Detection
We track 15 posts about Detection from 13 engineering blogs. Most active: Elastic, Ivan Ursul, Confluent. Latest post: Oct 8, 2026.
Companies writing about Detection
Recent posts
Hotword detection in FHE on GPU in 350ms (opens on the source site)
A quick update on our homomorphic encryption compiler HEIR: our partners at Belfort have a hotword detector in FHE that runs in 350ms. More specifically, they launched a live demo at hotword.belfortlabs.com, that has a little game inspired by the NY Times Connections puzzle. Instead of typing in your guess for the word that connects a group of clues, you say it out loud. Your audio is encrypted under FHE, transitted to their server, and a hotword detector runs on it to determine which word you said (still encrypted).
How to rank fraud detection models using custom cost metrics (opens on the source site)
Red Hat ·
When building fraud detection systems, standard training steps often hide expensive failures. A model can show 96% accuracy on paper while letting every single fraudulent transaction pass unchecked. In fraud detection, a common first pass uses logistic regression with basic features and a 0.5 threshold. which often yields an accuracy of 96%. The post How to rank fraud detection models using custom cost metrics appeared first on Red Hat Developer.
Automating Twilio Auth Token Detection and Rotation with TruffleHog, Tines, and Slack (opens on the source site)
Twilio ·
Automate Twilio auth token detection and rotation with TruffleHog, Tines, and Slack to quickly secure exposed credentials.
SNAP payment error detection: how Elastic helps US states beat the FY2028 penalty (opens on the source site)
Elastic ·
Detecting SNAP fraud requires a layered approach, where rules catch what agencies know to look for, machine learning surfaces what rules miss, and conversational investigation helps analysts act on what the data reveals. Elastic delivers all three.
Quiz: Traditional Face Detection With Python (opens on the source site)
Test your understanding of face detection with Python. Review Haar-like features, integral images, AdaBoost, and cascading classifiers.
Rootless Jailbreak Detection: Updating the Signals, Not the Claim (opens on the source site)
Codename One's iOS integrity checks now detect current rootless jailbreak layouts, cross-check hooked APIs, inspect mounts and loaded images, and rerun on foreground entry.
Building Secure, Resilient, and Compliant Fraud Detection With Confluent Cloud (opens on the source site)
Learn how Confluent Cloud powers real-time fraud detection with, multi-layered encryption, and built-in financial compliance
Type Construction and Cycle Detection (opens on the source site)
Go ·
The Go Blog Type Construction and Cycle Detection Mark Freeman 24 March 2026 Go’s static typing is an important part of why Go is a good fit for production systems that have to be robust and reliable. When a Go package is compiled, it is first parsed—meaning that the Go source code within that package is converted into an abstract syntax tree (or AST). This AST is then passed to the Go type checker. In this blog post, we’ll dive into a part of the type checker we significantly improved in Go 1.26. How does this change things from a Go user’s perspective? Unless one is fond of arcane type…
Building a Real-Time AI Fraud Detection System with Spring Kafka and MongoDB (opens on the source site)
In this tutorial, we'll build a real-time fraud detection system using MongoDB Atlas Vector Search, Apache Kafka, and AI-generated embeddings. We'll demonstrate how MongoDB Atlas Vector Search can be ... The post Building a Real-Time AI Fraud Detection System with Spring Kafka and MongoDB appeared first on DEV.
Advancing Fall Detection: Crafting a Custom PCB for the Raspberry Pi Zero 2W (opens on the source site)
Schematics of the PCB module In my previous post, Developing a Fall Detection Device with Raspberry Pi, I delved into the initial steps of building a fall detection system using the Raspberry Pi Zero 2W. Today, I’m excited to share the next phase of this journey: designing and fabricating a custom PCB that integrates essential sensors to create a compact, robust, and efficient fall detection device. The Quest for Compactness The primary goal of this project was to shrink the device’s size, making it thinner and more wearable for our target users. Bulky prototypes are a hindrance, especially…
“Show Me What’s Wrong!”: Enhancing Fraud Detection Analysis by Combining Charts and Text (opens on the source site)
Feedzai ·
Every year, millions of people fall victim to financial fraud. In 2023, the losses tied to this type of crime were estimated at US$159 billion just in the US, with some people losing all of their retirement savings to scammers.However, the impacts of this issue stretch beyond someone’s finances. It can also impact a victim’s life in many dimensions. Detecting and quickly acting upon suspicious transactions is essential to tackle this problem.Finding Fraud Through Data TablesTo review the data of alerted transactions, analysts look at information in tabular format (similar to what is presented…
Developing a High-Accuracy Fall Detection Device Using Raspberry Pi and Transformer Models (opens on the source site)
Your browser does not support the audio element. ** Dive into an AI-generated podcast where two virtual hosts discuss the key findings and implications of the featured article and its groundbreaking research." The prototype with the cover removed Falls are a significant concern for the elderly population, often leading to serious injuries and a decrease in the quality of life. Detecting falls promptly can enable quick assistance, potentially reducing the severity of injuries and providing peace of mind for both seniors and their families. In my recent project, I set out to create a highly…
Know your tools: The full range of Elastic Security’s detection engineering capabilities (opens on the source site)
Elastic ·
This blog provides a comprehensive overview of the detection capabilities available in Elastic Security. Learn about the latest features and get useful tips and tricks for your detection practice!
Monkey Patch Detection in Ruby (opens on the source site)
My last post detailed one way that CRuby will eliminate some intermediate array allocations when using methods like Array#hash and Array#max. Part of the technique hinges on detecting when someone monkey patches array. Today, I thought we’d dive a little bit in to how CRuby detects and de-optimizes itself when these “important” methods get monkey patched. Monkey Patching Problem The optimization in the previous post made the assumption that the implementation Array#max was the original definition (as defined in Ruby itself). But the Ruby language allows us to reopen classes, redefine any…
Real-world Insights: Anomaly Detection in Internet Traffic (opens on the source site)
Trivago ·
Anomaly detection for time series is like finding unusual events in a sequence of data over time. It helps identify outliers or deviations from the expected pattern, signaling potential issues or anomalies in the dataset. This is the theory, but how does it translate into practical implementation for real business needs?
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This page is generated automatically from the engineering blogs we follow. Every post links to its source, where it was published. See all sources.