Week 6.1: eCrime

The document summarizes an experiment on providing nudges to help people avoid regrettable online disclosures on social media. The experiment tested picture, timer, and sentiment nudges. The picture nudge reminded people how many others could see their post. This led one person to change their privacy settings and another to cancel posts. The timer nudge made people think more about their posts, leading some to cancel posts. The sentiment nudge was less effective as it sometimes misinterpreted sentiment. Overall, the nudges were found to help people make better privacy decisions but more work is needed to understand how different nudges work in different contexts.

Privacy and Security in Online Social Media : OSM APIs and tools for data col...

This document provides an overview of online social media and frameworks for analyzing social media data. It discusses the 4 V's of online social media data including volume, velocity, variety, and veracity. It also outlines programming languages, databases, and visualization tools that can be used to extract, store, and analyze social media data, including APIs, Python, MySQL, MongoDB, PHPMyAdmin, and RoboMongo. Finally, it provides an introduction to graph databases and Facebook's Graph API for representing online social relationships and content.

Privacy and Security in Online Social : Privacy and Pictures on Online Social...

This document summarizes a presentation on privacy and security in online social media. It discusses topics that will be covered including online social networks, programming languages, APIs, databases, and data analysis techniques. It then discusses concepts related to privacy including Westin's categories of privacy attitudes, concerns about privacy of personal information shared online, and types of privacy. Several experiments are described that aim to re-identify individuals by matching their publicly available social media photos with other unidentified sources, such as dating profiles or campus photos. The results showed that 6.3-10.5% of dating profiles and 38.18% of campus photos could be re-identified this way. The presentation concludes by discussing potential applications of these techniques in India.

Week 7.3 Semantic Attacks - Spear Phishing

Privacy and Security in Online Social Media : Trust and Credebillity on OSM

This document summarizes a lecture on privacy and security in online social media. It discusses analyzing misinformation spread on social media during real-world events like hurricanes and bombings. Features of tweets and user profiles are used to classify tweets as real or fake. A Chrome extension called TweetCred is demonstrated that analyzes tweets in real-time to assess credibility using machine learning models trained on these features. The lecture covers collecting, filtering, and annotating social media data from events. Network and linguistic analysis are used to understand information flow and credibility.

Week 8.1 Profile Linking on Online Social Media

Week 6.2: eCrime

This document discusses link farming in online social media platforms like Twitter. It explains that link farming involves users exchanging reciprocal links or follows to improve their ranking in search engines and influence scores. While link farming aims to boost metrics, it is considered spamming behavior. The document notes that both spammers and some legitimate users engage in link farming on Twitter to gain more followers and appear higher in search results. It also presents data from a study of a large Twitter dataset that found a significant percentage of accounts, links, and clicks led to spam, malware, or scam sites.

This document analyzes data from 85 public police department Facebook pages and over 100,000 posts to understand human behavior in online social media discussions between citizens and police. It finds that discussions between just citizens are more self-focused, while those including police comments show lower negative emotions. Citizen-initiated threads also have higher negative sentiment. The study aims to help police improve community engagement and support by better understanding topics of discussion, emotional expressions, and how citizens and police interact online. The results could help communities make consensus-based decisions and help police sense changing public sentiment to take timely action.

Privacy and Security in Online Social Media : Privacy and Social Media

This document discusses privacy and security issues related to using online social media. It covers topics like how privacy is defined, Westin's three categories of privacy attitudes, and different types of privacy issues that can occur on Facebook. Specific examples mentioned include getting personalized ads based on online activity and demographic information being collected from social media users. The document appears to be from a tutorial or presentation on privacy concerns in social media.

Week 7.1 Link Farming

This document discusses research into spammers and link farmers on Twitter. It finds that the top spam-followers, who reciprocate all links from spammers, account for 60% of spammer links. Popular users with more followers are also more likely to reciprocate spammer links. However, analysis of the top 100,000 link farmers found that most were still active legitimate accounts, like bloggers and experts, rather than spammers. These link farmers seem to engage in the practice to increase their social capital and influence, with account bios focused on promoting their own content or business.

