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NEW QUESTION: 1
Which three statements about the IPsec ESP modes of operation are true? (Choose three.)
A. Transport mode leaves the original IP header in the clear.
B. Tunnel mode only encrypts and authenticates the data.
C. Tunnel mode is used between two security gateways.
D. Tunnel mode is used between a host and a security gateway.
E. Transport mode authenticates the IP header.
Answer: A,C,D
Explanation:
http://www.cisco.com/en/US/docs/net_mgmt/vpn_solutions_center/2.0/ip_security/provision
ing/guide/IPsecPG1.html
The Encapsulating Security Payload (ESP)
The Encapsulating Security Payload (ESP) contains six parts as described below. The first
two parts are not encrypted, but they are authenticated. Those parts are as follows:
The Security Parameter Index (SPI) is an arbitrary 32-bit number that tells the device receiving the packet what group of security protocols the sender is using for communication. Those protocols include the particular algorithms and keys, and how long those keys are valid.
The Sequence Number is a counter that is incremented by 1 each time a packet is sent to the same address and uses the same SPI. The sequence number indicates which packet is which, and how many packets have been sent with the same group of parameters. The sequence number also protects against replay attacks.
Replay attacks involve an attacker who copies a packet and sends it out of sequence to confuse communicating devices. The remaining four parts of the ESP are all encrypted during transmission across the network. Those parts are as follows:
The Payload Data is the actual data that is carried by the packet.
The Padding, from 0 to 255 bytes of data, allows certain types of encryption algorithms to require the data to be a multiple of a certain number of bytes. The padding also ensures that the text of a message terminates on a four-byte boundary (an architectural requirement within IP).
The Pad Length field specifies how much of the payload is padding rather than data.
The Next Header field, like a standard IP Next Header field, identifies the type of data carried and the protocol.
The ESP is added after a standard IP header. Because the packet has a standard IP header, the network can route it with standard IP devices. As a result, IPsec is backwards-compatible with IP routers and other equipment even if that equipment isn't designed to use IPsec. ESP can support any number of encryption protocols. It's up to the user to decide which ones to use. Different protocols can be used for every person a user communicates with. However, IPsec specifies a basic DES-Cipher Block Chaining mode (CBC) cipher as the default to ensure minimal interoperability among IPsec networks. ESP's encryption capability is designed for symmetric encryption algorithms. IPsec employs asymmetric algorithms for such specialized purposes as negotiating keys for symmetric encryption.
Tunneling with ESP Tunneling takes an original IP packet header and encapsulates it within the ESP. Then, it adds a new IP header containing the address of a gateway device to the packet. Tunneling allows a user to send illegal IP addresses through a public network (like the Internet) that otherwise would not accept them. Tunneling with ESP offers the advantage of hiding original source and destination addresses from users on the public network. Hiding these addresses reduces the power of traffic analysis attacks. A traffic analysis attack employs network monitoring techniques to determine how much data and what type of data is being communicated between two users.

NEW QUESTION: 2
You have a table in Power BI Desktop as shown in the following exhibit.

You pivot the columns as shown in the following exhibit.

You need to resolve the error in row3. The solution must preserve all the data.
What should you do?
A. Change the Data Type of the Value column.
B. Select the Score column, and then click Remove Errors.
C. Select the Key column, and then click Remove Duplicates
D. Change the Aggregate Value Function of the pivot.
Answer: D
Explanation:
Explanation
References: https://docs.microsoft.com/en-us/power-bi/desktop-common-query-tasks

