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The effects of misinformation, disinformation and malinformation (MDM) cost the global economy billions of dollars each year. Often known colloquially as “fake news,” MDM is damaging to public trust in institutions and, during elections, may even pose a threat to democracy itself. MDM has become a serious concern for consumers and organizations of all sizes. New technologies such as machine learning, natural language processing and amplification networks are being used to discredit factual information. Disinformation campaigns may use artificial intelligence (AI) and generative AI to spread false and misleading information, such as deepfakes. This document offers consumers and organizations information on identifying MDM and implementing the appropriate security measures to counter it.
On this page
- Types of information
- Defining misinformation, disinformation and malinformation
- What to look for
- Targets and victims
- Deepfakes
- Taking action as a consumer
- Taking action as an organization
- Learn more
Types of information
- Valid information means that it is factually correct, is based on data that can be confirmed and isn’t misleading in any way
- Inaccurate information is either incomplete or manipulated in a way that portrays a false narrative
- False information is incorrect and there is data that disproves it
- Unsustainable information can neither be confirmed nor disproved based on the available data
Defining misinformation, disinformation and malinformation
MDM can be identified as three main forms of informational activity that can cause minor or major harm:
- misinformation refers to false information that is not intended to cause harm
- disinformation refers to false information that is intended to manipulate, cause damage and guide people, organizations and countries in the wrong direction
- malinformation refers to information that stems from the truth but is often exaggerated in a way that misleads and causes potential harm
What to look out for
To identify MDM, evaluate the information landscape critically and take the time to review the sources and messaging. When viewing content in any form, ask yourself the following questions:
- Does it provoke an emotional response?
- Does it make a bold statement on a controversial issue?
- Is it an extraordinary claim?
- Does it contain clickbait?
- Does it use small pieces of valid information that are exaggerated or distorted?
Has it spread virally on unvetted or loosely vetted platforms?
These are a few guiding questions that can help you identify MDM. Even if one of these questions applies to a source, it does not automatically discredit the information. It is an indication to conduct more research on the item before trusting it.
Targets and Victims
Understanding who might be targeted and how threat actors use MDM is crucial for protecting your organization. Check out Tactics of disinformation from our partners at CISA.
Foreign actors use MDM to reduce trust in online spaces and influence international narratives. Primary target recipients for disinformation campaigns are members of linguistic minorities and diasporic communities. The idea is to use social and cultural differences to destabilize political systems.
Women, are disproportionately targeted subjects of MDM. Hyper-sexualized deepfakes are frequently used to shame and undermine women in public and political spheres.
Deepfakes
Deepfakes are becoming an increasingly common tactic used by cyber threat actors. They refer to synthetic content that has been digitally manipulated and is intended to deceive. This includes artificially generated images, audio and videos used in place of the original content. Technology is evolving rapidly and deepfakes are getting easier to make and harder to detect. While AI facilitates the creation of MDM, it is also an integral tool to help detect false information. AI can examine the metadata of a file, photo or video and can provide information on its source.
Taking action as a consumer
- Use a fact-checking site to ensure the information you are reading has not already been proven false
- Conduct a reverse image search to ensure images are not copied from a legitimate website or organization
