條件式動態資料遮罩 - Amazon Redshift

本文為英文版的機器翻譯版本,如內容有任何歧義或不一致之處,概以英文版為準。

條件式動態資料遮罩

您可以在遮罩運算式中使用條件運算式建立遮罩政策,以在儲存格層級上遮罩資料。例如,您可以建立一個遮罩政策,根據該資料列中其他資料欄的值,將不同的遮罩套用至值。

以下是使用條件式資料遮罩來建立並附加遮罩政策的範例,該遮罩政策會修改涉及詐騙的部分信用卡號碼,同時完全隱藏所有其他信用卡號碼。您必須是超級使用者或具有 sys:secadmin 角色才能執行此範例。

--Create an analyst role. CREATE ROLE analyst; --Create a credit card table. The table contains an is_fraud boolean column, --which is TRUE if the credit card number in that row was involved in a fraudulent transaction. CREATE TABLE credit_cards (id INT, is_fraud BOOLEAN, credit_card_number VARCHAR(16)); --Create a function that partially redacts credit card numbers. CREATE FUNCTION REDACT_CREDIT_CARD (credit_card VARCHAR(16)) RETURNS VARCHAR(16) IMMUTABLE AS $$ import re regexp = re.compile("^([0-9]{6})[0-9]{5,6}([0-9]{4})") match = regexp.search(credit_card) if match != None: first = match.group(1) last = match.group(2) else: first = "000000" last = "0000" return "{}XXXXX{}".format(first, last) $$ LANGUAGE plpythonu; --Create a masking policy that partially redacts credit card numbers if the is_fraud value for that row is TRUE, --and otherwise blanks out the credit card number completely. CREATE MASKING POLICY card_number_conditional_mask WITH (fraudulent BOOLEAN, pan varchar(16)) USING (CASE WHEN fraudulent THEN REDACT_CREDIT_CARD(pan) ELSE Null END); --Attach the masking policy to the credit_cards/analyst table/role pair. ATTACH MASKING POLICY card_number_conditional_mask ON credit_cards (credit_card_number) USING (is_fraud, credit_card_number) TO ROLE analyst PRIORITY 100;