Presentation of the InVID technologies for image forensics analysis

•

0 gostou•6,046 visualizações

Presentation of the challenges related to the detection of manipulation or tampering of digital images, and description of the funtionalities offered by the REVEAL Media Verificaiton Assistant that is integrated in the InVID Verification Plugin.

Tecnologia

Markos Zampoglou
Postdoctoral Research Associate, CERTH
Workshop on Content Verification Tools
June 6, 2018 @ Thessaloniki, Greece
DETECTING MALICIOUS TAMPERING
IN DIGITAL IMAGES

Image forgeries in the news
https://thelede.blogs.nytimes.com/2008/07/10/in-an-iranian-image-a-missile-
too-many/

Image forensics
Lens
Optical
filter
CFA pattern
Real-world
scene
R
G
G
B
Imaging
sensor
(e.g. CCD)
CFA
interpolat.
In-camera
SW
processing
In-camera
JPEG
compress.
DIGITAL CAMERA
Digital image
Tampered
digital image
Out of camera SW
processing
Piva, A. (2013). An overview on image forensics. ISRN Signal Processing, 2013.

Example: JPEG Ghosts
Farid, H. (2009). Exposing digital forgeries from JPEG ghosts. IEEE transactions on information forensics
and security, 4(1), 154-160.
• JPEG compression
• DCT coefficient quantization
• Tampered areas: different
quantization coefficients
• Recompression &
subtraction highlights
differences
• JPEG Ghosts

Tampering localization algorithms
Tampering
localization
Splicing
localization
Copy-move
detection
Block
matching
Keypoint
matching
High-frequency
noise
CFA
patterns
JPEG compression
traces
Filtering and
analysis
Camera-
specific (PRNU)
Quantization
artefacts
Compression grid
misalignment
JPEG ghosts,
ELA

Features
• Tampering localization maps
• “Magnifying glass”
• GPS localization
• Thumbnails
• Metadata
• Tutorials and examples
• Export PDF

Using the tools
1. Magnifying glass
2. Tampering localization
• Do more than one maps agree?
• Does the highlighted region correspond to a specific
object/part?
• Is this part suspicious/interesting?
3. Reverse search
• Is this the best version for analysis?

The pitfalls of image forensics
“MH17 – Forensic Analysis of Satellite Images
Released by the Russian Ministry of Defence”
• A report by Bellingcat1 using ELA to prove that the
Russian MoD had forged the images
• N. Krawetz: Bellingcat “misinterpreted the results”2
1https://www.bellingcat.com
2http://www.hackerfactor.com/blog/index.php?/archives/676-Continuing-Education.html

The future of image forensics
https://www.technologyreview.com/s/610784/this-algorithm-
automatically-spots-face-swaps-in-videos/

Acknowledgements
• Dr. Chryssanthi Iakovidou (CAGI algorithm)
• Olga Papadopoulou (back-end development)
• Lazaros Apostolidis (front-end development)
• Dr. Symeon Papadopoulos (Overview & design)
• Ruben Bouwmeester, DW (Design and evaluation)
• Yiannis Kompatsiaris (Overview)

Thank you!
http://reveal-mklab.iti.gr/reveal
Get in touch!
Markos Zampoglou markzampoglou@iti.gr
Symeon Papadopoulos papadop@iti.gr
Olga Papadopoulou olgapapa@iti.gr

Mais conteúdo relacionado

Semelhante a Presentation of the InVID technologies for image forensics analysis

Stegnography projects

keerthanapothula

A Web-based Service for Image Tampering Detection

Symeon Papadopoulos

IRJET- Video Forgery Detection using Machine Learning

IRJET Journal

An ordinary person always has confidence in the integrity of visual imagery and believes it without any doubt. But today's digital technology has eroded this trust. A relatively new method called image forgery is extensively being used everywhere. This paper proposes a method to depict forged regions in the digital image. The results for the proposed work are obtained using the MATLAB version 7.10.0.499(R2010a). The projected design is such that it extracts the regions that are forged. The proposed scheme is composed for uncompressed still images. Experimental outcome reveals well the validity of the proposed approach.

Elucidating Digital deception: Spot counterfeit fragment

VIT-AP University

An Approach for Copy-Move Attack Detection and Transformation Recovery

IRJET Journal

An Enhanced Method to Detect Copy Move Forgey in Digital Image Processing usi...