- Avoid automatically assuming that information you receive is correct, even if it comes from a valid source (such as a friend or family member)
- Look for out of place design elements such as unprofessional logos, colours, spacing and animated gifs
- Verify domain names to ensure they match the organization. The domain name may have typos or use a different Top-Level Domain (TLD) such as .net or .org
- Check that the organization has contact information listed, a physical address and an “About Us” page
- Perform a WHOIS lookup on the domain to see who owns it and verify that it belongs to a trustworthy organization. WHOIS is a database of domain names and has details about the owner of the domain, when the domain was registered and when it expires
- Ensure the information is up to date
Taking action as an organization
- Set up social media, web monitoring and alerting services for identifying and tracking fake news related to your brand and organizations. These services often let you monitor not only your own social media profiles, but also public posts, web forums, websites, reviews, mentions, etc.
- Use search engine optimization (SEO) along with transparent, high-quality content on any web presence. SEO is used to optimize your site and social media listings on search engines such as Google and can ensure that your website is being displayed higher than a website with MDM that is targeting your organization
- Use answer engine optimization (AEO) which focuses on voice assistants to optimize answers from these devices so that they point to facts about your organization and not false information
- Use amplification networks to increase the reach and visibility of your content and prevent false information from overpowering the truth. Amplification networks act as loudspeakers for the truth and can include organizational partners, brand ambassadors and existing customers
- Encourage engagement with your customers and users to ensure trust is established and maintained. For example, search engines use reviews by customers and users to gauge the trustworthiness of a brand
- Create a response team to indirectly counteract any MDM campaigns and ensure a response occurs as soon as possible
- Avoid directly engaging with MDM
- Responses should be passive in nature and not within the conversation, post or thread that they are posted on
- Opt to post your response on your website instead
- Ensure that a response to MDM includes detailed, transparent and factual answers
Learn more
- Fact or fiction: Quick tips to help identify “fake news”
- ITSAP.00.040: Artificial intelligence
- ITSAP:00.041: Generative artificial intelligence (AI)
- ITSAP.00.101: Don’t take the bait: Recognize and avoid phishing attacks
- National Cyber Threat Assessment 2023-2024
- Online disinformation (GC)
- Cyber threats and elections (GC)
- Protecting democracy (GC)
- Election integrity and security including foreign interference (Elections Canada)
ᐃᒪᓐᓇ ᓇᓗᓇᐃᖅᓯᔪᓐᓇᖅᑐᑎᑦ ᑕᒪᒃᑯᓂᖓ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ
ᑕᒪᒃᑯᐊ ᐊᒃᑐᐃᓂᖏᑦ ᐅᕙᑦᑎᓐᓄᑦ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐊᑭᓖᔾᔪᑕᐅᓲ ᐱᓕᐊᓐᔅ ᑖᓚᓂᒃ ᐊᕐᕌᒍᑕᒫᑦ. ᖃᐅᔨᒪᔭᐅᔪᖅ ᑕᐃᔭᐅᓲᖑᓪᓗᑎᒃ, "ᓱᓕᓐᖏᑦᑐᓂᒃ ᑐᓴᒐᒃᓴᓕᑦ," ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᓱᕋᐃᔪᑦ ᑭᒃᑯᑐᐃᓐᓇᐃᑦ ᐃᒃᐱᒍᓱᑦᑎᐊᕈᓐᓇᐅᑎᖏᓐᓂᒃ ᑎᒥᐅᔪᓄᑦ ᐊᒻᒪᓗ, ᑕᐃᑲᓂ ᓂᕈᐊᖅᑎᓪᓗᒋᑦ, ᐅᓗᕆᐊᓇᖅᑐᒦᑎᑦᑎᔪᑦ ᒐᕙᒪᑦᑎᓐᓂᒃ. ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐊᖏᔪᒥᒃ ᐃᓱᒫᓘᑕᐅᔪᖅ ᓂᐅᕕᖅᑎᑦᑎᕙᒃᑐᓄᑦ ᐊᒻᒪᓗ ᐊᐅᓚᑦᓯᔨᓄᑦ ᑕᒪᐃᓐᓄᑦ ᖃᓄᑐᐃᓐᓇᖅ ᐊᖏᓕᕇᒐᓗᐊᓂᑦ. ᓄᑖᑦ ᐱᓕᕆᔾᔪᑕᐅᓕᖅᑐᑦ ᓲᕐᓗ ᖃᕆᓴᐅᔭᑎᒍᑦ ᐃᓕᓐᓂᐊᕈᑎᑦ, ᐅᖃᐅᓯᑐᖃᖅ ᐱᓕᕆᔾᔪᓯᖃᕐᓗᓂ ᐊᒻᒪᓗ ᐃᓚᒋᐊᕈᑎᓗᓂ ᖃᕆᓴᐅᔭᒃᑯᑦ ᐊᑦᑕᑕᕈᑎᒋᓯᒪᔭᕐᓄᑦ ᐊᑐᖅᑕᐅᔪᑦ ᑐᑭᓯᓂᕐᓗᒃᑎᑦᑎᔾᔪᑕᐅᓪᓗᑎᒃ. ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᓂᖅ ᐊᑐᖅᓯᔪᓐᓇᖅᑐᑦ ᐃᓄᖑᐊᓕᐊᕆᓯᒪᓕᖅᑐᑦ ᖃᕆᓴᐅᔭᐃᑦ ᐃᓱᒪᓕᖅᑕᐅᓯᒪᔪᑦ ᐊᒻᒪᓗ ᐋᕿᒃᓲᑎᖏᑦ ᐃᓱᒪᓕᖅᓯᒪᔪᑦ ᖃᕆᓴᐅᔭᐃᑦ ᑐᓂᐅᖃᐃᔪᓐᓇᕐᓂᐊᕐᒪᑕ ᓴᒃᓗᓯᒪᔪᓂᒃ ᐊᒻᒪᓗ ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ, ᓲᕐᓗ ᑭᒃᑯᖒᔭᖅᑐᑦ. ᐅᓇ ᑎᑎᕋᖅ ᑐᓂᓯᓯᒪᔪᖅ ᓂᐅᕕᖅᐸᒃᑐᓄᑦ ᐊᒻᒪᓗ ᐊᐅᓚᑦᓯᔨᓄᑦ ᑐᓴᒐᒃᓴᓂᒃ ᓇᓗᓇᐃᖅᓯᔪᓐᓇᕐᓂᐊᕐᒪᑕ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐊᒻᒪᓗ ᐊᑐᓕᖅᑎᑦᑎᓗᑎᒃ ᓈᒻᒪᒃᑐᓂᒃ ᐱᐅᔪᓂᒃ ᐅᓗᕆᐊᓇᖅᑐᒦᓕᖅᑕᐃᓕᔾᔪᑎᑦ ᑕᒪᒃᑯᐊ ᓵᓚᒋᓂᐊᕐᓗᒋᑦ.
ᖃᓄᕆᑑᓂᖏᑦ ᑐᓴᕐᑎᑦᑎᔾᔪᑕᓲᑦ
- ᓱᓕᕙᑦ ᑐᓴᒐᒃᓴᖓ ᑐᑭᖃᖅᑐᖅ ᓱᓕᔪᑦ, ᒪᓕᒃᑐᖅ ᖃᐅᔨᓴᖅᑎᒪᔪᓂᒃ ᓇᓗᓇᐃᑦᑎᐊᕈᓐᓇᖅᑐᑦ ᐊᒻᒪᓗ ᑕᒻᒪᖅᓴᐃᓐᖏᑦᑐᑦ
- ᑕᒻᒪᖅᓯᒪᔪᑦ ᐱᔭᕇᖅᓯᒪᓇᓂᓗ ᐅᕝᕙᓘᓐᓃᑦ ᐃᓚᐅᖅᓯᒪᓪᓗᓂ ᐃᓚᐅᖅᓯᒪᓇᓂᓘᓐᓃᑦ ᖃᐅᔨᓇᖅᑐᖅ ᓱᓕᓐᖏᑦᑐᒥᒃ ᐅᖃᖅᓯᒪᔪᖅ
- ᓱᓂᓐᖏᑦᑐᖅ ᑕᒻᒪᖅᓯᒪᔪᖅ ᐊᒻᒪᓗ ᖃᐅᔨᓇᖅᓯᓂᖓ ᑕᒪᑐᒧᖓ ᐊᔾᔨᒋᓐᖏᑕᖓᓂᒃ ᐅᖃᖅᓯᒪᔪᖅ
- ᐊᖑᒻᒪᑎᓐᖏᑦᑐᖅ ᐅᖃᖅᓯᒪᔪᖅ ᓇᓗᓇᐃᑦᑎᐊᒐᒃᓴᐅᔪᖅ ᐅᕝᕙᓘᓐᓃᑦ ᐊᔾᔨᒋᓐᖏᑕᖓ ᒪᓕᒃᑐᖅ ᐊᑐᐃᓐᓇᐅᒌᖅᑐᓂᒃ.
