ALEX Resources

   View Standards     Standard(s): [DLIT] (7) 15 :

9) Identify common methods of securing data.

Examples: Permissions, encryption, vault, locked closet.

[DLIT] (9-12) 35 :

29) Summarize the role of compression and encryption in modifying the structure of digital artifacts and the varieties of information carried in the metadata of these artifacts.

With recent high-profile security decryption cases, encryption is more important than ever. Much of your browser usage and your smartphone data is encrypted. But what does that process actually entail? And when computers get smarter and faster due to advances in quantum physics, how will encryption keep up? This video can be played during a lesson on identifying common methods of securing data.

   View Standards     Standard(s): [DLIT] (7) 15 :

9) Identify common methods of securing data.

Examples: Permissions, encryption, vault, locked closet.

[DLIT] (8) 30 :

24) Compare and contrast common methods of cybersecurity.

Example: Discuss how password protections and encryption are similar and different.

This video will walk you through some common encryption techniques such as the Advanced Encryption Standard (AES), Diffie-Hellman Key Exchange, and RSA which are employed to keep your information safe, private, and secure.

   View Standards     Standard(s): [DLIT] (6) 25 :

19) Track data change from a variety of sources.

Example: Use editing or versioning tools to track changes to data.

[DLIT] (6) 26 :

20) Identify data transferring protocols, visualization, and the purpose of data and methods of storage.

Examples: Using an online collection tool or form to collect data that is then stored in a spreadsheet or database.

[DLIT] (6) 27 :

21) Identify varying data structures/systems and methods of classification, including decimal and binary.

Examples: Difference between a bit and a byte, bit representation, pixels.

[DLIT] (7) 15 :

9) Identify common methods of securing data.

Examples: Permissions, encryption, vault, locked closet.

[DLIT] (7) 26 :

20) Evaluate the validity and accuracy of a data set.

The world is a noisy place, and errors can occur whenever information is stored or transmitted. Error detection techniques add extra parity bits to data to determine when errors have occurred.

This activity is a magic trick which most audiences find intriguing. In the trick the demonstrator is “magically” able to figure which one out of dozens of cards has been turned over, using the same methods that computers use to figure out if an error has occurred in data storage.

   View Standards     Standard(s): [DLIT] (3) 7 :

1) Use numbers or letters to represent information in another form.

Examples: Secret codes/encryption, Roman numerals, or abbreviations.

[DLIT] (4) 7 :

1) Construct a basic system of numbers, letters, or symbols to represent information as a cipher.

Examples: Combine data from multiple sources, sorting multi-level.

[DLIT] (7) 15 :

9) Identify common methods of securing data.

Examples: Permissions, encryption, vault, locked closet.

[DLIT] (8) 28 :

22) Encrypt and decrypt various data.

Example: Create and decipher a message sent in a secret code.

What is Cryptography? A story which takes us from Caesar to Claude Shannon. Created by Brit Cruise.

On the left side of the linked webpage, there are additional resources related to cryptology, including Caesar cipher, polyalphabetic cipher, and the Enigma machine.

   View Standards     Standard(s): [DLIT] (6) 25 :

19) Track data change from a variety of sources.

Example: Use editing or versioning tools to track changes to data.

[DLIT] (6) 26 :

20) Identify data transferring protocols, visualization, and the purpose of data and methods of storage.

Examples: Using an online collection tool or form to collect data that is then stored in a spreadsheet or database.

[DLIT] (7) 15 :

9) Identify common methods of securing data.

Examples: Permissions, encryption, vault, locked closet.

[DLIT] (7) 26 :

20) Evaluate the validity and accuracy of a data set.

[DLIT] (7) 33 :

27) Identify data needed to create a model or simulation of a given event.

Examples: When creating a random name generator, the program needs access to a list of possible names.

In this lesson, students look at how data is collected and used by organizations to solve problems in the real world. The lesson begins with a quick review of the data problem-solving process they explored in the last lesson. Then students are presented with three scenarios that could be solved using data, brainstorm the types of data they would want to solve them, and how they could collect the data. Each problem is designed to reflect a real-world service that exists. After brainstorming, students watch a video about a real-world service and record notes about what data is collected by the real-world service and how it is used. At the end of the lesson, students record whether data was provided actively by a user, was recorded passively, or is collected by sensors.

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