IRJET Journal

20110220 computer vision_eruhimov_lecture01

Computer Science Club

Steganography using visual cryptography: Report

Aparna Nk

Multimedia applications are becoming increasingly significant in modern world. The mushroom growth of multimedia data of these applications, particularly over the web has increased the demand for protection of copyright. Digital watermarking is much more acceptable as a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. In this paper, a DWT based watermarking scheme is proposed. We have used Genetic Algorithm (GA) in order to make an optimum tradeoff between imperceptibility and robustness by choosing an optimum watermarking level for each coefficient of the cover image. In addition to the suitable watermarking strength, the selection of best block size is also necessary for superior perceptual shaping functions. To achieve this goal we have trained and used GA to pick the best block size to tailor the watermark in one of the coefficients of the DWT. The fitness function criterion for the genetic algorithm decision making is based on PSNR values

A Secure & Optimized Data Hiding Technique Using DWT With PSNR Value

IJERA Editor

SasuriE ajal

AJAL A J

Facial look identity is a vital mission by means of human-interacting structures that goal to be aware of versions within the human’s emotional state. the principle challenge or the crucial part in surveillance society is the privacy-shielding era. because the rapid improvement in the internet international it turns into very essential to scramble the pics in the video or files for the duration of transmission. in this the biometric identity of photographs or faces from scrambled pictures plays a completely tough mission. Numbers of various technology are carried out to provide privateness for the duration of surveillance or during transmission of video however they're lack of essential traits, like reversibility or visible fine maintenance. in lots of scrambling methods the faces are covered by a few animation which may additionally or may not cover all faces or it receives hard to recover pics from this technique. Many guide method also are us used by which we will unscramble an photo but they are no longer powerful that a good deal. to overcome all this matters we proposed a novel approach- Many-Kernel Random Discriminate analysis (MK-RDA) to find out discriminative patterns from chaotic indicators. structures get better accuracy bring about best photos. To PIE and ORL datasets has getting above ninety% accuracy.

4. ijece edit sat

IAESIJEECS

Steganography is the art and science of writing hidden messages in such a way that no one apart from the sender and intended recipient suspects the existence of the message a form of security through obscurity. The internet as a whole does not use secure links, thus information in transit may be vulnerable to interception as well. The important of reducing a chance of the information being detected during the transmission is being an issue now days. In this paper, we proposed a class of new distortion functions known as uniform embedding distortion function (UED) is presented. By incorporating the syndrome trellis coding, the best code word with undetectable data hiding is achieved. Due to hiding more amounts of data into the intersected area, embedding capacity is increased. Our aim is to hide the secret information behind the image file. Steganography hides the secret message so that intruder’s can’t detect the communication. When hiding data into the intersected area, thus provides a higher level of security with more efficient data mean square error is reduced and embedding capacity is increased.

Design of an adaptive JPEG Steganalysis with UED

IJCERT JOURNAL

IRJET- Homomorphic Image Encryption

IRJET Journal

Baythreat Cryptolocker Presentation

OpenDNS

Information hiding for covert communication is rapidly gaining momentum. With sophisticated techniques being developed in steganography, steganalysis needs to be universal. In this paper we propose Universal Steganalysis using Histogram, Discrete Fourier Transform and SVM (SHDFT). The stego image has irregular statistical characteristics as compare to cover image. Using Histogram and DFT, the statistical features are generated to train One- Class SVM to discriminate the cover and stego image. SHDFT algorithm is found to be efficient and fast since the number of statistical features is less compared to the existing algorithm.

Detecting Original Image Using Histogram, DFT and SVM

IDES Editor

MODIFIED-HYBIRD DESIGN (COMBINATION VERILOG HDL WITH MATLAB.pptx

vcrajan1

IRJET- A Review on Moving Object Detection in Video Forensics

IRJET Journal

LCI - MICC Seminario-Forensics

ICL - Image Communication Laboratory

"Forgery" is a subjective word. An image can become a forgery based upon the context in which it is used. An image altered for fun or someone who has taken a bad photo, but has been altered to improve its appearance cannot be considered a forgery even though it has been altered from its original capture. The other side of forgery are those who perpetuate a forgery for gain and prestige. They create an image in which to dupe the recipient into believing the image is real and from this they are able to gain payment and fame. Detecting these types of forgeries has become serious problem at present. To determine whether a digital image is original or doctored is a big challenge. To find the marks of tampering in a digital image is a challenging task. Now these marks of tampering can be done by various operations such as rotation, scaling, JPEG compression, Gaussian noise etc. called as attacks. There are various methods proposed in this field in recent years to detect above mentioned attacks. This paper provides a detailed analysis of different approaches and methodologies used to detect image forgery. It is also analysed that block-based features methods are robust to Gaussian noise and JPEG compression and the key point-based feature methods are robust to rotation and scaling.

