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Fluid Notarization: Verifiable Evolution of Concurrently Edited Structured Documents
Fluid Notarization anchors delta-CRDT change graphs on blockchain, providing verifiable provenance for concurrently edited documents, demonstrated on collaborative electronic health records.
The paper introduces Fluid Notarization, a paradigm that notarizes the evolution of collaboratively edited structured documents rather than isolated snapshots. It builds on Melda, a JSON-native delta-CRDT representing changes as compact content-addressed deltas linked by causal dependencies, with blockchain notarization reduced to recording identifiers of evolution artifacts while synchronization, reconstruction, and conflict resolution remain off-chain. The architecture combines deterministic CRDT convergence with independently auditable proof-of-existence, provenance, and publication evidence, validated through a prototype based on collaboratively edited electronic health records.
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Why Johnny Can't Encrypt: A Usability Evaluation of PGP 5.0 (1999)
Seminal 1999 USENIX study finds most novice users cannot correctly sign and encrypt email with PGP 5.0 in 90 minutes.
Whitten and Tygar's USENIX Security Symposium paper evaluates whether cryptography novices can use PGP 5.0 effectively, using cognitive walkthrough analysis and a laboratory user test. The majority of test participants failed to successfully sign and encrypt a message within 90 minutes, despite PGP 5.0 having a well-regarded graphical interface. The authors argue that security requires usability standards beyond those of general consumer software and propose domain-specific UI design principles for security. The paper is a foundational reference in usable security research.
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PHAT: PHotonic Accelerator for TFHE
PHAT photonic accelerator using optically addressed phase-change memory speeds TFHE bootstrapping FFTs 2.14x-5.10x over the prior ASIC accelerator.
Researchers propose PHAT, an electro-photonic accelerator for TFHE fully homomorphic encryption built on optically addressed phase-change memory (OPCM) processing-in-memory. The architecture adds OPCM-based FFT units, a twiddle-stationary dataflow, and a scheduling mechanism to maximize FFT utilization for TFHE bootstrapping. It achieves 2.14x-5.10x speedups across four real-world TFHE workloads versus the state-of-the-art ASIC accelerator, improving feasibility of privacy-preserving computation in the cloud.
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LG TV shown scanning LAN for third-party phones and other devices
Security researchers showed LG OLED TVs scan local networks and collect nearby device details, raising privacy concerns for TV owners.
Gamers Nexus, working with Level1Techs and security researchers, used packet captures and Wireshark to show that LG TVs, including the $2,500 OLED65G3PUA and the G5 OLED, scan the local network for phones, smartwatches, and other unconnected devices. The TV's firmware can identify the user's IP address, nearby Wi-Fi network names and signal strength, neighboring channel numbers, and internal IP addresses of other devices. LG Ad Solutions marketing claims reach of 363 million 'addressable secondary devices' in the US, and LG says the scanning supports device connectivity and smart home features. It remains unclear whether the collected data is transmitted to LG for purposes beyond advertising.
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Automobile Camouflage to Hide from Flock Cameras
Schneier on Security highlights a printed vehicle-camouflage pattern tested to defeat Flock surveillance cameras and Axon body cameras.
The post discusses covering cars with printed patterns designed to fool Flock automated license-plate recognition software, with testing reportedly done against Flock and Axon body cameras. Reader comments question effectiveness against other ALPR vendors, Flock's RF MAC-address upgrade, and whether such camouflage might become regulated. The page also contains off-topic comment threads about anti-bot over-blocking and privacy.
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Trends in Web Threats: Attackers Were More Active During Holiday Season
Unit 42 tracked 533,000 malicious landing URL incidents from October-December 2021, showing web threats peaked during the holiday shopping season.
Unit 42 detected 533,452 malicious landing URL incidents (120,753 unique) and 2,906,875 malicious host URL incidents (165,255 unique) from October through December 2021. Threat activity peaked in November, likely tied to Black Friday in the United States, United Kingdom, and Germany. Most malicious domains appeared to originate in the United States, followed by Russia and Germany. Personal sites, blogs, business sites, and shopping sites were the most common apparently benign entry points for attacks.
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Automatically Detecting DNS Hijacking in Passive DNS
Unit 42's machine learning pipeline detected 6,729 DNS hijacking events between March and September 2024, hitting political parties, ISPs, and universities.
Unit 42 processes roughly 167 million new DNS records daily and applies a machine learning model using 74 features over 169 TB of passive DNS and geolocation data to flag hijacked domains. From March to September 2024 the pipeline screened over 29 billion records and classified 6,729 as DNS hijacking, averaging 38 detections per day; a new model detects hijacks in customer traffic within about 10 minutes. Notable cases include a Hungarian political party's hijacked domain, defacement of a large utility company and ISP, and university and research center domains repurposed for illicit gambling. DNS hijacking typically relies on stolen registrar or DNS provider credentials or cache poisoning, enabling MitM attacks, phishing, drive-by downloads, and scams.
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