Week 8.2 Anonymous Networks

This document summarizes research on the anonymous social media platform Whisper. Key findings include: 1) Most Whisper users interact anonymously with strangers and do not form strong social ties. 2) Over 18% of Whisper content is deleted through moderation, compared to 4% on Twitter. 3) Deleted content is typically moderated within 24 hours of posting. 4) While new users contribute content, overall user engagement declines as most users disengage from the platform over time.

Privacy and Security in Online Social Media : Incidents

Privacy and Security in Online Social Media : Policing and Social Media - Part 1

This document summarizes a course on privacy and security in online social media. It outlines topics that will be covered including an overview of online social media, tools like Linux, Python, APIs, and databases, and issues like trust, credibility, privacy, social network analysis, cybercrime, and identity resolution. It also discusses how police departments around the world are using social media for community outreach and to share information. Case studies of police presence on Facebook and Twitter in India, the US, and UK are presented.

Privacy and Security in Online Social Media : Intro to OSM

The document discusses various online social media platforms and privacy/security issues. It provides an overview of social media and its growth in India. Key platforms covered include Facebook, Twitter, YouTube, Pinterest, LinkedIn, Foursquare, Google+, Periscope and Tinder. Each platform's features and functionality are briefly explained. The document concludes by noting perceptions of privacy and security issues in social media.

Privacy and Security in Online Social Media : Misinformation on Social Media

This document discusses frameworks and tools for analyzing privacy and security in online social media. It outlines APIs, programming languages, databases and visualization tools that can be used to extract, store and analyze social media data. It then discusses tutorials on the Facebook API and temporal patterns of misinformation spreading on social media. Finally, it describes features that can be used to classify tweets and an architecture for analyzing fake accounts and their networks.

Privacy and Security in Online Social Media : Policing and Social Media - Part 2

The document discusses using social media data from citizen posts to police to understand public concerns and provide actionable information. 1600 comments across 255 posts were analyzed. The analysis found that posts provided spatial and temporal data on citizen concerns. It also found that citizens communicated both formally and informally with police. Police response time averaged 30.53 hours. The analysis also examined direct vs indirect reports, victimization language, and how social media could enable mutual accountability between citizens and police.

Basics of Image Processing using MATLAB

vkn13

The document provides an overview of basic image processing concepts and techniques using MATLAB, including: - Reading and displaying images - Performing operations on image matrices like dilation, erosion, and thresholding - Segmenting images using global and local thresholding methods - Identifying and labeling connected components - Extracting properties of connected components using regionprops - Performing tasks like edge detection and noise removal Code examples and explanations are provided for key functions like imread, imshow, imdilate, imerode, im2bw, regionprops, and edge.

Introduction to Digital Image Processing Using MATLAB

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This was a 3 hour presentation given to undergraduate and graduate students at Ryerson University in Toronto, Ontario, Canada on an introduction to Digital Image Processing using the MATLAB programming environment. This should provide the basics of performing the most common image processing tasks, as well as providing an introduction to how digital images work and how they're formed. You can access the images and code that I created and used here: https://www.dropbox.com/sh/s7trtj4xngy3cpq/AAAoAK7Lf-aDRCDFOzYQW64ka?dl=0

Digital Image Processing

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This presentation discusses digital image processing. It begins with definitions of digital images and digital image processing. Digital image processing focuses on improving images for human interpretation and processing images for machine perception. The history of digital image processing is then reviewed from the 1920s to today. Key examples of applications like medical imaging, satellite imagery, and industrial inspection are provided. The main stages of digital image processing are outlined, including image acquisition, enhancement, restoration, segmentation, and compression. The document concludes with an overview of a system for automatic face recognition using color-based segmentation.

