Principles of Information Security (MindTap Course List)
6th Edition
ISBN: 9781337516938
Author: WHITMAN
Publisher: Cengage
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Chapter 6, Problem 15RQ
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Sacrificial host:
It is a system server, which is located outside a company’s Internet firewall in order to deliver a service that compromise the public network’s security if it is placed within the firewall.
- It is an individual network defender on the outside network.
- A sacrificial host is also referred as “bastion host”. Basically both hosts are same...
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Chapter 6 Solutions
Principles of Information Security (MindTap Course List)
Ch. 6 - Prob. 1RQCh. 6 - Prob. 2RQCh. 6 - Prob. 3RQCh. 6 - Prob. 4RQCh. 6 - Prob. 5RQCh. 6 - Prob. 6RQCh. 6 - Prob. 7RQCh. 6 - Prob. 8RQCh. 6 - Prob. 9RQCh. 6 - Prob. 10RQ
Ch. 6 - Prob. 11RQCh. 6 - Prob. 12RQCh. 6 - Prob. 13RQCh. 6 - Prob. 14RQCh. 6 - Prob. 15RQCh. 6 - Prob. 16RQCh. 6 - Prob. 17RQCh. 6 - Prob. 18RQCh. 6 - Prob. 19RQCh. 6 - Prob. 20RQCh. 6 - Prob. 1ECh. 6 - Prob. 2ECh. 6 - Prob. 3ECh. 6 - Prob. 4ECh. 6 - Prob. 5ECh. 6 - Prob. 1CEDQCh. 6 - Prob. 2CEDQCh. 6 - Suppose that Ms. Hamir stacked the deck with her...
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- Construct an experiment to estimate the speed at which a particular computer can process an authentication password. From that estimate, determine how long it would take to test common password candidate lists, such as a list of 100 or 1000 popular passwords, the same list enhanced with orthographic substitutions (3 for e, zero for O, one for l, 2 for z, and so forth), and a word list from a common online dictionary.arrow_forwardTeren and Tixe are two distrustful friends. Tixe trains a neural network, and mentions to Teren that her neural network operates with hidden states. Teren doesn't believe the claim. Which part of her neural network must Tixe show Teren to convince him? a) MaxPool layer b) Linear layer c) Conv2d layer d) Elman layerarrow_forwardAn Artificial Neural Network contains 2 neurons in the Input Layer (called neuron 0 and neuron 1), 2 neurons in the middle layer or hidden layer (called neuron 2 and neuron 3), and one neuron in the output layer (neuron 4). The depiction shows the structure of this Neural Network: -4.8 5.9 3 5.2 -5.2 -3.2 -2.7 Bias Assume that the activation function used for all neurons is "logistic function" and the Bias is 1. If an input is given to the Input Layer as (1,0), i.e., the value of 1 will go the Neuron 0 and value of 0 goes to Neuron 1, calculate the outputs for Neurons 2, 3, and 4. Fill the blank by typing your answers for the output of neurons. below. (Round your answer to the nearest thousandth, i.e. 0.01583 will be entered as 0.016 or .016) Output of Neuron 2 is Output of Neuron 3 is Output of Neuron 4 is 5,1 4-6 -2.6arrow_forward
- Over a network using WEP, we were able to capture two frames with the sameInitialization Vector (IV). The following are the encrypted messages:• First frame encrypted message:1 0 0 1 0 0 1 0 1 0 1 1 0 0 0 0 0 1 1 1 0 1 0 1 1 0 0 1 0 1 1 1 1 0 1 1 0 1 1 0 1 0 0 11 1 1 1 1 0 0 1 0 0 0 1 0 0 1 1 1 0 0 0• Second frame encrypted message:1 1 0 0 0 0 0 1 1 1 1 0 0 0 0 1 0 0 1 1 0 1 1 1 1 1 0 0 1 0 1 1 1 1 1 0 0 0 1 1 1 1 0 11 0 1 0 1 1 0 0 1 1 0 0 0 1 1 0 1 1 1 0We also know that one of the messages is a control message with the following plaintext content:0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 01 0 0 1 1 0 0 1 0 0 0 1 1 1 0 0 01. Find the plaintext of the other message.2. If the captured messages were from two different stations on a network that usesTKIP, is it possible to find the plaintext of the other message? Explain why orwhy not possible.arrow_forwardHttps is a protocol used to secure websites from being tampered with by other parties without proper authorization. it bridges the gap between sender and receiver.Using protocols like secure socket layer/TLS, HTTPS encrypts data sent over the internet, making it unreadable to anybody who shouldn't have it.This prevents a "man in the middle" assault on the system.Such assaults intercept messages before they reach their intended recipient.It then transmits the revised information to the user.It guarantees the server's authenticity, too.arrow_forwardTelemedicine is the ability