire Squid Ancestor Discovered

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/03/friday-squid-blog-328-million-year-old-vampire-squid-ancestor-discovered.html

A fossilized ancestor of the vampire squid — with ten arms — was discovered and named Syllipsimopodi bideni after President Biden.

Here’s the research paper. Note: Vampire squids are not squids. (Yes, it’s weird.)

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.

Hacking Alexa through Alexa’s Speech

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/03/hacking-alexa-through-alexas-speech.html

An Alexa can respond to voice commands it issues. This can be exploited:

The attack works by using the device’s speaker to issue voice commands. As long as the speech contains the device wake word (usually “Alexa” or “Echo”) followed by a permissible command, the Echo will carry it out, researchers from Royal Holloway University in London and Italy’s University of Catania found. Even when devices require verbal confirmation before executing sensitive commands, it’s trivial to bypass the measure by adding the word “yes” about six seconds after issuing the command. Attackers can also exploit what the researchers call the “FVV,” or full voice vulnerability, which allows Echos to make self-issued commands without temporarily reducing the device volume.

It does require proximate access, though, at least to set the attack up:

It requires only a few seconds of proximity to a vulnerable device while it’s turned on so an attacker can utter a voice command instructing it to pair with an attacker’s Bluetooth-enabled device. As long as the device remains within radio range of the Echo, the attacker will be able to issue commands.

Research paper.

Samsung Encryption Flaw

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/03/samsung-encryption-flaw.html

Researchers have found a major encryption flaw in 100 million Samsung Galaxy phones.

From the abstract:

In this work, we expose the cryptographic design and implementation of Android’s Hardware-Backed Keystore in Samsung’s Galaxy S8, S9, S10, S20, and S21 flagship devices. We reversed-engineered and provide a detailed description of the cryptographic design and code structure, and we unveil severe design flaws. We present an IV reuse attack on AES-GCM that allows an attacker to extract hardware-protected key material, and a downgrade attack that makes even the latest Samsung devices vulnerable to the IV reuse attack. We demonstrate working key extraction attacks on the latest devices. We also show the implications of our attacks on two higher-level cryptographic protocols between the TrustZone and a remote server: we demonstrate a working FIDO2 WebAuthn login bypass and a compromise of Google’s Secure Key Import.

Here are the details:

As we discussed in Section 3, the wrapping key used to encrypt the key blobs (HDK) is derived using a salt value computed by the Keymaster TA. In v15 and v20-s9 blobs, the salt is a deterministic function that depends only on the application ID and application data (and constant strings), which the Normal World client fully controls. This means that for a given application, all key blobs will be encrypted using the same key. As the blobs are encrypted in AES-GCM mode-of-operation, the security of the resulting encryption scheme depends on its IV values never being reused.

Gadzooks. That’s a really embarrassing mistake. GSM needs a new nonce for every encryption. Samsung took a secure cipher mode and implemented it insecurely.

News article.

Decrypting Hive Ransomware Data

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/03/decrypting-hive-ransomware-data.html

Nice piece of research:

Abstract: Among the many types of malicious codes, ransomware poses a major threat. Ransomware encrypts data and demands a ransom in exchange for decryption. As data recovery is impossible if the encryption key is not obtained, some companies suffer from considerable damage, such as the payment of huge amounts of money or the loss of important data. In this paper, we analyzed Hive ransomware, which appeared in June 2021. Hive ransomware has caused immense harm, leading the FBI to issue an alert about it. To minimize the damage caused by Hive Ransomware and to help victims recover their files, we analyzed Hive Ransomware and studied recovery methods. By analyzing the encryption process of Hive ransomware, we confirmed that vulnerabilities exist by using their own encryption algorithm. We have recovered the master key for generating the file encryption key partially, to enable the decryption of data encrypted by Hive ransomware. We recovered 95% of the master key without the attacker’s RSA private key and decrypted the actual infected data. To the best of our knowledge, this is the first successful attempt at decrypting Hive ransomware. It is expected that our method can be used to reduce the damage caused by Hive ransomware.

Here’s the flaw:

The cryptographic vulnerability identified by the researchers concerns the mechanism by which the master keys are generated and stored, with the ransomware strain only encrypting select portions of the file as opposed to the entire contents using two keystreams derived from the master key.

The encryption keystream, which is created from an XOR operation of the two keystreams, is then XORed with the data in alternate blocks to generate the encrypted file. But this technique also makes it possible to guess the keystreams and restore the master key, in turn enabling the decode of encrypted files sans the attacker’s private key.

The researchers said that they were able to weaponize the flaw to devise a method to reliably recover more than 95% of the keys employed during encryption.

Bunnie Huang’s Plausibly Deniable Database

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/02/bunnie-huangs-plausibly-deniable-database.html

Bunnie Huang has created a Plausibly Deniable Database.

Most security schemes facilitate the coercive processes of an attacker because they disclose metadata about the secret data, such as the name and size of encrypted files. This allows specific and enforceable demands to be made: “Give us the passwords for these three encrypted files with names A, B and C, or else…”. In other words, security often focuses on protecting the confidentiality of data, but lacks deniability.

