#Anomaly Detection

[fridge-reviews]

The Exit 8 - Blast Review

Developer: Kotake Create Steam Deck Compatibility?: Playable Rrp: £3.39

Now this is a genre I’ve not come across before, anomaly hunting. It feels like it’s an offshoot from walking simulators since strictly speaking the only thing you do is walk. The thing is, that’s a bit of an unfair statement. You see, in this game genre, you may interact with the game world by walking around but the game itself requires you to be observant and detail oriented.

In The Exit 8 you are stuck in an endlessly repeating passageway for what seems like a train station. If you see an anomaly you’re supposed to walk back the way you came, otherwise continue on. Each time you do this you’ll pass a large yellow exit sign, if you were right about there being an anomaly or not the number on that sign goes up, but if you’re wrong it reduces down to zero. The aim of the game is to get that sign to eight and finally exit the passageway.

The anomalies vary wildly, sometimes they’re very obvious but often they’re some kind of hidden detail such as a missing doorknob or a strange stain on the ceiling.

I absolutely loved this game, I’ve always enjoyed playing ‘spot the difference’ as a kid and this game gives the same sense of satisfaction that those did. It’s just in this case there’s also a sense of liminal horror as well, but don’t worry there aren’t any jumpscares.

---- If you’d like to support me I have a Ko-fi, the reviews will continue to be posted donation or not.

[megayogiposts]

Corruption in UP Forest Department Tenders

Mahesh Pratap Singh <yogimpsingh@gmail.com> Corruption in Procurement Process of UP Forest Department1 message Abhinav Sharma <sharmaabhinav6766@gmail.com>28 January 2025 at 15:23To: Mahesh Pratap Singh <yogimpsingh@gmail.com>Three Divisions of Uttar Pradesh Forest Department namely Hardoi, Firozabad & Amethi have invited Tenders from the Participants for the Supply of Agriculture Grade Gypsum…

[oksoimstilllongforusernames]

To this day I still wonder how The Knight is in my photo album but like, from way back in 2014 (NEARLY 10 YEARS AGO)

[2sillylittleguys]

I hate when this shit happens :/

[ontonix]

Ontonix Develops Risk Stratification Tool for Multimorbidity AF Patients

In the framework of the European Horizon Project AFFIRMO, grant 899871, Ontonix has developed a Risk Stratification tool which provides a probability score of patient hospitalization within a 1-year period. The specific aim of the AFFIRMO project is to implement and test the effectiveness of an integrated patient-centered holistic care pathway for the management of older patients with AF and…

[firsteigen-databuck]

What is Anomaly Detection? Anomaly detection – also known as outlier analysis – is an approach to data quality control that identifies those data points that lie outside the norms for that dataset. 

[usaii]

A Comprehensive Introduction to Anomaly Detection in Machine Learning | USAII®

An in-depth score on Anomaly detection techniques and more awaits you. Explore the most comprehensive take on anomaly detection and become an ML engineering asset.

Read more: https://shorturl.at/LHKo5a, Anomaly detection techniques, Anomaly detection algorithms, machine learning engineers, Clustering, machine learning techniques, anomaly detection systems, Machine Learning Certifications, Machine Learning Certification programs, machine learning models

[margaret-mead]

Optimize Network Performance Through Anomaly Detection

Companies should have professional tools that can help to detect minor changes while transferring the information. It can access the resources online that use anomaly detection to know about abnormal activities within the enterprise. Selecting a professional network traffic monitoring solution will help in identifying major threats and maintaining cybersecurity. Also, the IT administrator in a company can easily get notifications of outside threats with them.

[ordazzle01]

https://ordazzle.com/staying-ahead-in-e-commerce-with-ai-driven-anomaly-detection-techniques/

Embark on a profound exploration into the revolutionary realm of e-commerce, where the transformative power of AI-driven anomaly detection takes center stage. This enlightening journey invites you to delve into the profound significance, multifaceted features, and the unparalleled competitive edge that AI-driven anomaly detection bestows upon online businesses. Uncover the intricate layers of this cutting-edge technology as it reshapes the landscape of e-commerce security and operational efficiency. From its nuanced role in identifying irregularities to its capacity for predictive insights, this comprehensive exploration unveils the transformative potential that AI-driven anomaly detection holds for businesses navigating the ever-evolving e-commerce terrain. Join us in unraveling the complexities and unlocking the strategic advantages that this technological innovation brings to the forefront of e-commerce excellence.