to provide medical assistance from a distance using telecommunication. For this example, imagine that a platoon of soldiers might be out in the battlefield. While a medic might be with them, he/she cannot constantly monitor each soldier’s vital signs, but if various sensors were sewn into soldier uniforms, vital statistics could be monitored from a distance by a doctor at headquarters. That doctor may be able to identify a medical problem for one of the soldiers and relay that information and instructions for care back to a medic in the area. The doctor at headquarters should be able to select a given soldier and see that soldier’s vital signs on a portable computer device (e.g., iPad). Perhaps the medic in the field might even have a video camera so that the doctor may be able to view a wound. Design the interface that the HQ doctor would see. Using the display design principles design an interface mockup using graphics, photos, and/or text to show what…arrow_forward
- One of the problems with the Internet email system is that sending forged emails is relatively straightforward, i.e., it is easy to send an email with a fake sender/from address. One solution to this problem would be for a domain’s mail servers to digitally sign any email originating from the domain. For this to be useful, the public key would need to be made available to clients to validate the signatures. It is proposed that the public keys of the mail servers will be verified and signed by a certification authority (same as SSL/TLS certificates) and distributed via a standardised URL for the domain, e.g., https://mybusiness.com/email.pubkey. (a) Explain how the client would obtain the public key and validate the email server’s digital signatures. (b) Discuss the problem of trusting the obtained public key and how this solution results in public keys that can/cannot be trusted. (c) Indicate whether you believe this approach could be used to prevent forged emails and explain why it…arrow_forwardConsider a neural language model (NLM) that uses a softmax layer as its output layer. How many nodes where there be in the output layer? What is the typical interpretation of the value of each output node?arrow_forwardA pyramid of size n is formed as follows: First, the base of the pyramid consists of n numbers, given as a list: [x_1, x_2, ., x_n] The next layer contains n-1 numbers, obtained from adding each pair of adjacent numbers in the lower layer: [x_1 + x_2, x_2 + x_3, x_(n-1) + x_n] The next layer contains n-2 numbers, obtained from adding each pair of adjacent numbers in the lower layer: [x_1 + 2x_2 + x_3, x_2 + 2x_3 + x_4, , x_(n-2) + 2x (n-1) + x_n] This process is repeated until the top layer which has only 1 number. Create a function that takes in a list of numbers in the bottom layer and returns the only number at the top layer. For example, we can form a pyramid having a base of [2, 0, 2, 1]: 9 4 5 2 3 2 1 >>> pyramid ( [1, 2]) 3 >>> pyramid ([3, 2, 1]) 8 >>> pyramid ([2, e, 2, 1]) Write the function pyramid (base) to return the number the top of a pyramid with a given base.arrow_forward
- The cost function of a general neural network is defined as J(ŷ,y) = m // [4 (9(0), y(1) The loss function L(ŷ), y() is defined by the logistic loss function Ly, y) = [ylogy) + (1-y)log (1 - ¹)] Please list the stochastic gradient descent update rule, batch gradient descent update rule, and mini-batch gradient descent update rule. Explain the main difference of these three update rules.arrow_forwardQuestion 6 : Figure 3 shows the structure of the LeNet5 convolutional neural network. What is the name of the C1 layer? What is the size of the filters of the C1 layer? How many weight values C1 layer has? What is the size of the filters in the C3 layer? How many weight values C3 layer has?" How many weight values C5 and F6 layers each has, respectively Cl: 6x28x28 S2 6x14x14 С3: 16х10х10 C5: 120 S4: 16x5x5 F6: 84 input image: 32х32 RBF output: 10 Figure 3: LeNet5 Convolutional Neural Networkarrow_forwardConverged Networks mean that there is a network for each type of data communication. * True False On a fault-tolerant network, if a data link fails, messages cannot be routed to the destination. * False O True Scalability means that the networks are able to grow and react to future changes. * False O Truearrow_forward
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