ᑐᑭᖏᑦ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ
ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᓇᓗᓇᐃᒐᒃᓴᐅᔪᑦ ᐱᖓᓱᑎᒍᑦ ᖃᓄᐃᓕᐅᖅᑐᑦ ᐋᓐᓂᖅᓯᔪᓐᓇᖅᑐᑦ ᐅᕝᕙᓘᓐᓃᑦ ᐊᒃᓱᐊᓘᖅᑐᒥᒃ ᐋᓐᓂᖅᓯᔪᓐᓇᖅᑐᑦ:
- ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᓯᒪᓂᖃᖅᑐᖅ ᓱᓕᓐᖏᑦᑐᑦ ᐱᔮᕆᓐᖏᓪᖢᑎᒃ ᐋᓐᓂᖅᓯᒋᐊᕋᑎᒃ
- ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐱᓯᒪᓂᖃᖅᑐᖅ ᓴᒡᓗᔪᑦ ᐱᔮᕆᓪᓗᑎᒃ ᑕᒻᒪᖅᑎᑦᑎᓇᓱᒃᑐᑦ, ᓱᕋᑦᑎᔪᑦ ᐊᒻᒪᓗ ᐊᔭᐅᕆᔪᑦ ᐃᓄᖕᓂᒃ, ᐊᐅᓚᑦᓯᔨᓂᒃ ᐊᒻᒪᓗ ᓯᓚᕐᔪᐊᒥ ᓄᓇᓕᖕᓂ ᑕᒻᒪᖅᑎᑦᑎᓪᓗᑎᒃ
- ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐱᓯᒪᓂᖃᖅᑐᖅ ᓱᓕᔪᒥᖔᖅᑑᒐᓗᐊᖅ ᑭᓯᐊᓂ ᐊᒃᓱᓗᐊᖅᑐᒥᒃ ᐱᓪᓚᑲᐅᔭᖅᑐᖅ ᐅᖃᖅᓯᒪᔪᖅ ᑕᐃᒫᒃ ᑕᒻᒪᖅᑎᑦᑎᓪᓗᓂ ᐊᒻᒪᓗ ᐋᓐᓂᖅᓯᓇᓱᒍᑎᒋᓪᓗᒍ
ᑭᓱᓂᒃ ᑕᑯᓐᓇᓯᒋᐊᖃᖅᐱᑕ
ᓇᓗᓇᐃᖅᓯᓂᐊᖅᖢᓂ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ, ᖃᐅᔨᓇᓱᑦᑎᐊᕐᓗᑎᑦ ᓇᑭᑦ ᑐᓴᖅᑎᑦᑎᔾᔪᑎᒋᕚ ᐊᒻᒪᓗ ᑐᐊᕕᓐᖏᓪᓗᑎᑦ ᕿᒥᕐᕈᐊᑦᑎᐊᕐᓗᒍ ᑐᓂᓯᔪᖅ ᐊᒻᒪᓗ ᑎᑎᕋᖅᓯᒪᔪᖅ ᑐᓴᕐᑎᑦᑎᔾᔪᑎᖓ. ᑕᐃᑲᓂ ᑕᑯᓐᓇᖅᖢᒋᑦ ᑎᑎᖃᖏᑦ ᖃᓄᑐᐃᓐᓇᖅ ᐋᕿᒃᓯᒪᕙ, ᐊᐱᕆᓗᑎᑦ ᐅᑯᓂᖓ ᐊᑖᓂ ᑎᑎᕋᖅᓯᒪᔪᑦ ᐊᐱᖁᑎᑦ:
- ᐅᓇ ᐅᕙᖓ ᕿᐊᖓᓄᑦ ᐊᒃᑐᐃᕚ?
- ᐅᖃᐅᔾᔨᑦᑎᐊᖃᒻᒪᕆᒃᓯᒪᕙ ᐊᐅᕙᐅᑕᐅᔪᓐᓇᖅᑐᓂᒃ ᐱᔾᔪᑕᐅᔪᓄᑦ?
- ᐅᓇ ᐊᔾᔨᒋᔭᐅᓐᖏᑦᑐᒥᒃ ᐅᖃᐅᓯᖃᖅᑐᖅ?
- ᐃᓗᓕᖃᖅᐸ ᓇᕿᕝᕕᒋᔭᕆᐊᖃᖅᑐᒥᒃ?
- ᐊᑐᖅᓯᕙ ᐃᓚᐃᓐᓇᑯᓗᖏᓐᓂᒃ ᓱᓕᔪᓂᒃ ᐅᑯᐊᓗ ᐱᓗᐊᓕᖅᑎᓯᒪᔪᑦ ᐅᕝᕙᓘᓐᓃᑦ ᐋᕿᑦᑎᐊᕈᓐᓃᖅᑎᓯᒪᔪᑦ?