[meteoroby]

Eccezionali ondate di calore fuori stagione ma anche siccità, incendi e alluvioni lampo si celano dietro a questo inarrestabile trend climatico del nuovo millennio. Intanto, quasi con certezza, il 2023 si avvia a essere l'anno più caldo mai registrato

[cimcondigital]

Transforming Predictive Maintenance with CIMCON Digital’s IoT Edge Platform: Unlocking Proactive Asset Management

Introduction

In today’s fast-paced and technologically advanced world, the need for efficient and proactive asset management is paramount for businesses to stay competitive. CIMCON Digital’s IoT Edge Platform emerges as a game-changer in the realm of Predictive Maintenance, empowering organizations to detect anomalies in advance using ML algorithms. This capability not only enables customers to plan schedules well in advance and avoid costly downtime but also provides real-time visibility into the remaining useful life of assets. In this article, we delve into how CIMCON Digital’s IoT Edge Platform revolutionizes Predictive Maintenance with practical examples of proactive asset management.

1. The Challenge of Reactive Maintenance

Traditionally, companies have been plagued by reactive maintenance practices, where assets are repaired or replaced only after failures occur. This reactive approach leads to unexpected downtime, reduced productivity, and increased maintenance costs. Predicting asset failures and planning maintenance schedules in advance is critical to ensure smooth operations, optimize resource allocation, and minimize overall downtime.

2. Empowering Proactive Maintenance with ML Algorithms

CIMCON Digital’s IoT Edge Platform is equipped with advanced Machine Learning algorithms that analyze real-time data from connected assets and machines. By continuously monitoring sensor data and historical performance trends, the platform can accurately detect anomalies and deviations from normal operating patterns. This proactive approach allows businesses to predict potential asset failures well in advance, providing ample time to schedule maintenance activities before any critical failures occur.

3. Planning Ahead to Avoid Downtime

Imagine a scenario in a manufacturing facility where a critical piece of equipment experiences an unexpected failure. The consequences could be disastrous, leading to costly downtime and missed production targets. With CIMCON Digital’s IoT Edge Platform in place, the same equipment would be continuously monitored in real-time. As soon as the platform detects any unusual behavior or signs of potential failure, it triggers an alert to the maintenance team.

Armed with this early warning, the maintenance team can plan the necessary repairs or replacements well in advance, avoiding unplanned downtime and minimizing disruption to production schedules. This capability not only ensures smooth operations but also optimizes maintenance resources and lowers the overall maintenance costs.

4. Real-Time Visibility into Asset Health

The IoT Edge Platform goes beyond detecting anomalies; it also provides real-time insights into the remaining useful life of assets. By analyzing historical performance data and asset health indicators, the platform estimates the remaining operational life of an asset with high accuracy.

Consider a scenario in a utility company managing a fleet of aging turbines. The maintenance team needs to know the remaining useful life of each turbine to plan proactive maintenance and avoid sudden breakdowns. With CIMCON Digital’s IoT Edge Platform, the team can access real-time information on the health of each turbine, enabling them to make data-driven decisions about maintenance schedules, parts replacement, and resource allocation.

5. Benefits of CIMCON Digital's IoT Edge Platform

CIMCON Digital’s IoT Edge Platform offers a host of benefits to businesses seeking to enhance their Predictive Maintenance capabilities:

a) Proactive Decision-making: By detecting anomalies in advance, the platform enables proactive decision-making, reducing reactive responses and enhancing overall operational efficiency.

b) Minimized Downtime: With the ability to schedule maintenance activities in advance, businesses can avoid costly downtime, leading to increased productivity and higher customer satisfaction.

c) Optimal Resource Allocation: The platform’s real-time visibility into asset health allows for better resource allocation, ensuring that maintenance efforts are targeted where they are most needed.

d) Cost Savings: By avoiding unexpected failures and optimizing maintenance schedules, businesses can significantly reduce maintenance costs and improve their bottom line.

Conclusion:

CIMCON Digital’s IoT Edge Platform empowers businesses to transcend traditional reactive maintenance practices and embrace a proactive approach to asset management. With the platform’s advanced ML algorithms, businesses can detect anomalies in advance, plan maintenance schedules proactively, and gain real-time visibility into asset health. This transformative capability results in minimized downtime, optimized resource allocation, and substantial cost savings. As CIMCON Digital’s IoT Edge Platform continues to revolutionize Predictive Maintenance, businesses can embark on a journey towards greater efficiency, productivity, and long-term sustainability.

