Answer:
1. Option (a) is the correct answer. "Place a firewall between the Internet and your Web server".
2. Option (e) is the correct answer. "Require encryption for all traffic flowing into and out from the Ken 7 Windows environment".
3. Option (d) is the correct answer. "Implement Kerberos authentication for all internal servers".
4. The correct answer is option (g) "Require all personnel attend a lunch and learn session on updated network security policies".
5. Option (c) is the correct answer. "Enforce password complexity".
Explanation:
1. Users who tried to use ken 7 network resources for social media access will not be enable to do so.
2. Encryption for inflow and outflow of traffic from Ken 7 windows environment will monitor any personal devices which is connected to Ken 7 windows network.
3. The implementation of Kerberos authentication will deny anonymous users access to protected resources in Ken 7 infrastructure.
4.All personnel will be taught the network policies to avoid sending report to unsecured printers.
5. The more complex passwords are, the more secured the server will be. A complex password should be enforce for network security.
I'm pretty sure it's C) or D) because it seems those make the most sense because providing excitement does not matter if that is not their point, repeating a previous point is practically useless because that point has already been said.
Answer: Highlight the text you want to copy. Use the shortcut key combination Ctrl + C on a PC or Command + C on a Mac to copy the text. Move the text cursor to where you want to paste the text. Press Ctrl + V on a PC or Command + V on a Mac to paste the text
Explanation:
just copy and past by highlighting the text you want and clicking ctrl and c at the same time then ctrl and v to put it on word
Answer:
4. Supervised learning.
Explanation:
Supervised and Unsupervised learning are both learning approaches in machine learning. In other words, they are sub-branches in machine learning.
In supervised learning, an algorithm(a function) is used to map input(s) to output(s). The aim of supervised learning is to predict output variables for given input data using a mapping function. When an input is given, predictions can be made to get the output.
Unsupervised learning on the other hand is suitable when no output variables are needed. The only data needed are the inputs. In this type of learning, the system just keeps learning more about the inputs.
Special applications of supervised learning are in image recognition, speech recognition, financial analysis, neural networking, forecasting and a whole lot more.
Application of unsupervised learning is in pre-processing of data during exploratory analysis.
<em>Hope this helps!</em>