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The document discusses Thailand's national IT policy and efforts to train chief information officers (CIOs) to support good governance through IT. It outlines a 2-week CIO training course covering topics like the CIO's role, IT components and trends, IT and organizational reengineering, management information systems, and IT laws and policies. The training includes lectures, computer skills training, site visits, and workshops to help CIOs drive IT development in government agencies and address issues like lack of expertise and leadership. Over 220 CIOs have been trained across government ministries and agencies.

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This document discusses research challenges in the Internet of Things (IoT). It begins by defining IoT and describing its key components like sensing, embedded systems, cloud computing, and analytics. It then discusses several application areas like healthcare, automotive, retail, and more. The document outlines the complex IoT architecture involving various stakeholders. It also discusses technical challenges in areas like distributed computing, communication protocols, data storage, analytics, privacy and security. Finally, it provides an overview of Tata Consultancy Services' Innovation Lab in Kolkata, including its research areas, projects, publications, awards and references.

Fighting Fraud and Cyber Crime: WTF ... "Where's the Fraud"

The document discusses collaboration between the prepaid card industry and law enforcement to combat fraud and cybercrime. It describes obstacles to collaboration between industries and with government/law enforcement agencies. It then provides examples of the National Cyber Forensic Training Alliance's (NCFTA) successes in facilitating information sharing and investigations that have led to arrests. The panel discussion covered the regulator's view of prepaid cards and fraud mitigation, the industry's view, and NBPCA's collaboration efforts.

Fighting Fraud and Cyber Crime: WTF ... "Where's the Fraud"

The document discusses obstacles to collaboration between law enforcement and industry in fighting cybercrime and fraud, and proposes solutions to overcome these obstacles. It outlines how the National Cyber-Forensic Training Alliance (NCFTA) has helped facilitate collaboration by serving as a neutral third party where intelligence can be shared and cases developed jointly. Some key inhibitors to collaboration discussed include different views of the scope of the problem between industry and law enforcement, concerns about what information can be shared and with whom, and a lack of understanding of each other's resources and context. The NCFTA model aims to address these by focusing on cross-sector intelligence sharing and resource pooling between industry and law enforcement.

Workshop E: Fighting Fraud and Cyber Crime: WTF…"Where's the Fraud"

The document discusses collaboration between the prepaid card industry and law enforcement to combat fraud and cybercrime. It describes obstacles to collaboration between industries and law enforcement, including different views of the scope of problems and available resources. It provides examples of the National Cyber Forensic Training Alliance's (NCFTA) successes in enabling information sharing that has led to arrests. Industry best practices for responding to law enforcement requests are also discussed.

Oral Pseudo-Defense PPT DropboxPlease submit here a narrated P.docx

gerardkortney

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GDPR and IoT: What do you need to know?

MicheleNati

The document summarizes key points about GDPR compliance for IoT devices and applications. It discusses the definition of personal data under GDPR, requirements for obtaining consent and providing transparency around data collection and use. It also addresses challenges for IoT regarding maintaining consent, access controls and dealing with complex data flows. Advanced topics discuss using artificial intelligence and the need for transparency around automated decision making.

Workware Systems Situational Awareness & Predictive Policing Overview

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Front line and community-based Policing is a high knowledge-based activity. Exploiting organisational knowledge in dynamic front line policing activity key to improving productivity. Productivity and effectiveness can be improved by pushing information to front line officers which is: - Relevant to their role - Relevant to their location - Relevant in time Our solutions Help Patrol Officers understand their environment and take action. We do this without significant cost and complexity.

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The document discusses collaboration between the prepaid card industry and law enforcement to combat fraud and cybercrime. It describes obstacles to collaboration between industries and law enforcement, including different views of the scope of problems and available resources. It provides examples of the National Cyber Forensic Training Alliance's (NCFTA) successes in enabling information sharing that has led to arrests. Industry best practices for responding to law enforcement requests are also discussed.