[kbvresearch]

Anomaly Detection: Uncovering Hidden Insights in Your Data

In today’s data-driven world, the ability to detect anomalies is crucial for businesses and organizations across various industries. Anomaly detection, also known as outlier detection, is a technique used to identify patterns or data points that deviate significantly from the norm. In this blog, we will delve into the fascinating world of anomaly detection, exploring its importance, methods, and…

[ontonix]

AI Guesses Solutions. We Compute Them.

First of all, let’s clarify what Artificial Intuition can do: Identify faults, anomalies or malfunctions in all sorts of systems, providing early warnings. Pinpoint concentrations of fragility and vulnerability. Basically this means indicating where things can break. Find key variables in complex systems to help prioritise in case of trouble, or when optimising and re-designing for certain…

[jcmarchi]

Self-Authenticating Images Through Simple JPEG Compression

New Post has been published on https://thedigitalinsider.com/self-authenticating-images-through-simple-jpeg-compression/

Self-Authenticating Images Through Simple JPEG Compression

Concerns about the risks posed by tampered images have been showing up regularly in the research over the past couple of years, particularly in light of a new surge of AI-based image-editing frameworks capable of amending existing images, rather than creating them outright.

Most of the proposed detection systems addressing this kind of content fall into one of two camps: the first is watermarking – a fallback approach built into the image veracity framework now being promoted by the Coalition for Content Provenance and Authenticity (C2PA).

The C2PA watermarking procedure is a fallback, should the image content become separated from its original and ongoing provenance ‘manifest’. Source: https://www.imatag.com/blog/enhancing-content-integrity-c2pa-invisible-watermarking

These ‘secret signals’ must subsequently be robust to the automatic re-encoding/optimization procedures that often occur as an image transits through social networks and across portals and platforms – but they are often not resilient to the kind of lossy re-encoding applied through JPEG compression (and despite competition from pretenders such as webp, the JPEG format is still used for an estimated 74.5% of all website images).

The second approach is to make images tamper-evident, as initially proposed in the 2013 paper Image Integrity Authentication Scheme Based On Fixed Point Theory. Instead of relying on watermarks or digital signatures, this method used a mathematical transformation called Gaussian Convolution and Deconvolution (GCD) to push images toward a stable state that would break if altered.

From the paper ‘Image Integrity Authentication Scheme Based On Fixed Point Theory’: tampering localization results using a fixed point image with a Peak Signal-to-Noise (PSNR) of 59.7802 dB. White rectangles indicate the regions subjected to attacks. Panel A (left) displays the applied modifications, including localized noise, filtering, and copy-based attacks. Panel B (right) shows the corresponding detection output, highlighting the tampered areas identified by the authentication process. Source: https://arxiv.org/pdf/1308.0679

The concept is perhaps most easily understood in the context of repairing a delicate lace cloth: no matter how fine the craft employed in patching the filigree, the repaired section will inevitably be discernible.

This kind of transformation, when applied repeatedly to a grayscale image, gradually pushes it toward a state where applying the transformation again produces no further change.

This stable version of the image is called a fixed point. Fixed points are rare and highly sensitive to changes – any small modification to a fixed point image will almost certainly break its fixed status, making it easy to detect tampering.

As usual with such approaches, the artefacts from JPEG compression can threaten the integrity of the scheme:

On the left, we see a watermark applied to the face of the iconic ‘Lenna’ (Lena) image, which is clear under normal compression. On the right, with 90% JPEG compression, we can see that the distinction between the perceived watermark and the growth of JPEG noise is lowering. After multiple resaves, or at the highest compression settings, the majority of watermarking schemes face issues with JPEG compression artefacts. Source: https://arxiv.org/pdf/2106.14150

What if, instead, JPEG compression artefacts could actually be used as the central means of obtaining a fixed point? In such a case, there would be no need for extra bolt-on systems, since the same mechanism that usually causes trouble for watermarking and tamper detection would instead form the basis of tamper detection framework itself.

JPEG Compression as a Security Baseline

Such a system is put forward in a new paper from two researchers at the University of Buffalo at the State University of New York. Titled Tamper-Evident Image Using JPEG Fixed Points, the new offering builds on the 2013 work, and related works, by officially formulating its central principles, for the first time, as well as by ingeniously leveraging JPEG compression itself as a method to potentially produce a ‘self-authenticating’ image.

The authors expand:

‘The study reveals that an image becomes unchanged after undergoing several rounds of the same JPEG compression and decompression process.

‘In other words, if a single cycle of JPEG compression and decompression is considered a transformation of the image, referred to as a JPEG transform, then this transform exhibits the property of having fixed points, i.e., images that remain unaltered when the JPEG transform is applied.’