- ᑭᒃᑯᑐᐃᓐᓇᓂᑦ ᑕᑯᔭᐅᓯᒪᓕᕇᖅᐸ ᖃᐅᔨᓴᖅᓯᒪᑦᑎᐊᕋᓂ ᐅᕝᕙᓘᓐᓃᑦ ᖃᐅᔨᓴᖅᓯᒪᒐᓗᐊᖅᑐᑦ ᐊᑦᑕᕕᖃᑦᑎᐊᓐᖏᑦᑐᑦ ᑐᓐᖓᔾᔪᑎᒥᓂᒃ?
ᐅᑯᐊ ᐊᒥᓲᓐᖏᑦᑐᑦ ᐊᔪᕆᖅᓲᔾᔨᔪᑦ ᐊᐱᖁᑎᑦ ᐃᑲᔪᕈᓐᓇᖅᑐᑦ ᓇᓗᓇᐃᖅᓯᓗᑎᑦ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ. ᑕᐃᒪᓘᓐᓃᑦ ᐅᑯᐊ ᐊᐱᖁᑎᑦ ᐊᑑᑎᖃᓐᖏᑉᐸᑕ, ᐲᖅᓯᑲᐅᑎᒋᓐᖏᑦᑐᖅ ᑐᓴᒐᒃᓴᒥᒃ. ᐅᓇ ᓇᓗᓇᐃᖅᓯᔪᖅ ᐊᑏ ᖃᐅᔨᓴᑦᑎᐊᒃᑲᓐᓂᕐᓗᑎᑦ ᐅᑯᐊ ᐱᖁᑎᑦ ᓱᓕᑦᑎᐊᕋᓗᐊᕐᒪᖔᑕ.
ᐱᔮᕆᔭᐅᔪᑦ ᐊᒻᒪᓗ ᐱᓂᕐᓗᒃᑕᐅᔪᑦ
ᑐᑭᓯᐅᒪᓗᑎᑦ ᑕᐃᒪᓗ ᐱᔮᕆᔭᐅᔪᓐᓇᖅᑐᑎᑦ ᐊᒻᒪᓗ ᐅᓗᕆᐊᖅᓵᖅᑕᐅᓗᑎᒃ ᐱᓐᖏᐊᖅᑐᓂᑦ ᐊᑐᖅᓯᔪᓂᑦ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐱᒻᒪᕆᐅᕗᖅ ᓴᐳᒻᒥᓗᒍ ᐊᐅᓚᑦᓯᔩᑦ. ᖃᐅᔨᒋᐊᕐᓗᒋᑦ ᐅᕘᓇ ᐸᕐᓇᐃᓯᒪᔪᑦ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᕈᒪᓇᑎᒃ ᐱᓕᕆᖃᑎᒋᔭᑦᑎᓐᓂᑦ ᖃᕆᓴᐅᔭᒃᑯᑦ ᐱᕋᔭᒃᑐᓕᕆᔨᒃᑯᑦ ᐊᒻᒪᓗ ᓇᑉᐸᖅᑕᐅᓯᒪᔪᓂᒃ ᖃᐅᔨᓴᖅᑎᑦ ᑎᒥᖁᑎᖏᑦ.
ᑲᓇᑕᐅᑉ ᐊᑭᐊᓂᕐᒥᐅᑦ ᐱᓐᖑᐊᖅᑎᑦ ᐊᑐᓲᑦ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐅᒃᐱᕐᓇᕈᓐᓃᓱᖑᓕᖅᑐᑦ ᐃᑭᐊᕿᕕᒃᑯᑦ ᐃᓂᖃᕐᑎᑦᑎᓲᓂᒃ ᐊᒻᒪᓗ ᑕᐃᒪᐃᓕᐅᖅᑎᑦᑎᓲᑦ ᓯᓚᕐᔪᐊᒥ ᐅᖃᖅᑕᐅᒋᐊᓕᒃ ᒪᓕᒃᑎᑦᑎᓪᓗᑎᒃ.ᐳᖅᑐᓛᖅ ᑐᕌᖅᑕᐅᔪᑦ ᑐᑭᓯᑎᑕᐅᑦᑎᐊᕈᒪᓐᖏᑦᑐᓄᑦ ᐊᔪᐃᓐᓇᒋᐊᓪᓚᒍᑎᑦ ᐃᓚᒋᔭᐅᔪᓄᑦ ᐅᖃᐅᓯᓕᕆᓂᕐᒥ ᐊᒥᓲᓚᐅᖑᔪᑦ ᐊᒻᒪᓗ ᓇᒧᑐᐃᓐᓈᑦᓯᐊᓲᑦ ᓄᓇᓕᖕᓄᑦ. ᐅᓇ ᐃᓱᒪᓕᕈᑎ ᐊᑐᖅᑕᐅᓲᖅ ᐃᓅᓯᖃᑎᒌᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᐅᓯᖃᖃᑎᒌᓐᖏᑦᑐᑦ ᐋᕿᑦᑎᐊᕆᐊᒃᑲᓐᓂᖅᖢᑎᒃ ᓂᕈᐊᖅᑕᓯᒪᔾᔪᓯᕆᔭᖏᑦ.