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This document proposes a system for personal and community context discovery as a service. It suggests using mobile phone sensors, 3D cameras, and web data in a non-intrusive way to gather information on location, proximity, activity, and identity to discover individual behaviors and community patterns. A multimodal fusion approach is recommended to integrate these context sources for improved accuracy. An IoT platform is presented as a way to implement and deploy this context discovery service for application developers.

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There is no "right or wrong" answer here; however, it is imperative that you substantiate your commentary. For this assignment, you are to answer the following questions with a minimum of 200 words. 1.In some states, such as in Colorado, state governments have legalized the possession and use of marijuana for its citizens. However, a federal law, known as The Controlled Substances Act of 1970, makes the possession and use of marijuana illegal under federal law. If Article VI of the United States Constitution stipulates that federal law takes precedence over state laws (known as the Supremacy Clause), then how is it that some states can make marijuana legal? The question posed to you this week is as follows: 1. Are states that legalize marijuana in violation of the Supremacy Clause contained in Article VI of the United States Constitution? Why or why not 2.Currently, in the private sector, according to the Bureau of Labor Statistics, a woman typically makes 87 percent of the wage a man makes in a similar position with similar responsibilities. There are some who state that women are more expensive to employ, primarily due to women being the bearer of children and the extended time off typically required after the birth of a child. However, there are others who state that this constitutes a violation of the Equal Protection Clause of the 14th Amendment, that women should be paid the same as men with similar positions and similar responsibilities. Even with the Equal Pay Act of 1963, signed into law by then-President John Kennedy, we still see these disparities in pay between the genders. Hence, the question I have for you is: 2.What steps can we take to ensure equal pay between genders for employment positions with similar responsibilities and similar duties? RESEARCH ARTICLE Where Is Current Research on Blockchain Technology?—A Systematic Review Jesse Yli-Huumo1, Deokyoon Ko2, Sujin Choi4*, Sooyong Park2, Kari Smolander3 1 Dept. of Innovation and Software, Lappeenranta University of Technology, Lappeenranta, Finland, 2 Dept. of Computer Science & Engineering, Sogang University, Seoul, South Korea, 3 Dept. of Computer Science, Aalto University, Helsinki, Finland, 4 Sogang Institute of Advanced Technology, Sogang University, Seoul, South Korea * [email protected] Abstract Blockchain is a decentralized transaction and data management technology developed first for Bitcoin cryptocurrency. The interest in Blockchain technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and data integrity without any third party organiza- tion in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain techno ...

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This document discusses personal and community context discovery as a service. It proposes using sensors from mobile phones, 3D cameras, and web data to gather context about individuals and communities in an unobtrusive way. These include location data, proximity, activity, identity and interaction level. A multimodal fusion approach and generic IoT platform are suggested to implement and provide context discovery as a service to application developers. Example use cases include organizational behavior analysis, customer behavior studies, and crowd analysis.

Digital forensic principles and procedure

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This document provides an overview of digital forensics principles and procedures. It discusses key guidelines for digital forensic investigations from organizations like ACPO and NIJ. The core principles of digital forensics are outlined, including that investigators should not alter original data and must have the skills to explain their examination process. The document also categorizes different types of digital forensics like computer, mobile, and audio/video forensics. The typical processes in a digital investigation are identified as identification, preservation, analysis, documentation, and presentation. Evidence can come from various electronic sources like computers, phones, and storage devices.

CPaaS.io Y1 Review Meeting - Citizen Empowerment

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Privacy and data protection are important in the context of IoT. The CPaaS.io platform empowers citizens to control the data that is related to them. This presentation given at the first year review meeting in Tokyo on October 5, 2017 explains how. Disclaimer: This document has been produced in the context of the CPaaS.io project which is jointly funded by the European Commission (grant agreement n° 723076) and NICT from Japan (management number 18302). All information provided in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. For the avoidance of all doubts, the European Commission and NICT have no liability in respect of this document, which is merely representing the view of the project consortium. This document is subject to change without notice.

