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NEW QUESTION: 1
You execute the following PL/SQL:
Which two statements are true?
A. Fine-Grained Auditing (FGA) is enabled for the PRICEcolumn in the PRODUCTStable for SELECT statements only when a row with PRICE > 10000is accessed.
B. FGA is enabled for the PRODUCTS.PRICEcolumn and an audit record is written whenever a row with PRICE > 10000is accessed.
C. FGA is enabled for all DML operations by JIMon the PRODUCTS.PRICEcolumn.
D. FGA is enabled for the PRICEcolumn of the PRODUCTStable and the SQL statements is captured in the FGA audit trial.
Answer: A,D
Explanation:
Explanation/Reference:
Explanation:
DBMS_FGA.ADD_POLICY(object_schema => 'hr',object_name => 'emp',policy_name =>
'chk_hr_emp',audit_condition => 'dept = "SALES" ',audit_column => 'salary'statement_types =>
'insert,update,delete,select');
Default value for statement_types is SELECT
Setting audit_trail to DBMS_FGA.DB sends the audit trail to the SYS.FGA_LOG$ table in the database
and omits SQL Text and SQL Bind.
Setting audit_trail to DBMS_FGA.DB+EXTENDED sends the audit trail to the SYS.FGA_LOG$ table in
the database and includes SQL Text and SQL Bind.
Setting audit_trail to DBMS_FGA.XML writes the audit trail in XML files sent to the operating system
and omits SQL Text and SQL Bind.
Setting audit_trail to DBMS_FGA.XML+EXTENDED writes the audit trail in XML files sent to the
operating system and includes SQL Text and SQL Bind.
Default value fo audit_trail parameter in DBMS_FGA.ADD_POLICY is DB+EXTENDED
NEW QUESTION: 2
What type of a vulnerability/attack is it when the malicious person forces the user's browser to send an authenticated request to a server?
A. Cross-site request forgery
B. Server side request forgery
C. Cross-site scripting
D. Session hijacking
Answer: A
NEW QUESTION: 3
A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold.
What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?
A. L1 norm
B. Root Mean Square Error (RMSE)
C. Misclassification rate
D. Receiver operating characteristic (ROC) curve
Answer: D
Explanation:
https://docs.aws.amazon.com/machine-learning/latest/dg/binary-model-insights.html