ᐊᕐᓇᐃᑦ, ᐅᓄᓛᑦᑎᐊᑦ ᐱᔮᕆᔭᐅᓲᑦ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ. ᐊᐃᑉᐸᕇᖕᓂᕐᒧᑦ ᑭᒃᑯᖒᔭᖅᑐᑦ ᐊᑐᖅᑕᐅᒐᔪᓲᑦ ᑲᖑᓱᓕᖅᑎᑕᐅᓇᓱᒃᖢᑎᒃ ᑲᑕᒃᓴᔭᐅᓪᓗᑎᒃ ᐊᒻᒪᓗ ᐊᔪᓕᖅᑎᑕᐅᓇᓱᒃᓗᑎᒃ ᐊᕐᓇᐃᑦ ᑭᒃᑯᑐᐃᓐᓇᐃᑦ ᓵᖏᓐᓂ ᐊᒻᒪᓗ ᓂᕈᐊᖅᑕᐅᓯᒪᔪᓕᕆᓂᕐᒥ. ᖃᐅᔨᒋᐊᕐᓗᒋᑦ ᐅᕘᓇ ᐊᖑᑎᑦ ᐊᕐᓇᐃᑦ ᑐᑭᓯᓇᕈᓐᓃᖅᑎᓯᒪᔪᑦ ᐱᓕᕆᔾᔪᑕᐅᔪᑦ, ᑐᑭᖏᑦ ᐊᒻᒪᓗ ᐊᓯᖑᖃᑦᑕᖅᑐᑦ ᐊᑭᐊᓂᕐᒥᐅᓂᑦ ᐱᐅᓐᖏᑦᑐᐊᓘᓪᓗᑎᒃ ᐱᓐᖑᐊᖅᑐᑦ: ᐃᓕᑦᑎᒃᑲᓐᓂᕐᓗᑎᑦ ᐱᔾᔪᑎᒋᓪᓗᒍ ᑕᒪᓐᓇ ᐱᔾᔪᑎ
ᑭᒃᑯᖒᔭᖅᑐᑦ
ᑭᒃᑯᖒᔭᖅᑐᑦ ᐅᓄᖅᓯᕙᓪᓕᐊᕗᑦ ᐹᔾᔪᑎᒋᔭᐅᓇᓱᒃᖢᑎᒃ ᖃᕆᓴᐅᔭᒃᑯᑦ ᐅᓗᕆᐊᖅᓵᕆᔾᔪᑕᐅᔪᑦ ᐱᓐᖑᐊᖅᑎᓂᑦ. ᐊᑐᖅᖢᒋᑦ ᐱᓪᓚᕆᐅᔪᑦ ᐅᖃᖅᓯᒪᔪᑦ ᖃᕆᓴᐅᔭᒃᑯᑦ ᐋᕿᒃᓱᑲᓐᓂᖅᖢᒋᑦ ᐱᐅᔪᓐᓃᖅᑎᓪᓗᒋᑦ ᐊᒻᒪᓗ ᓴᒡᓗᕿᑖᕆᔾᔪᑎᒋᓪᓗᒋᑦ. ᐅᓇ ᐃᓚᖃᖅᑐᑦ ᐊᔾᔨᑐᖃᕆᓐᖏᑕᖏᓐᓂᒃ, ᓂᐱᑐᖃᕆᓐᖏᑕᖏᓐᓂᒃ ᐊᒻᒪᓗ ᑕᕐᕆᔭᐅᓯᐅᖅᓯᒪᔪᑐᖃᐅᓐᖏᑦᑐᓂᒃ ᐊᑐᓲᑦ ᐋᕿᒃᓯᒪᔪᑐᖃᕐᓂᑦ. ᖃᕆᓴᐅᔭᐃᑦ ᐊᓯᕈᖅᐸᓪᓕᐊᓂᖏᓐᓄᑦ ᓱᑲᓕᔪᒥᒃ ᐊᒻᒪᓗ ᑭᒃᑯᖒᔭᖅᑐᑦ ᐱᔭᕐᓂᕐᓂᖅᓴᕈᖅᐸᓪᓕᐊᔪᑦ ᐊᒻᒪᓗ ᖃᐅᔨᔭᒃᓴᐅᓐᖏᓂᖅᓴᕈᖅᐸᓪᓕᐊᔪᑦ. ᑕᐃᑲᓂ ᖃᕆᓴᐅᔭᒃᑯᑦ ᐃᓱᒪᔪᓐᓇᖅᑎᑦᑎᓂᖅ ᓴᕿᑦᑎᓯᒪᔪᑦ ᑖᒃᑯᓂᖓ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ, ᐅᓇᑦᑕᐃᖅ ᑕᒪᐃᓐᓄᑦ ᓴᓇᕐᕈᑎ ᐃᑲᔪᓲᖅ ᓴᕿᑎᑦᑎᓪᓗᓂ ᑕᒻᒪᖅᓯᒪᔪᓂᒃ. ᐃᓱᒪᓲᖅ ᖃᕆᓴᐅᔭᖅ ᖃᐅᔨᓴᕈᓱᓐᓇᖅᑐᖅ ᐊᖏᔪᓂᒃ ᑎᑎᖃᓂᒃ ᓄᐊᓯᒪᔪᓂᒃ, ᐊᔾᔨᖑᐊᓂᒃ ᐅᕝᕙᓘᓐᓃᑦ ᑕᕐᕆᔭᐅᑎᓂᒃ ᐊᒻᒪᓗ ᖃᐅᔨᑎᑦᑎᓗᑎᒃ ᑭᓇᒥᖔᕐᓂᖓᓂᒃ.