From the new paper, an illustration of JPEG fixed point convergence. In the top row we see an example image undergoing repeated JPEG compression, with each iteration showing the number and location of changing pixels; in the bottom row, the pixel-wise L2 distance between consecutive iterations is plotted across different compression quality settings. Ironically, no better resolution of this image is available. Source: https://arxiv.org/pdf/2504.17594

Rather than introducing external transformations or watermarks, the new paper defines the JPEG process itself as a dynamic system. In this model, each compression and decompression cycle moves the image toward a fixed point. The authors prove that, after a finite number of iterations, any image either reaches or approximates a state where further compression will produce no change.

The researchers state*:

‘Any alterations to the image will cause deviations from the JPEG fixed points, which can be detected as changes in the JPEG blocks after a single round of JPEG compression and decompression…

‘The proposed tamper-evident images based on JPEG fixed points have two advantages. Firstly, tamper-evident images eliminate the need for external storage of verifiable features, as required by image fingerprinting [schemes], or the embedding of hidden traces, as in image watermarking methods. The image itself serves as its proof of authenticity, making the scheme inherently self-evident.

‘Secondly, since JPEG is a widely-used format and often the final step in the image processing pipeline, the proposed method is resilient to JPEG operations. This contrasts with the original [approach] that may lose integrity traces due to JPEG.’

The paper’s key insight is that JPEG convergence is not just a byproduct of its design but a mathematically inevitable outcome of its operations. The discrete cosine transform, quantization, rounding, and truncation together form a transformation that (under the right conditions) leads to a predictable set of fixed points.

Schema for the JPEG compression/decompression process formulated for the new work.

Unlike watermarking, this method requires no embedded signal. The only reference is the image’s own consistency under further compression. If recompression produces no change, the image is presumed authentic. If it does, tampering is indicated by the deviation.

Tests

The authors validated this behavior using one million randomly generated eight-by-eight patches of eight-bit grayscale image data. By applying repeated JPEG compression and decompression to these synthetic patches, they observed that convergence to a fixed point occurs within a finite number of steps. This process was monitored by measuring the pixel-wise L2 distance between consecutive iterations, with the differences diminishing until the patches stabilized.

L2 difference between consecutive iterations for one million 8×8 patches, measured under varying JPEG compression qualities. Each process begins with a single JPEG-compressed patch and tracks the reduction in difference across repeated compressions.

To evaluate tampering detection, the authors constructed tamper-evident JPEG images and applied four types of attacks: salt and pepper noise; copy-move operations; splicing from external sources; and double JPEG compression using a different quantization table.

Example of fixed point RGB images with detection and localization of tampering, including the four disruption methods used by the authors. In the bottom row, we can see that each perturbation style betrays itself, relative to the generated fixed-point image.

After tampering, the images were re-compressed using the original quantization matrix. Deviations from the fixed point were detected by identifying image blocks that exhibited non-zero differences after recompression, enabling both detection and localization of tampered regions.

Since the method is based entirely on standard JPEG operations, fixed point images work just fine with regular JPEG viewers and editors; but the authors note that if the image is recompressed at a different quality level, it can lose its fixed point status, which could break the authentication, and needs to be handled carefully in real-world use.

While this isn’t just a tool for analyzing JPEG output, it also doesn’t add much complexity. In principle, it could be slotted into existing workflows with minimal cost or disruption.

The paper acknowledges that a sophisticated adversary might attempt to craft adversarial changes that preserve fixed point status; but the researchers contend that such efforts would likely introduce visible artifacts, undermining the attack.

While the authors do not claim that fixed point JPEGs could replace broader provenance systems such as C2PA, they suggest that fixed point methods could complement external metadata frameworks by offering an additional layer of tamper evidence that persists even when metadata is stripped or lost.

Conclusion

The JPEG fixed point approach offers a simple and self-contained alternative to conventional authentication systems, requiring no embedded metadata, watermarks, or external reference files, and instead deriving authenticity directly from the predictable behavior of the compression process.

In this way, the method reclaims JPEG compression – a frequent source of data degradation – as a mechanism for integrity verification. In this regard, the new paper is one of the most innovative and inventive approaches to the problem that I have come across over the past several years.

The new work points to a shift away from layered add-ons for security, and toward approaches that draw on the built-in characteristics of the media itself. As tampering methods grow more sophisticated, techniques that test the image’s own internal structure may start to matter more.

Further, many alternative systems proposed to address this problem introduce significant friction by requiring changes to long-established image-processing workflows – some of which have been operating reliably for years, or even decades, and which would demand a far stronger justification for retooling.

* My conversion of the authors’ inline citations to hyperlinks.

First published Friday, April 25, 2025