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NEW QUESTION: 1

A. Option A
B. Option D
C. Option C
D. Option B
Answer: B
Explanation:
The Set-DnsServerCache cmdlet modifies cache settings for a Domain Name System (DNS) server.
Run Set-DnsServerCache with the -LockingPercent switch.
/ -LockingPercent<UInt32>
Specifies a percentage of the original Time to Live (TTL) value that caching can consume.
Cache locking is configured as a percent value. For example, if the cache locking value is set to 50, the DNS server does not overwrite a cached entry for half of the duration of the TTL. By default, the cache locking percent value is 100. This value means that the DNS server will not overwrite cached entries for the entire duration of the TTL.
Note. A better way would be clear the DNS cache on the DNS server with either Dnscmd /ClearCache (from command prompt), or Clear-DnsServerCache (from Windows PowerShell).
Reference: Set-DnsServerCache
http://technet.microsoft.com/en-us/library/jj649852.aspx
Incorrect:
Not A. You need to use the /config parameter as well:
You can change this value if you like by using the dnscmd command:
dnscmd /Config /CacheLockingPercent<percent>

NEW QUESTION: 2
Audits are either done based on the status of a system or application at a specific time or done as a study over a period of time that takes into account changes and processes.
Which of the following pairs matches an audit type that is done over time, along with the minimum span of time necessary for it?
A. SOC Type 1, one year
B. SOC Type 2, one year
C. SOC Type 2, one month
D. SOC Type 2, six months
Answer: D
Explanation:
Explanation
SOC Type 2 audits are done over a period of time, with six months being the minimum duration. SOC Type 1 audits are designed with a scope that's a static point in time, and the other times provided for SOC Type 2 are incorrect.

NEW QUESTION: 3
ハッシュ付きのメッセージが送信されています。攻撃者がメッセージを変更して本物のハッシュ値c * nを生成するリスクは、次の方法で緩和されます。
A. 送信者の公開鍵を使用してメッセージを暗号化します。
B. 元のメッセージと同じサイズのハッシュ出力を生成し、
C. ハッシュアルゴリズムと共に秘密鍵mを使用します。
D. 受信者に異なるハッシュアルゴリズムの使用を要求する、
Answer: C

NEW QUESTION: 4
Why would anomaly detection IDSs often generate a large number of false positives?
A. Because they can only identify correctly attacks they already know about.
B. Because normal patterns of user and system behavior can vary wildly.
C. Because they can't identify abnormal behavior.
D. Because they are application-based are more subject to attacks.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
An Anomaly-Based Intrusion Detection System, is a system for detecting computer intrusions and misuse by monitoring system activity and classifying it as either normal or anomalous. The classification is based on heuristics or rules, rather than patterns or signatures, and attempts to detect any type of misuse that falls out of normal system operation. This is as opposed to signature-based systems, which can only detect attacks for which a signature has previously been created.
In order to determine what is attack traffic, the system must be taught to recognize normal system activity.
This can be accomplished in several ways, most often with artificial intelligence type techniques. Systems using neural networks have been used to great effect. Another method is to define what normal usage of the system comprises using a strict mathematical model, and flag any deviation from this as an attack. This is known as strict anomaly detection.
Anomaly-based Intrusion Detection does have some shortcomings, namely a high false-positive rate and the ability to be fooled by a correctly delivered attack.
A cause of the high false-positive rate is that normal patterns of user and system behavior can vary wildly.
Different people do things in different ways. These can appear as 'anomalies' to the IDS and generate a false positive.
Incorrect Answers:
A: It is not true that anomaly detection IDSs can only identify correctly attacks they already know about.
This statement describes signature-based IDSs.
B: It is not true that anomaly detection IDSs are application-based and are more subject to attacks. They can be hardware-based. Furthermore, hackers attack computer systems; they don't attack IDSs.
C: It is not true that anomaly detection IDSs cannot identify abnormal behavior; that's exactly what they do.
References:
https://en.wikipedia.org/wiki/Anomaly-based_intrusion_detection_system

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