Explain types of digital authentication.

-

 Types of digital authentication 

Unique Passwords: 

The unique password is the most frequent method of digital authentication. Some businesses demand longer or more complicated passwords that include a mixture of characters, symbols, and numbers to make passwords safer. Users often find memorizing unique passwords onerous unless they can automatically aggregate their collection of passwords behind a single sign-on entry point.


Pre-shared Key (PSK): 

PSK is a sort of digital authentication in which the password is shared among users who are permitted to access the same resources - think of it as a branch office Wi-Fi password. Individual passwords are more secure than this method of authentication. One issue with shared passwords, such as PSK, is that they must be changed regularly, which can be inconvenient.


Behavioral authentication: 

When working with extremely sensitive data and systems, businesses can employ behavioral authentication to go much more detailed and evaluate keyboard dynamics or mouse-usage patterns. Organizations can swiftly determine if the user or machine behavior deviates from the usual by utilizing artificial intelligence, a trend in IAM systems, and can automatically lock down systems. 


Biometrics:

 It is a term used to describe the use of Biometrics used in modern IAM systems to provide more precise authentication. They capture fingerprints, irises, faces, palms, gaits, voices, and, in certain circumstances, DNA, among other biometric features. Passwords have been discovered to be less successful than biometrics and behavior-based analytics.



Comments

Post a Comment

Popular posts from this blog

Suppose that a data warehouse consists of the three dimensions time, doctor, and patient, and the two measures count and charge, where a charge is the fee that a doctor charges a patient for a visit. a) Draw a schema diagram for the above data warehouse using one of the schemas. [star, snowflake, fact constellation] b) Starting with the base cuboid [day, doctor, patient], what specific OLAP operations should be performed in order to list the total fee collected by each doctor in 2004? c) To obtain the same list, write an SQL query assuming the data are stored in a relational database with the schema fee (day, month, year, doctor, hospital, patient, count, charge)

-
Image
Solution: a) Star Schema is shown in the figure below: b) First, we should use the roll-up operation to get the year 2004(rolling-up from the day then month to a year). After getting that, we need to use the slice operation to select (2004). Second, we should use roll-up operation again to get all patients. Then, we need to use the slice operation to select (all). Finally, we get a list of the total fee collected by each doctor in 2004. So, 1. roll up from day to month to year 2. slice for year = “2004” 3. roll up on patient from the individual patient to all 4. slice for patient = “all” 5. get the list of the total fees collected by each doctor in 2004 c) Select doctor, Sum(charge) From fee Where year = 2004 Group by doctor
Read more

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

-
Image
a) A Snowflake Shema is shown in figure below: b) The specific OLAP operations to be performed: 1. Roll-up on course from course_id to department. 2. Roll-up on a student from student_id to university. 3. Dice on course, student with department ="CS" and university = "biguniversity" 4. Drill-down on a student from the university to student_name. c) N = 4 dimensions The cube will contain 54 = 625 cuboids.
Read more

Suppose that a data warehouse consists of the four dimensions; date, spectator, location, and game, and the two measures, count and charge, where charge is the fee that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. a) Draw a star schema diagram for the data b) Starting with the base cuboid [date; spectator; location; game], what specific OLAP operations should perform in order to list the total charge paid by student spectators at GM Place in 2004?

-
Image
  b) The specific OLAP operations to be performed are: 1. Roll-up on date from date id to year. 2. Roll-up on spectator from spectator id to status. 3. Roll-up on location from location id to location name. 4. Roll-up on the game from game id to all. 5. Dice with status= “students”, location name= “GM Place”, and year=2004
Read more