14320 matches found
Intelligent Detection of Non-Essential IoT Traffic on the Home Gateway
The rapid expansion of Internet of Things IoT devices, particularly in smart home environments, has introduced considerable security and privacy concerns due to their persistent connectivity and interaction with cloud services. Despite advancements in IoT security, effective privacy measures rema...
On the Price of Differential Privacy for Hierarchical Clustering
Hierarchical clustering is a fundamental unsupervised machine learning task with the aim of organizing data into a hierarchy of clusters. Many applications of hierarchical clustering involve sensitive user information, therefore motivating recent studies on differentially private hierarchical...
Did DOGE “breach” Americans’ data? (Lock and Code S06E08)
This week on the Lock and Code podcast … If you don't know about the newly created US Department of Government Efficiency DOGE, there's a strong chance they already know about you. Created on January 20 by US President Donald Trump through Executive Order, DOGE's broad mandate is “modernizing...
Did DOGE “breach” Americans’ data? (Lock and Code S06E08)
This week on the Lock and Code podcast … If you don't know about the newly created US Department of Government Efficiency DOGE, there's a strong chance they already know about you. Created on January 20 by US President Donald Trump through Executive Order, DOGE's broad mandate is “modernizing...
A Refreshment Stirred, Not Shaken (III): Can Swapping Be Differentially Private?
The quest for a precise and contextually grounded answer to the question in the present paper's title resulted in this stirred-not-shaken triptych, a phrase that reflects our desire to deepen the theoretical basis, broaden the practical applicability, and reduce the misperception of differential...
Dual Utilization of Perturbation for Stream Data Publication under Local Differential Privacy
Stream data from real-time distributed systems such as IoT, tele-health, and crowdsourcing has become an important data source. However, the collection and analysis of user-generated stream data raise privacy concerns due to the potential exposure of sensitive information. To address these...
A Review on Privacy in DAG-Based DLTs
Directed Acyclic Graph DAG-based Distributed Ledger Technologies DLTs have emerged as a promising solution to the scalability issues inherent in traditional blockchains. However, amidst the focus on scalability, the crucial aspect of privacy within DAG-based DLTs has been largely overlooked. This...
Fast Plaintext-Ciphertext Matrix Multiplication from Additively Homomorphic Encryption
Plaintext-ciphertext matrix multiplication PC-MM is an indispensable tool in privacy-preserving computations such as secure machine learning and encrypted signal processing. While there are many established algorithms for plaintext-plaintext matrix multiplication, efficiently computing...
Reveal-Or-Obscure: a Differentially Private Sampling Algorithm for Discrete Distributions
We introduce a differentially private DP algorithm called reveal-or-obscure ROO to generate a single representative sample from a dataset of $n$ observations drawn i.i.d. from an unknown discrete distribution $P$. Unlike methods that add explicit noise to the estimated empirical distribution, ROO...
pixiv: Bypassing Inbox Privacy Settings and Enabling Spam on Pixiv.net
A vulnerability was discovered in the messaging system of Pixiv.net. The vulnerability allowed any user to bypass the inbox privacy settings and send messages to another user who had disabled their inbox. The vulnerability was triggered by manipulating the id parameter in the message-sending POST...
Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
Differentially private DP machine learning often relies on the availability of public data for tasks like privacy-utility trade-off estimation, hyperparameter tuning, and pretraining. While public data assumptions may be reasonable in text and image domains, they are less likely to hold for tabul...
Multi-Class Item Mining under Local Differential Privacy
Item mining, a fundamental task for collecting statistical data from users, has raised increasing privacy concerns. To address these concerns, local differential privacy LDP was proposed as a privacy-preserving technique. Existing LDP item mining mechanisms primarily concentrate on global...
Benchmarking Differentially Private Tabular Data Synthesis
Differentially private DP tabular data synthesis generates artificial data that preserves the statistical properties of private data while safeguarding individual privacy. The emergence of diverse algorithms in recent years has introduced challenges in practical applications, such as inconsistent...
Care what you share
Welcome to this week's edition of the Threat Source newsletter. As we navigate our daily routines, certain tasks become second nature to us, especially if they are integral to our professions. However, what feels instinctive to one person might be foreign to another. This disparity is akin to a...
Leveraging Functional Encryption and Deep Learning for Privacy-Preserving Traffic Forecasting
Over the past few years, traffic congestion has continuously plagued the nation's transportation system creating several negative impacts including longer travel times, increased pollution rates, and higher collision risks. To overcome these challenges, Intelligent Transportation Systems ITS aim ...
CVE-2025-32783
XWiki Platform is a generic wiki platform. A vulnerability in versions from 5.0 to 16.7.1 affects users with Message Stream enabled and a wiki configured as closed from selecting "Prevent unregistered users to view pages" in the Administrations Rights. The vulnerability is that any message sent i...
I Know What You Bought Last Summer: Investigating User Data Leakage in E-Commerce Platforms
In the digital age, e-commerce has transformed the way consumers shop, offering convenience and accessibility. Nevertheless, concerns about the privacy and security of personal information shared on these platforms have risen. In this work, we investigate user privacy violations, noting the risks...
Privacy-Preserving CNN Training with Transfer Learning: Two Hidden Layers
Whitepaper called Privacy-Preserving CNN Training With Transfer Learning: Two Hidden Layers...
From Data Behavior to Code Analysis: a Multimodal Study on Security and Privacy Challenges in Blockchain-Based DApp
The recent proliferation of blockchain-based decentralized applications DApp has catalyzed transformative advancements in distributed systems, with extensive deployments observed across financial, entertainment, media, and cybersecurity domains. These trustless architectures, characterized by the...