WEBVTT

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In this lesson,

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we will learn about labeling and tagging.

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Data labeling and tagging

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involves assigning markers to data

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to indicate its classification, sensitivity,

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or handling requirements.

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Additionally, labeling and tagging

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ensures proper data management and protection.

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Now, in addition to understanding that data classifications,

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like confidential, secret, and top secret,

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require different levels of protection,

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let's explore how these classifications

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and related tags are applied to data.

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Spoiler alert, this is done through labeling and tagging.

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Data labels can be applied either manually or automatically,

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depending upon how the systems are configured.

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In many systems, data labels are automatically set

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based on a list of certain terms known as a dirty word.

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For example, let's say I am going to send you an email

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and I write the word bazooka in the email.

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If bazooka was on your list of secret classified terms

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or on your dirty word list,

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the email would automatically be labeled as secret

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because it contains a secret word, bazooka.

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However, automatic classification labeling

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isn't always the most effective method to use

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because the system might not know

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whether I meant bazooka the weapon

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or Bazooka the chewing gum.

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If I were referring to the chewing gum,

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then the email doesn't need to be classified as secret.

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Manual labeling occurs when the end user creates the data

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and adds a text-based classification label on their own.

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So if you created a document

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that had the new marketing strategy for your company

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and you only wanted top level executives

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to see that document, you might label it as top secret.

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In the military, every document has a classification label

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in both the header and the footer of the document.

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This might be unclassified, secret, or top secret labeling.

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This labeling ensures that everyone who sees the document

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knows its classification level and can protect it properly.

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In addition to labeling documents

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with a classification label,

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they can also be labeled with declassification requirements.

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This label will indicate

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when the data can be downgraded to an unclassified

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or lower level.

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Declassification typically occurs

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when the data is no longer useful.

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Let's look at an example

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to understand the importance of declassification.

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In 1944, the Allied forces invaded France

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on the beaches of Normandy.

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The invasion was known as Operation Overlord.

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The invasion plans were highly classified

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to ensure the Allies could launch a surprise attack

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against the Axis powers.

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Any documents created for Operation Overlord

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were labeled as top secret.

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While it made sense

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to keep this data highly classified during the war,

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after the invasion, there was no need

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to keep the information classified,

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so its classification was changed to unclassified.

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You can easily find the plans online today

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and read through them.

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So declassifying old data frees up resources

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that can then be used to protect current

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and more important information.

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By declassifying war plans such as Operation Overlord,

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historians and anyone who is interested

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can now read the plans.

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While classification labels are broad,

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such as secret or top secret,

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data tags can be used to provide additional detail

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on how the data should be protected.

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A data tag can further specify requirements

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for a piece of data within a classification.

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For instance, the documents for the Normandy invasion

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had a data tag.

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These documents were all tagged with the acronym BIGOT

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which stood for British Invasion

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of German-Occupied Territory.

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So the data was labeled as top secret,

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indicating a level of classification,

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but it was also given the tag BIGOT

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so that people would know the contents

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related to the invasion.

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Any document with the data tag BIGOT

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required additional special handling.

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Similarly, certain industries use data tags

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to indicate special handling instructions.

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For example, companies may have data tags like PII,

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or Personally Identifiable Information,

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SPI, or Sensitive Personal Information,

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PHI, or Personal Health Information,

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and financial or restricted data.

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Although these tags may be on documents

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that are labeled unclassified,

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the data tags tell people handling that data

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that it still needs protection.

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This is because tags help indicate

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the additional levels of protection

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that are required for specific data.

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For example, in a hospital,

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your medical record is not top secret,

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but it should still be protected,

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so it receives the data tag PHI,

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or Protected Health Information,

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to ensure that it receives the additional protection

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that is required by law for medical records.

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Now, even within highly classified data labels,

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there are tags that indicate

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even higher levels of protection.

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For example, under the top secret classification label,

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you might find tags like SI, or Special Intelligence,

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TK, or Talent Keyhole,

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and HCS, or Human Intelligence Control System.

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While you don't need to memorize these tags for the exam,

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they demonstrate that tags exist

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across all classification levels,

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including unclassified data,

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providing even more refined handling requirements

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than the classification levels themselves do.

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When dealing with technology,

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there are various technical solutions available

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for managing and protecting data using labels and tags.

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For example, Microsoft's Data Loss Prevention,

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or DLP solution,

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includes over 70 sensitive information types,

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such as PII, SPI, and PII,

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under the unclassified category.

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Another key design factor to consider

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is the format of your data.

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Format refers to how the information is organized

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based on specific structures or standards.

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Data formats fall into two main categories,

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structured and unstructured data.

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Structured data follows a predefined model.

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For instance, A CSV, or Comma-separated value file,

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organizes data in a predictable way,

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with each piece of information separated by commas.

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If I exported a list with a person's name, address,

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and phone number in CSV format, it might look like this.

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Jeremiah Minner, 123 Main Street,

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555-111-1234.

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This predictable structure

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makes it easy to manage and process data in this format.

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Unstructured data, by contrast,

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is not organized by a specific model at all,

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and it can include formats like PowerPoint slides,

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Word documents, emails, text files, and chat logs.

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Unstructured data is highly flexible

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because it does not need to follow a specific format.

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Because of the differences

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between structured and unstructured data,

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as well as the differences between labels and tags,

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various systems and classification mechanisms

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must be established

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to interpret different data types and formats.

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So remember, data labeling and tagging

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are used for marking data

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with classifications such as confidential,

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secret, or top secret,

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and for managing that data sensitivity

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and handling requirements like PII and PHI.

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In the end, labels and tags ensure that data is protected

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according to its level of importance.

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Furthermore, data labeling

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can be done automatically or manually,

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depending upon the system set up,

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and tags provide specific detail

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about the protection required for specific data

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even more so than a classification label does.

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Next, declassification plays a role

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when classified data is no longer sensitive

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and can be made public.

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And finally, both structured and unstructured data

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require different systems to manage their classification

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and protection properly.