Big social data analytics - social network analysis

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This document discusses social network analysis and visualization of Twitter data using tools like Gephi. It provides steps to collect Twitter data using an API script, create a network file from the data, and calculate network metrics and visualize the network in Gephi. Key aspects covered include extracting tweet data, creating a network file with NetworkX, uploading files to PythonAnywhere to run the script, and analyzing and visualizing the resulting network in Gephi to understand information diffusion on Twitter.

Digital Footprints_ Investigating Digital Evidence in Online Crime Cases.pptx

webb00704

Have you ever stopped to consider the trail of breadcrumbs you leave behind every time you browse the internet? From social media posts to online purchases, your digital footprint is expanding with each click. But what if I told you that this seemingly harmless virtual path holds immense significance in solving online crime cases? In an era where cybercriminals are growing more sophisticated by the day, understanding the importance of digital footprints has become crucial for law enforcement agencies and individuals alike. Get ready to dive into a world where every keystroke could be a potential clue in unraveling complex web-based crimes.

Fundamental digital forensik

newbie2019

This document provides an overview of digital forensics. It defines digital forensics and forensic science. Digital forensics involves the preservation, collection, analysis and presentation of digital evidence. There are different branches of digital forensics related to different devices. Examples of digital evidence include emails, photos, transaction logs, documents and computer memory contents. Characteristics of good digital evidence are that it is admissible, authentic, fragile, accurate and convincing. Several digital forensic models are described that involve multiple phases of an investigation. The benefits of digital forensics include protecting against theft, fraud, hacking and viruses. Skills required for digital forensics include technical experience, strong analysis and evidence handling skills.

ADPP: A NOVEL ANOMALY DETECTION AND PRIVACY-PRESERVING FRAMEWORK USING BLOCKC...

ijaia

The increasing popularity of crypto assets has resulted in greater cryptocurrency investor interest and more exposure in both industry and academia. Despite the substantial socioeconomic benefits, the anonymous character of cryptocurrency trading makes it prone to abuse and a magnet for illicit purposes, which cause monetary losses for individual traders and erosion in the standing of the tokenomics industry. To regulate the illicit behavior and secure users' privacy for cryptocurrency trading, we present an Anomaly Detection and Privacy-Preserving (ADPP) Framework integrating blockchain and deep learning technologies. Specifically, ADPP leverages blockchain technologies to build a user management platform that ensures anonymity and enhances the privacy-preservation of user information. Atop the user management system, an Anomaly Detection System adapts neural networks and imbalanced learning on topological cryptocurrency flow among users to identify anomalous addresses and maintain a sanction list repository. The experiments on the real-world dataset demonstrate the effectiveness and superior performance of ADPP. The flexible framework can be easily generalized to the crypto assets with public real-time transaction (e.g., Non-fungible Token), which takes up a significant proportion of market capitalization in the domain of tokenomics.

Big Data in FinTech

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Do online interactions trigger reactions back in the offline world? How can these reactions be detected and quantified? Specifically, what insights can be extracted for users, platform owners, and policymakers to minimize the potential harm of such reactions? Society functions based on the complex interactions between individuals, communities, and organizations. The advent of the Internet has enabled these interactions to move online. A website or an application that facilitates the digitization of social interactions is called a socio-technical platform. For instance, individuals converse with each other via direct messaging applications (e.g., WhatsApp, Telegram), share thoughts, and gather feedback from communities (e.g., Reddit, Twitter, Youtube). Trade of goods occurs via e-commerce (e.g., Flipkart, Amazon) and online marketplaces (e.g., Google Play store). At times interactions happening in the online world, trigger reactions in the offline world, which we call overflow. Such overflows can have either a positive or negative impact. Socio-technical platforms save every interaction and associated metadata, providing a unique opportunity to analyze rich data at scale. Discover interaction patterns, detect and quantify overflow of interactions, and extract insights for users and policymakers. This report aims to study the interactions by keeping the individual as the focal point. We focus on two broad forms of interactions - i) the effect online community feedback can have on individual offline actions and ii) organizations leveraging individual customers' online presence to optimize business processes. In the first part, we work on two scenarios - (a) How does community feedback affect an individual future drug consumption frequency in a drug community forum? and (b) What changes does an individual undergo immediately after getting sudden popularity in Online social media? What actions help in maintaining popularity for longer? In the second part, we leverage online information about a customer to improve the prediction of Return-to-Origin in the e-commerce platform.