Analysis and Detection of Image Forgery Methodologies

ijsrd.com

For the full video of this presentation, please visit: http://www.embedded-vision.com/platinum-members/qualcomm/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit-mangen For more information about embedded vision, please visit: http://www.embedded-vision.com Michael Mangen, Product Manager for Camera and Computer Vision at Qualcomm, presents the "High-resolution 3D Reconstruction on a Mobile Processor" tutorial at the May 2016 Embedded Vision Summit. Computer vision has come a long way. Use cases that were previously not possible in mass-market devices are now more accessible thanks to advances in depth sensors and mobile processors. In this presentation, Mangen provides an overview of how we are able to implement high-resolution 3D reconstruction – a capability typically requiring cloud/server processing – on a mobile processor. This is an exciting example of how new sensor technology and advanced mobile processors are bringing computer vision capabilities to broader markets.

"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...

Edge AI and Vision Alliance

Semelhante a Presentation of the InVID technologies for image forensics analysis (20)

Stegnography projects

A Web-based Service for Image Tampering Detection

IRJET- Video Forgery Detection using Machine Learning

Elucidating Digital deception: Spot counterfeit fragment

An Approach for Copy-Move Attack Detection and Transformation Recovery

An Enhanced Method to Detect Copy Move Forgey in Digital Image Processing usi...

20110220 computer vision_eruhimov_lecture01

Steganography using visual cryptography: Report

A Secure & Optimized Data Hiding Technique Using DWT With PSNR Value

SasuriE ajal

4. ijece edit sat

Design of an adaptive JPEG Steganalysis with UED

IRJET- Homomorphic Image Encryption

Baythreat Cryptolocker Presentation

Detecting Original Image Using Histogram, DFT and SVM

MODIFIED-HYBIRD DESIGN (COMBINATION VERILOG HDL WITH MATLAB.pptx

IRJET- A Review on Moving Object Detection in Video Forensics

LCI - MICC Seminario-Forensics

Analysis and Detection of Image Forgery Methodologies

"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...

Mais de InVID Project

InVID at IFCN Global Fact V

InVID Project

Presentation of the InVID tool for video fragmentation and keyframe-based rev...

InVID Project

Presentation of the InVID project and verification technologies

InVID Project

Presentation of the InVID verification technologies at IPTC 2018

InVID Project

IUT-Toulouse-InVID-2018

InVID Project

A state of the art in journalism about fake image and video detection

InVID Project

Presentation of the InVID tool for social media verification

InVID Project

Presentation of the InVID tool for video fragmentation and reverse keyframe s...

InVID Project

Presentation of the InVID Verification Plugin

InVID Project

Overview of the InVID project

InVID Project

Second issue of the InVID newsletter

InVID Project

The InVID Plug-in: Web Video Verification on the Browser

InVID Project

This slideset presents an approach to automatically detecting breaking news events from social media streams, using event detection to collecting near real time relevant video documents from social networks regarding that breaking news. A visual analytics dashboard provides access to the results of the content processing pipeline, providing a rich interactive interface to explore emerging stories and select video material around those stories for verification.

Video Retrieval for Multimedia Verification of Breaking News on Social Networks

InVID Project

The InVID Vefirication Plugin at #IFRAExpo #DCXExpo

InVID Project

The InVID Vefirication Plugin at DisinfoLab

InVID Project

Comparison of Fine-tuning and Extension Strategies for Deep Convolutional Neu...

InVID Project

TRECVID 2016 Ad-hoc Video Seach task, CERTH-ITI

InVID Project

InVID at the IPTC Autumn Meeting 2016

InVID Project

ELLA LC algorithm presentation in ICIP 2016

InVID Project

InVID verification application presentation at SMVW16

InVID Project

Mais de InVID Project (20)

InVID at IFCN Global Fact V

Presentation of the InVID tool for video fragmentation and keyframe-based rev...