ᐱᓕᕆᐊᕆᓗᒋᑦ ᓂᐅᕕᓲᖑᓃᑦ ᐱᔾᔪᑎᒋᓪᓗᒍ
- ᐊᑐᖅᓯᓗᑎᑦ ᓱᓕᖕᒪᖔᑕ-ᖃᐅᔨᓇᓱᒃᕕᒃ ᐃᓂᖓ ᑕᐃᒪᓗ ᑐᓴᖅᑕᑎᑦ ᐅᖃᓕᒫᖅᑕᑎᓪᓗ ᓇᓗᓇᐃᖅᑕᐅᔪᕕᓂᐅᖕᒪᖔᑕ ᑕᒻᒪᖅᓯᒪᓂᖏᓐᓂᒃ
- ᐱᓕᕆᐊᕆᓗᒋᑦ ᐊᔾᔨᖑᐊᑦ ᐋᕿᒃᓱᖅᑕᐅᓂᑰᓐᖏᒃᑲᓗᐊᕐᒪᖔᑕ ᑕᕐᕋᓕᐅᖅᓯᒪᓐᖏᒃᑲᓗᐊᕐᒪᖔᑕ ᑕᐃᒪᐃᑦᑐᓪᓚᕆᐅᖕᒪᖔᑦ ᖃᕆᓴᐅᔭᖃᕐᕕᒃ ᐅᕝᕙᓘᓐᓃᑦ ᐊᐅᓚᑦᓯᔨᖏᑦ
- ᑲᓴᒃᑕᐃᓕᓗᒋᑦ ᑕᒻᒪᖅᓴᐃᓇᓱᒋᑲᐅᑎᒋᓗᒍ ᐃᓱᒪᐃᑦ ᑖᓐᓇ ᑐᓴᕐᑎᑦᑎᔪᑦ ᑕᒻᒪᖅᑎᑦᑎᓇᓱᒋᓐᖏᓪᓗᒍ, ᑕᐃᑲᖔᕋᓗᐊᕈᓂ ᖃᐅᔨᒪᑦᑎᐊᖅᑕᕐᓂᑦ (ᓲᕐᓗ ᐱᖃᓐᓇᕆᔭᕐᓂᑦ ᐅᕝᕙᓘᓐᓃᑦ ᐃᓚᖕᓂᑦ)
- ᕿᓂᕐᓗᑎᑦ ᑎᑎᕋᐅᔭᖅᓯᒪᔪᖃᕐᒪᖔᑦ ᓲᕐᓗ ᐱᓪᓚᕆᐅᓐᖏᑦᑐᓂᒃ ᑕᖅᓴᓂᒃ, ᑲᓚᓂᒃ, ᐃᓂᓕᐅᖅᓯᒪᔪᑦ ᐊᒻᒪᓗ ᐊᔾᔨᖑᐊᑯᓗᐃᑦ
- ᖃᐅᔨᓇᓱᑦᑎᐊᕐᓗᒍ ᓇᑭᑦ ᐊᐅᓪᓚᖅᑎᑕᐅᓯᒪᖕᒪᖔᑦ ᐊᑎᖏᑦ ᐊᑎᖃᕋᓗᐊᕐᒪᖔᓪᓗ ᐊᐅᓚᑦᓯᔨᖏᓐᓂ. ᐅᓇ ᑭᒃᑯᓂᑦ ᐊᑎᖃᕐᒪᖔᑦ ᐊᐅᓚᑦᑎᔪᑦ ᑕᒻᒪᖅᓯᒪᔪᖃᕐᒪᖔᑕ ᑎᑎᕋᖅᓯᒪᓂᖏᑦ ᐅᕝᕙᓘᓐᓃᑦ ᐊᑐᖅᓯᖕᒪᖔᑕ ᑐᕌᕈᑎᑦ ᐃᓚᒍᑎᖏᑦ ᓲᕐᓗ .net ᐅᕝᕙᓘᓐᓃᑦ .org
- ᖃᐅᔨᒋᐊᕐᓗᒍ ᑖᓐᓇ ᐊᐅᓚᑦᓯᔨᖓ ᐊᑎᖓ ᑎᑎᕋᖅᓯᒪᖃᑕᐅᖕᒪᖔᑦ, ᑐᕌᕈᑎᓪᓚᑖᖓᓗ ᐃᒡᓗ ᐊᒻᒪᓗ ᐅᓇ "ᐅᕙᑦᑎᓐᓂᒃ ᐱᔾᔪᑎᓕᒃ" ᒪᒃᐱᒐᖅ
- ᐱᓕᕆᐊᕆᓗᒋᑦ WHOIS ᕿᓂᕐᕕᒃ ᐊᐅᓪᓚᕐᑎᑦᑎᕕᐅᓯᒪᔪᓂ ᑕᑯᓗᒋᑦ ᑭᒃᑯᓂᑦ ᓇᖕᒥᓂᕆᔭᐅᖕᒪᖔᑦ ᐊᒻᒪᓗ ᓇᓗᓇᐃᑦᑎᐊᒃᑲᓐᓂᕐᓗᒋᑦ ᐱᖁᑎᒋᔭᐅᓂᖓ ᓱᓕᔪᑦ ᐊᐅᓚᑦᓯᔨᓪᓚᕆᐅᓪᓗᑎᒃ. WHOIS ᓄᐊᑦᑎᓯᒪᔪᖅ ᖃᐅᔨᓴᖅᓯᒪᔪᓂᒃ ᐱᖁᑎᖃᖅᑐᑦ ᐊᑎᖏᑦ ᐊᒻᒪᓗ ᓇᓗᓇᐃᔭᑦᑎᐊᖅᓯᒪᔪᑦ ᓇᖕᒥᓂᖁᑎᖃᖅᑐᑦ, ᑕᐃᑲᓂ ᐃᓂᖃᕐᕕᒋᔭᖓ ᐱᖁᑎᖃᖅᑐᓂᑦ ᐊᑎᖃᕐᒪᖔᑕ ᐊᒻᒪᓗ ᖃᖓ ᐃᓱᓕᕕᒃᓴᖃᕐᒪᖔᑕ
- ᑕᐃᒪᓗ ᑐᓴᒐᒃᓴᖅ ᒫᓐᓇ ᑎᑎᕋᖅᑕᐅᓂᑰᓗᑎᒃ ᐃᒻᒪᑲᓪᓚᓂᑕᐅᓐᖏᓪᓗᑎᒃ