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The document is a transcript of a talk given by PK to B.Tech orientation students at IIIT Hyderabad. Some key points from the talk include: - Encouraging students to make friends, participate in clubs and extracurricular activities. - Emphasizing time management and not missing out on opportunities in the first two semesters. - Advising students to explore different projects and areas before deciding on a focus or specialization. - Noting that managing courses, social life, hobbies and more will be challenging but important during their time at IIIT.

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Stress has become a significant mental health problem of the 21st century. The number of people suffering from stress is increasing rapidly. Thus, easy-to-use, inexpensive, and accurate biomarkers are needed to detect stress during its inception. Early detection of stress-related diseases allows people to access healthcare services. This thesis focuses on the development of stress stimuli and the detection of stress induced by these stimuli. Identifying brain regions affected while exposing the subject to these stressful stimuli has also been done. Three different stimuli, viz. videos, gamified application, and a game, are investigated to study their effect as stress induction stimuli. To this end, in this thesis, a system is proposed to classify participants into stressed and non-stressed categories using machine learning, deep learning, and statistical techniques. The statistical significance between stressed and non-stressed was found using Higuchi Fractal Dimensions (HFD) feature extracted from EEG. This feature also helped identify the brain’s most affected region due to stress. Another outcome of this thesis is the extra annotation of the ground truth which further helps to validate the participant’s experience under the influence of stressful stimuli. This annotation was performed by evaluating participant performance under time pressure. In addition, a technique based on in-game analytics is presented to complement the betterment of self-reported data. Further, another dimension utilizing signatures from WiFi Media Access Control (MAC) layer traffic is presented to detect stress indicators in a device-agnostic way.

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Elysian Digital Services Pvt. Ltd.

The distribution of research efforts done in the field of Natural Language Processing (NLP) has not been uniform across all natural languages. It has been observed that there is a significant gap between the development of NLP tools in Indic languages (indic-NLP), and in European languages. We aim to explore different directions to develop an automatic question answering system for Indic languages. We built a FAQ-retrieval based chatbot for healthcare workers and young mothers of India. It supported Hindi language in either Devanagri script or Roman script. We observed that, in our FAQ database, if there exists a question similar to the query asked by the user, then the developed chatbot is able to find a relevant Question-Answer pair (QnA) among its top-3 suggestions 70% of the time. We also observed that performance of our chatbot is dependent on the diversity in the FAQ database. Since database creation requires substantial manual efforts, we decided to explore other ways to curate knowledge from raw text irrespective of domain. We developed an Open Information Extraction (OIE) tool for Indic languages. During the preprocessing, chunking of text is performed with our fine-tuned chunker, and the phrase-level dependency tree was constructed using the predicted chunks. In order to generate triples, various rules were handcrafted using the dependency relations in Indic languages. Our method performed better than other multilingual OIE tools on manual and automatic evaluations. The contextual embeddings used in this work does not take syntactic structure of sentence into consideration. Hence, we devised an architecture that takes the dependency tree of the sentence into consideration to calculate Dependency-aware Transformer (DaT) embeddings. Since the dependency tree is also a graph, we used Graph Convolution Network (GCN) to incorporate the dependency information into the contextual embeddings, thus producing DaT embeddings. We used a hate-speech detection task to evaluate the effectiveness of DaT embeddings. Our future plan is to evaluate the applicability of DaT embeddings for the task of chunking. Moreover, the broader aim for the future is to develop an end-to-end pronoun resolution model to improve the quality of triples and DaT embeddings. We also aim to explore the applicability of all our works to solve the problem of long-context question answering.

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