Presentation of the InVID project and verification technologies

Presentation of the InVID verification technologies at IPTC 2018

IUT-Toulouse-InVID-2018

A state of the art in journalism about fake image and video detection

Presentation of the InVID tool for social media verification

Presentation of the InVID tool for video fragmentation and reverse keyframe s...

Presentation of the InVID Verification Plugin

Overview of the InVID project

Second issue of the InVID newsletter

The InVID Plug-in: Web Video Verification on the Browser

Video Retrieval for Multimedia Verification of Breaking News on Social Networks

The InVID Vefirication Plugin at #IFRAExpo #DCXExpo

The InVID Vefirication Plugin at DisinfoLab

Comparison of Fine-tuning and Extension Strategies for Deep Convolutional Neu...

TRECVID 2016 Ad-hoc Video Seach task, CERTH-ITI

InVID at the IPTC Autumn Meeting 2016

ELLA LC algorithm presentation in ICIP 2016

InVID verification application presentation at SMVW16

Último

Following the popularity of "Cloud Revolution: Exploring the New Wave of Serverless Spatial Data," we're thrilled to announce this much-anticipated encore webinar. In this sequel, we'll dive deeper into the Cloud-Native realm by uncovering practical applications and FME support for these new formats, including COGs, COPC, FlatGeoBuf, GeoParquet, STAC, and ZARR. Building on the foundation laid by industry leaders Michelle Roby of Radiant Earth and Chris Holmes of Planet in the first webinar, this second part offers an in-depth look at the real-world application and behind-the-scenes dynamics of these cutting-edge formats. We will spotlight specific use-cases and workflows, showcasing their efficiency and relevance in practical scenarios. Discover the vast possibilities each format holds, highlighted through detailed discussions and demonstrations. Our expert speakers will dissect the key aspects and provide critical takeaways for effective use, ensuring attendees leave with a thorough understanding of how to apply these formats in their own projects. Elevate your understanding of how FME supports these cutting-edge technologies, enhancing your ability to manage, share, and analyze spatial data. Whether you're building on knowledge from our initial session or are new to the serverless spatial data landscape, this webinar is your gateway to mastering cloud-native formats in your workflows.

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Safe Software

In this session, we will delve into strategic approaches for optimizing knowledge management within Microsoft 365, amidst the evolving landscape of Copilot. From leveraging automatic metadata classification and permission governance with SharePoint Premium, to unlocking Viva Engage for the cultivation of knowledge and communities, you will gain actionable insights to bolster your organization's knowledge-sharing initiatives. In this session, we will also explore how to facilitate solutions to enable your employees to find answers and expertise within Microsoft 365. You will leave equipped with practical techniques and a deeper understanding of how there is more to effective knowledge management than just enabling Copilot, but building actual solutions to prepare the knowledge that Copilot and your employees can use.

Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...

Drew Madelung

Scaling API-first – The story of a global engineering organization Ian Reasor, Senior Computer Scientist - Adobe Radu Cotescu, Senior Computer Scientist - Adobe Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

apidays

How to Troubleshoot Apps for the Modern Connected Worker

ThousandEyes

Imagine a world where information flows as swiftly as thought itself, making decision-making as fluid as the data driving it. Every moment is critical, and the right tools can significantly boost your organization’s performance. The power of real-time data automation through FME can turn this vision into reality. Aimed at professionals eager to leverage real-time data for enhanced decision-making and efficiency, this webinar will cover the essentials of real-time data and its significance. We’ll explore: FME’s role in real-time event processing, from data intake and analysis to transformation and reporting An overview of leveraging streams vs. automations FME’s impact across various industries highlighted by real-life case studies Live demonstrations on setting up FME workflows for real-time data Practical advice on getting started, best practices, and tips for effective implementation Join us to enhance your skills in real-time data automation with FME, and take your operational capabilities to the next level.

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

Safe Software

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc

MySQL Webinar, presented on the 25th of April, 2024. Summary: MySQL solutions enable the deployment of diverse Database Architectures tailored to specific needs, including High Availability, Disaster Recovery, and Read Scale-Out. With MySQL Shell's AdminAPI, administrators can seamlessly set up, manage, and monitor these solutions, ensuring efficiency and ease of use in their administration. MySQL Router, on the other hand, provides transparent routing from the application traffic to the backend servers in the architectures, requiring minimal configuration. Completely built in-house and supported by Oracle, these solutions have been adopted by enterprises of all sizes for their business-critical applications. In this presentation, we'll delve into various database architecture solutions to help you choose the right one based on your business requirements. Focusing on technical details and the latest features to maximize the potential of these solutions.