A scheme with deniability would make even the existence of secret files difficult to prove. This makes it difficult for an attacker to formulate a coherent demand: “There’s no evidence of undisclosed data. Should we even bother to make threats?” A lack of evidence makes it more difficult to make specific and enforceable demands.

[…]

Precursor is a device we designed to keep secrets, such as passwords, wallets, authentication tokens, contacts and text messages. We also want it to offer plausible deniability in the face of an attacker that has unlimited access to a physical device, including its root keys, and a set of “broadly known to exist” passwords, such as the screen unlock password and the update signing password. We further assume that an attacker can take a full, low-level snapshot of the entire contents of the FLASH memory, including memory marked as reserved or erased. Finally, we assume that a device, in the worst case, may be subject to repeated, intrusive inspections of this nature.

We created the PDDB (Plausibly Deniable DataBase) to address this threat scenario. The PDDB aims to offer users a real option to plausibly deny the existence of secret data on a Precursor device. This option is strongest in the case of a single inspection. If a device is expected to withstand repeated inspections by the same attacker, then the user has to make a choice between performance and deniability. A “small” set of secrets (relative to the entire disk size, on Precursor that would be 8MiB out of 100MiB total size) can be deniable without a performance impact, but if larger (e.g. 80MiB out of 100MiB total size) sets of secrets must be kept, then archived data needs to be turned over frequently, to foil ciphertext comparison attacks between disk imaging events.

I have been thinking about this sort of thing for many, many years. (Here’s my analysis of one such system.) I have come to realize that the threat model isn’t as simple as Bunnie describes. The goal is to prevent “rubber-hose cryptanalysis,” simply beating the encryption key out of someone. But while a deniable database or file system allows the person to plausibly say that there are no more keys to beat out of them, the perpetrators can never be sure. The value of a normal, undeniable encryption system is that the perpetrators will know when they can stop beating the person — the person can undeniably say that there are no more keys left to reveal.

Breaking 256-bit Elliptic Curve Encryption with a Quantum Computer

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/02/breaking-245-bit-elliptic-curve-encryption-with-a-quantum-computer.html

Researchers have calculated the quantum computer size necessary to break 256-bit elliptic curve public-key cryptography:

Finally, we calculate the number of physical qubits required to break the 256-bit elliptic curve encryption of keys in the Bitcoin network within the small available time frame in which it would actually pose a threat to do so. It would require 317 × 106 physical qubits to break the encryption within one hour using the surface code, a code cycle time of 1 μs, a reaction time of 10 μs, and a physical gate error of 10-3. To instead break the encryption within one day, it would require 13 × 106 physical qubits.

In other words: no time soon. Not even remotely soon. IBM’s largest ever superconducting quantum computer is 127 physical qubits.

Friday Squid Blogging: Are Squid from Another Planet?

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/02/friday-squid-blogging-are-squid-from-another-planet.html

An actually serious scientific journal has published a paper speculating that octopus and squid could be of extraterrestrial origin.

News 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.

Using EM Waves to Detect Malware

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/01/using-em-waves-to-detect-malware.html

I don’t even know what I think about this. Researchers have developed a malware detection system that uses EM waves: “Obfuscation Revealed: Leveraging Electromagnetic Signals for Obfuscated Malware Classification.”

Abstract: The Internet of Things (IoT) is constituted of devices that are exponentially growing in number and in complexity. They use numerous customized firmware and hardware, without taking into consideration security issues, which make them a target for cybercriminals, especially malware authors.

We will present a novel approach of using side channel information to identify the kinds of threats that are targeting the device. Using our approach, a malware analyst is able to obtain precise knowledge about malware type and identity, even in the presence of obfuscation techniques which may prevent static or symbolic binary analysis. We recorded 100,000 measurement traces from an IoT device infected by various in-the-wild malware samples and realistic benign activity. Our method does not require any modification on the target device. Thus, it can be deployed independently from the resources available without any overhead. Moreover, our approach has the advantage that it can hardly be detected and evaded by the malware authors. In our experiments, we were able to predict three generic malware types (and one benign class) with an accuracy of 99.82%. Even more, our results show that we are able to classify altered malware samples with unseen obfuscation techniques during the training phase, and to determine what kind of obfuscations were applied to the binary, which makes our approach particularly useful for malware analysts.

This seems impossible. It’s research, not a commercial product. But it’s fascinating if true.

Friday Squid Blogging: Deep-Dwelling Squid

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2021/12/friday-squid-blogging-deep-dwelling-squid.html

We have discovered a squid — (Oegopsida, Magnapinnidae, Magnapinna sp.) — that lives at 6,000 meters deep.

:They’re really weird,” says Vecchione. “They drift along with their arms spread out and these really long, skinny, spaghetti-like extensions dangling down underneath them.” Microscopic suckers on those filaments enable the squid to capture their prey.

But the squid that Jamieson and Vecchione saw in the footage captured 6,212 meters below the ocean’s surface is a small one. They estimate that its mantle measured 10 centimeters long — ­about a third the size of the largest-known magnapinnid. And the characteristically long extensions observed on other magnapinnids were nowhere to be seen in the video. That could mean, says Vecchione, that this bigfin squid was a juvenile.

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.