ᐱᓕᕆᐊᕆᓗᒋᑦ ᐊᐅᓚᑦᓯᔨᐅᓂᓯ ᐱᔾᔪᑎᒋᓪᓗᒍ
- ᐋᕿᒃᓱᕐᓗᒋᑦ ᐅᖃᓘᑎᕋᓛᖅᓯᐅᑎᑦ ᑐᓴᐅᑎᓕᕆᔾᔪᑎᒋᔭᑦ, ᖃᕆᓴᐅᔭᖃᕐᕕᑦ ᒥᐊᓂᕆᓗᒋᑦ ᐊᒻᒪᓗ ᑐᓴᖅᑎᑦᑎᔾᔪᑏᑦ ᐱᔨᑦᑎᕋᐅᑎᑦ ᓇᓗᓇᐃᖅᓯᔾᔪᑎᒃᓴᓄᑦ ᐊᒻᒪᓗ ᒪᓕᒋᐊᖃᖅᑐᑦ ᑖᒃᑯᐊᓪᓚᑖᖑᒐᓗᐊᕐᒪᖔᑕ ᐅᖃᐅᓯᕆᔭᖏᑦ ᐃᕝᕕᑦ ᓴᓇᐅᒐᑎᑦ ᐊᒻᒪᓗ ᐊᐅᓚᑦᓯᔨᑦ. ᐅᑯᐊ ᐱᔨᑦᑎᕋᐅᑎᑦ ᐃᓛᓐᓂᒃᑯᑦ ᒥᐊᓂᕆᑎᑦᑎᓲᑦ ᓇᖕᒥᓂ ᐅᖃᓘᑎᕋᓛᕐᒥ ᐃᓕᖕᓂᒃ ᑎᑎᕋᖅᓯᒪᔪᓂ, ᑭᓯᐊᓂ ᑭᒃᑯᑐᐃᓐᓇᐃᑦᑕᐅᖅ ᑎᑎᕋᖅᑕᖏᓐᓂᒃ, ᖃᕆᓴᐅᔭᒃᑯᑦ ᑲᑎᒪᔪᓂ, ᖃᕆᓴᐅᔭᖃᕐᕕᖕᓂ, ᕿᒥᕐᕈᐊᖅᑕᐅᔪᓂ, ᐅᖃᐅᓯᐅᔪᓂ, ᐊᓯᖏᓪᓗ
- ᐊᑐᖅᓯᓗᑎᑦ ᕿᓂᕈᑎᖏᑦ ᐊᐅᓚᐅᑎᑦ ᓴᕿᑎᑦᑎᔪᓐᓇᖅᑐᑦ, ᑎᑎᕋᖅᓯᒪᑦᑎᐊᖅᑐᑦ ᐃᓗᓕᖏᑦ ᓇᓕᐊᑐᐃᓐᓇᖅ ᖃᕆᓴᐅᔭᕐᕕᑦ ᑐᕌᕈᑎᖏᓐᓂᒃ. ᐅᓇ ᐊᐅᓚᐅᑎ ᐊᑐᖅᑕᐅᔪᓐᓇᖅᑐᖅ ᐊᑐᖅᑕᐅᑯᑖᒍᓐᓇᕐᓂᐊᕐᒪᑦ ᐃᓂᒋᔭᐃᑦ ᐊᒻᒪᓗ ᐅᖃᓘᑎᕋᓛᕐᒥ ᑐᓴᐅᑎᓕᕆᔾᔪᑎᑦ ᑎᑎᕋᖅᓯᒪᔪᑦ ᕿᓂᕐᕕᖓᓂ ᐊᐅᓚᐅᑎᓂ ᓲᕐᓗ ᒎᓪᒍ ᐊᒻᒪᓗ ᖃᐅᔨᓴᑦᑎᐊᕐᓗᑎᑦ ᐃᕝᕕᑦ ᖃᕆᓴᐅᔭᖃᕐᕕᖓ ᓴᕿᔮᑦᑎᐊᕋᓗᐊᕐᒪᖔᑦ ᐳᖅᑐᓂᖅᓴᐅᓗᓂ ᖃᕆᓴᐅᔭᖃᕐᕕᖏᑦᑕ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐅᑯᐊ ᐱᔮᕆᔪᑦ ᐊᐅᓚᑦᓯᔨᑦᑎᓐᓂᒃ
- ᐊᑐᖅᓯᓗᑎᑦ ᑭᐅᓯᔾᔪᑎᑦ ᐊᐅᓚᐅᑎᑦ ᐊᐅᓪᓗᑎᔪᑦ ᓂᐱᖕᓂᒃ ᐃᑲᔪᖅᑎᑦ ᑭᐅᔭᐅᑦᑎᐊᕈᓐᓇᕐᓂᐊᕋᕕᑦ ᑖᒃᑯᓇᖓᑦ ᐱᓕᕆᔾᔪᑕᐅᔪᓂᑦ ᑕᐃᒪᓗ ᐊᑕᓕᖅᑎᑦᑎᓲᑦ ᓱᓕᔪᓂᒃ ᐱᔾᔪᑎᒋᓪᓗᒍ ᐊᐅᓚᑦᓯᔩᑦ ᐊᒻᒪᓗ ᑕᒻᒪᖅᓯᒪᔪᖃᓐᖏᑦᑐᑦ ᐅᖃᖅᓯᒪᓂᖏᑦ