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Miguel Araújo

Top 10 Most Downloaded Games on Play Store in 2024

SynarionITSolutions

With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

Boost PC performance: How more available memory can improve productivity

Principled Technologies

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Rafal Los

The Good, the Bad and the Governed - Why is governance a dirty word? David O'Neill, Chief Operating Officer - APIContext Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...

apidays

Boost Fertility New Invention Ups Success Rates.pdf

sudhanshuwaghmare1

🐬 The future of MySQL is Postgres 🐘

RTylerCroy

Building Digital Trust in a Digital Economy Veronica Tan, Director - Cyber Security Agency of Singapore Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...

apidays

Manulife - Insurer Innovation Award 2024

The Digital Insurer

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

Tata AIG General Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving

Edi Saputra

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Neo4j

GenAI Risks & Security Meetup 01052024.pdf

lior mazor

Presentation of the InVID technologies for image forensics analysis

1. Markos Zampoglou Postdoctoral Research Associate, CERTH Workshop on Content Verification Tools June 6, 2018 @ Thessaloniki, Greece DETECTING MALICIOUS TAMPERING IN DIGITAL IMAGES

2. Image forgeries in the news https://thelede.blogs.nytimes.com/2008/07/10/in-an-iranian-image-a-missile- too-many/

3. Image forensics Lens Optical filter CFA pattern Real-world scene R G G B Imaging sensor (e.g. CCD) CFA interpolat. In-camera SW processing In-camera JPEG compress. DIGITAL CAMERA Digital image Tampered digital image Out of camera SW processing Piva, A. (2013). An overview on image forensics. ISRN Signal Processing, 2013.

4. Example: JPEG Ghosts Farid, H. (2009). Exposing digital forgeries from JPEG ghosts. IEEE transactions on information forensics and security, 4(1), 154-160. • JPEG compression • DCT coefficient quantization • Tampered areas: different quantization coefficients • Recompression & subtraction highlights differences • JPEG Ghosts

5. Tampering localization algorithms Tampering localization Splicing localization Copy-move detection Block matching Keypoint matching High-frequency noise CFA patterns JPEG compression traces Filtering and analysis Camera- specific (PRNU) Quantization artefacts Compression grid misalignment JPEG ghosts, ELA

6. Web image forensics

7. REVEAL Media Verification Assistant

8. Features • Tampering localization maps • “Magnifying glass” • GPS localization • Thumbnails • Metadata • Tutorials and examples • Export PDF

9. Using the tools 1. Magnifying glass 2. Tampering localization • Do more than one maps agree? • Does the highlighted region correspond to a specific object/part? • Is this part suspicious/interesting? 3. Reverse search • Is this the best version for analysis?

10. Forensic analysis outputs

11. The pitfalls of image forensics “MH17 – Forensic Analysis of Satellite Images Released by the Russian Ministry of Defence” • A report by Bellingcat1 using ELA to prove that the Russian MoD had forged the images • N. Krawetz: Bellingcat “misinterpreted the results”2 1https://www.bellingcat.com 2http://www.hackerfactor.com/blog/index.php?/archives/676-Continuing-Education.html

12. The future of image forensics https://www.technologyreview.com/s/610784/this-algorithm- automatically-spots-face-swaps-in-videos/

13. Acknowledgements • Dr. Chryssanthi Iakovidou (CAGI algorithm) • Olga Papadopoulou (back-end development) • Lazaros Apostolidis (front-end development) • Dr. Symeon Papadopoulos (Overview & design) • Ruben Bouwmeester, DW (Design and evaluation) • Yiannis Kompatsiaris (Overview)

14. Thank you! http://reveal-mklab.iti.gr/reveal Get in touch! Markos Zampoglou markzampoglou@iti.gr Symeon Papadopoulos papadop@iti.gr Olga Papadopoulou olgapapa@iti.gr

Presentation of the InVID technologies for image forensics analysis

Recomendados

Recomendados

Mais conteúdo relacionado

Semelhante a Presentation of the InVID technologies for image forensics analysis

Semelhante a Presentation of the InVID technologies for image forensics analysis (20)

Mais de InVID Project

Mais de InVID Project (20)

Último

Último (20)

Presentation of the InVID technologies for image forensics analysis