NEW QUESTION: 3
Which one of the following queries selects the customer whose order has the highest total price?
A. CriteriaBuilder cb = ...
CriteriaQuery<Customer> cq = cb.createQuery(Customer.class);
Root<Customer> c = cq.from(Customer.class);
Join<Customer, Order> o = c.join(Customer_.orders);
cq.select(c).distinct(true);
Subquery<Double> sq = cq.subquery(Double.class);
Root<Order> subo = sq.from(Order.class);
sq.select (cb.max ( subo.get (Order_ . Total Price) ) ) ;
cq.where(sq.all(o.get(Order_.totalPrice)));
B. CriteriaBuilder cb = ...
Criteria Query <Customer> cq = cb.create Query (Customer.class);
Root<Customer> c = cq.from(Customer.class);
Join<Customer, Order> o = c.join(Customer__.orders);
cq.select(c).distinct(true);
Subquery<Double> sq = cq.subquery(Double.class);
Root<Order> subo = cq.correlate(o);
sq.select(cb.max(subo.get(Order_.totalPrice)));
cq.where(cb.equal(o.get(Order_.totalPrice), cb.all(sq)));
C. CriteriaBuilder cb = ...
CriteriaQuery<Customer> cq = cb.createquery(customer.class)
Root<Customer> c = cq.from(Customer.class);
Join<Customer, Order> o = c.join(Customer__.orders);
cq.select(c).distinct(true);
Subquery<Double> sq = cq.subquery(Double.class);
Root<Order> subo = cq.correlate(o);
sq.select(cb.max(subo.get(Order_.totalPrice)));
cq.where(cb.equal(o.get(Order_.totalPrice), cb.all(sq)));
D. CriteriaBuilder cb = ...
CriteriaQuery<Customer> cq = cb.cteateQuery(Customer.class);
Root<Customer> c = cq.from(Customer.class);
Join<Customer, Order> o = c.join(Customer__.orders);
cq.select(c).distinct(true);
Subquery<Double> sq = cq.subquery(Double.class);
Root<Order> subo = cq.correlate(o);
sq.select(cb.max(subo.get(Order_.totalPrice)));
cq.where(cb.equal(o.get(Order_.totalPrice), cb.all(sq)));
Answer: A
Explanation:
Explanation/Reference:
Incorrect: Not a, not b, not C: use .from not .correlate.
Example:
CriteriaBuilder qb = em.getCriteriaBuilder();
CriteriaQuery<Number> cq = qb.createQuery(Number.class);
Root<Event> root = cq.from(Event.class);
cq.select(qb.max(root.get("dateProcessed")));
cq.where(qb.equal(Event.get("org"), qb.parameter(MyOrgType.class, "myOrg"))); em.createQuery(cq).setParameter("myOrg", myOrg).getSingleResult();
Note:
max(Expression<N> x)
Create an aggregate expression applying the numerical max operation.
Reference: javax.persistence.criteria, Interface CriteriaBuilder

NEW QUESTION: 4
A bank is designing an online customer service portal where customers can chat with customer service agents. The portal is required to maintain a 15-minute RPO or RTO in case of a regional disaster. Banking regulations require that all customer service chat transcripts must be preserved on durable storage for at least 7 years, chat conversations must be encrypted in-flight, and transcripts must be encrypted at rest. The Data Lost Prevention team requires that data at rest must be encrypted using a key that the team controls, rotates, and revokes.
Which design meets these requirements?
A. The chat application logs each chat message into two different Amazon CloudWatch Logs groups in two different regions, with the same AWS KMS key applied. Both CloudWatch Logs groups are configured to export logs into an Amazon Glacier vault with a 7-year vault lock policy with a KMS key specified.
B. The chat application logs each chat message into Amazon CloudWatch Logs. The CloudWatch Logs group is configured to export logs into an Amazon Glacier vault with a 7-year vault lock policy. Glacier cross-region replication mirrors chat archives to the backup region. Separate AWS KMS keys are specified for the CloudWatch Logs group and the Amazon Glacier vault.
C. The chat application logs each chat message into Amazon CloudWatch Logs. A subscription filter on the CloudWatch Logs group feeds into an Amazon Kinesis Data Firehose which streams the chat messages into an Amazon S3 bucket in the backup region. Separate AWS KMS keys are specified for the CloudWatch Logs group and the Kinesis Data Firehose.
D. The chat application logs each chat message into Amazon CloudWatch Logs. A scheduled AWS Lambda function invokes a CloudWatch Logs. CreateExportTask every 5 minutes to export chat transcripts to Amazon S3. The S3 bucket is configured for cross-region replication to the backup region. Separate AWS KMS keys are specified for the CloudWatch Logs group and the S3 bucket.
Answer: C

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