- ᐅᓇ ᑭᐅᔭᐅᓯᔾᔪᑎᑦ ᐊᐅᓚᐅᑎ ᖃᖓᑦᑕᖅᑎᑕᐅᓯᒪᔪᑎᒍᑦ ᐅᓄᖅᓯᒋᐊᖅᑎᑦᑎᓲᖅ ᑎᑭᐅᑎᔪᓐᓇᖅᑕᒥᓂᒃ ᐊᒻᒪᓗ ᑕᑯᔪᓐᓇᖅᑕᒥᓂᑦ ᐃᕝᕕᑦ ᑎᑎᕋᖅᑕᖏᓐᓂᒃ ᐃᓗᓕᖏᓐᓂᒃ ᐊᒻᒪᓗ ᓱᓕᓐᖏᑦᑐᓂᒃ ᑭᐅᓯᑦᑕᐃᓕᑎᑦᑎᔪᖅ ᓵᓚᖃᕐᒪᑕ ᓱᓕᔪᑦ. ᐊᐅᓚᐅᑎᑦ ᖃᕆᓴᐅᔭᖅᑎᒍᑦ ᐊᐅᓚᑦᑎᔾᔪᑎᖏᑦᑎᒍᑦ ᓲᕐᓗ ᑐᓵᔾᔪᑏᑦ ᓂᐱᖁᖅᑐᓯᒋᐊᖅᓯᒪᔪᑦ ᓱᓕᔪᓂᒃ ᐊᒻᒪᓗ ᐃᓚᖃᖅᑐᖅ ᐊᐅᓚᑦᓯᔨᑦ ᐱᓕᕆᖃᑎᒌᖕᓂᒃ, ᐊᑎᖏᑦ ᐱᔭᐅᔪᒪᓛᑦ ᐊᒻᒪᓗ ᒫᓐᓇᐅᔪᖅ ᓂᐅᕕᖃᑦᑕᖅᑐᑦ
- ᑲᔪᖏᖅᓴᐅᑎ ᐱᓕᕆᖃᑎᒋᔪᓐᓇᕐᓗᒋᑦ ᓂᐅᕕᖅᑐᑦ ᐊᒻᒪᓗ ᐊᑐᖅᑐᑦ ᓱᓕᔪᓂᒃ ᓴᕿᑦᑎᓯᒪᒐᕕᑦ ᐊᒻᒪᓗ ᑕᐃᒪᐃᓕᖓᑏᓐᓇᕐᓂᐊᖅᑕᐃᑦ. ᐆᒃᑑᑎᒋᓪᓗᒍ, ᕿᓂᕈᑎᑦ ᐊᐅᓚᐅᑎᑦ ᐊᑐᖅᑕᐅᓲᑦ ᕿᒥᕐᕈᐊᖅᖢᑎᒃ ᑖᒃᑯᐊ ᓂᐅᕕᖅᑐᑦ ᐊᒻᒪᓗ ᐊᑐᖅᑐᑦ ᓱᓕᑦᑎᐊᕐᓂᐊᕐᒪᑕ ᐱᔪᒪᔭᖏᑦ ᑖᒃᑯᐊ ᓴᓇᐅᒐᖏᑦ ᑕᐃᒪᐃᑦᑐᖏᑦ
- ᓴᕿᑦᑎᓗᑎᑦ ᑭᐅᓯᔪᓐᓇᖅᑐᑦ ᐱᓕᕆᖃᑎᒌᑦ ᐊᑎᖏᓐᓂᒃ ᑕᕝᕙᖓᐅᓐᖏᑦᑐᖅ ᐊᑕᔪᑦ ᓇᓕᐊᑐᐃᓐᓇᖅ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᓄᖃᖓᑎᑦᑎᓇᓱᐊᖅᑐᓂ ᐊᒻᒪᓗ ᑭᐅᓯᖃᑦᑕᖅᑐᑦ ᐃᕐᖐᓐᓇᖅ
- ᑲᓴᒃᑕᐃᓕᓗᒋᑦ ᑐᕌᐃᓐᓇᖅᑐᖅ ᐱᓕᕆᖃᑎᖃᓕᕈᓐᓇᖅᑐᑦ ᑖᒃᑯᓄᖓ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ
- ᑭᐅᓯᔾᔪᑎᑦ ᐃᓄᑦᑎᐊᕙᐅᓗᑎᒃ ᐊᒻᒪᓗ ᖃᐅᔨᒪᓐᖏᓪᓗᑎᒃ ᑭᓱᒥᒃ ᐅᖃᐅᓯᖃᕐᓂᐊᕐᒪᖔᖅᐱᑦ, ᑎᑎᕋᕐᓂᐊᕐᒪᖔᖅᐱᑦ ᐅᕝᕙᓘᓐᓃᑦ ᐊᑕᑎᑦᑎᔾᔪᑎᒋᓂᐊᖅᑕᑎᑦ ᑕᐃᒃᑯᐊᓗ ᖃᕆᓴᐅᔭᒃᑯᑦ ᑎᑎᕋᖅᓯᒪᕕᒋᔭᖏᓐᓂ
- ᓄᖃᖅᑎᓪᓗᑎᑦ ᑭᐅᓯᔭᕆᐊᒃᓴᖅ ᑭᐅᓯᖔᕐᓗᑎᑦ ᐃᕝᕕᑦ ᖃᕆᓴᐅᔭᖃᕐᕕᖓᒍᑦ
- ᑕᐃᒪᓗ ᑭᐅᓯᔾᔪᑎᒋᔭᐃᑦ ᑕᒪᑐᒥᖓ ᑐᓴᕐᑎᑦᑎᑦᓯᐊᓐᖏᑦᑐᑦ ᐱᔮᕆᓇᑎᒃ, ᐱᔮᕆᓪᓗᑎᒃ ᑐᓴᕐᑎᑦᑎᓯᐊᓐᖏᑦᑐᑦ ᐊᒻᒪᓗ ᐱᓪᓚᑲᐅᔭᖅᑐᑦ ᐃᓚᖃᕐᓗᒍ ᓇᓗᓇᐃᔭᑦᑎᐊᖅᓯᒪᔪᓂᒃ, ᓴᕿᑦᑎᐊᕐᓗᒋᑦ ᐊᒻᒪᓗ ᓱᓕᔪᓂᒃ ᑭᐅᓯᒪᔪᑦ