Cloud Hosting Privacy Php

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Cloud Hosting Privacy Php

Cloud Hosting Privacy Php

Many Amazon Web Services customer workflows require receiving sensitive and regulated data such as Payment Card Industry Data (PCI), Personal Information (PII), and Protected Health Information (PHI). In this post, I’ll show you a method designed to protect sensitive data throughout its lifecycle in . This method can help improve your data security posture and be useful in meeting data protection regulatory requirements applicable to your organization to protect data at rest, in transit and in use.

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An existing method of protecting sensitive data is to use the field-level encryption feature offered by Amazon CloudFront. This CloudFront feature protects sensitive data fields in requests at the edge of the network. Selected fields are protected when received and remain protected within the application stack. The notion of protecting sensitive data early in its lifecycle is a highly desirable security architecture. However, CloudFront can protect a maximum of 10 fields and only within HTTP(S) POST requests that carry HTML-encoded payloads.

If your requirements exceed CloudFront’s built-in field-level encryption, such as the need to handle different application data formats, different HTTP methods, and more than 10 sensitive fields, you can implement field-level encryption yourself using Lambda@Edge. in CloudFront. In terms of choosing an appropriate encryption scheme, this problem requires an asymmetric cryptographic system that allows public keys to be openly distributed to the edges of the CloudFront network, while the corresponding private keys are securely stored in the core of the network. One such popular asymmetric cryptographic system is RSA. Therefore, we implement a Lambda@Edge function that uses asymmetric encryption using the RSA cryptosystem to protect any number of fields in any HTTP(S) request. We will discuss the solution using a JSON payload example, although this approach can be applied to any payload format.

Key management is a complex part of any encryption solution. To solve this, I use a Key Management Service (KMS). KMS simplifies the solution and offers an improved security posture and operational benefits, which are described later.

You can protect data in transit over individual communication channels using TLS (Transport Layer Security) and at rest in individual storage using volume encryption, object encryption, or database table encryption. However, if you have sensitive workloads, you may need additional protection that can track data as it moves through the application stack. Fine-grained data protection techniques such as field-level encryption make it possible to protect sensitive data fields in larger application data, while leaving non-sensitive fields in plain text. This approach allows an application to perform business functions on non-sensitive fields without the overhead of encryption and allows fine-grained control over which fields can be accessed by which parts of the application.

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The best practice for protecting sensitive data is to reduce its exposure throughout its lifecycle. This means protecting data as soon as possible after it is received and ensuring that only authorized users and applications have access to the data only when and as needed. CloudFront, combined with the flexibility provided by Lambda@Edge, provides a suitable environment at the edge of the network to protect sensitive data when received into .

Since downstream systems do not have access to sensitive data, data exposure is reduced, helping to minimize your compliance requirements for audit purposes.

The idea behind field-level encryption is to protect sensitive data fields individually while preserving the structure of the application’s payload. An alternative is full payload encryption, where the entire application payload is encrypted as a binary blob, rendering it unusable until everything is decrypted. With field-level encryption, non-sensitive data that remains in clear text remains usable for normal business functions. When retrofitting data protection into existing applications, this approach can reduce the risk of application failure because the data format is preserved.

Cloud Hosting Privacy Php

The following figure shows how JSON-constructed PII data fields that an application considers sensitive can be transformed from plaintext to ciphertext using a field-level encryption mechanism.

Pdf) The Factors Affecting On Managing Sensitive Data In Cloud Computing

You can change plaintext to encrypted, as shown in Figure 1, by using the Lambda@Edge function to perform field-level encryption. I discuss the encryption and decryption processes separately in the following sections.

Figure 2 shows CloudFront invoking a Lambda@Edge function while processing a client request. CloudFront offers several integration points for calling Lambda@Edge functions. Since you are processing a client request and your encryption behavior is related to the requests being forwarded to the origin server, you want your function to fire on request events originating in CloudFront. An origin request event represents an internal state transition in CloudFront that occurs immediately before CloudFront forwards the request to the downstream origin server.

You can associate your Lambda@Edge with CloudFront as described in Adding Triggers Using the CloudFront Console. A screenshot of the CloudFront console is shown in Figure 3. The selected event type is Origin Request and the Include Body checkbox is selected to send the request body to Lambda@Edge.

The Lambda@Edge function acts as a programmable hook in the CloudFront request processing flow. Using the function, you can replace the text of the incoming request with the text of the request with encrypted sensitive data fields.

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In KMS, you can generate an RSA Customer Managed Key (CMK) as described in the section Generating asymmetric CMKs. This is done at system configuration time.

Note: You can use your existing RSA key pairs or generate new ones externally using OpenSSL commands, especially if you need to perform RSA decryption and key management independently of KMS. Your choice does not affect the basic encryption design pattern presented here.

RSA key generation in KMS requires two inputs: key length and usage type. In this example, I created a 2048-bit key and assigned it to be used for encryption and decryption. The RSA CMK cryptographic configuration created in KMS is shown in Figure 4.

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Of the two encryption algorithms shown in Figure 4 – RSAES_OAEP_SHA_256 and RSAES_OAEP_SHA_1, this example uses RSAES_OAEP_SHA_256. The combination of a 2048-bit key and the RSAES_OAEP_SHA_256 algorithm allows you to encrypt a maximum of 190 bytes of data, which is enough for most PII fields. You can choose a different key length and encryption algorithm depending on your security and performance requirements. How to choose a CMK configuration contains information about RSA key specifications for encryption and decryption.

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Using KMS to manage RSA keys versus custom key management eliminates this complexity and can help you:

You must extract the RSA public key from KMS to include it in your Lambda deployment package. You can do this from the management console, through the KMS SDK, or by using the command line interface (CLI) get-public-key command. Figure 5 shows the public key copy and download options on the Public Key tab of the KMS console.

Note: As we will see in the code example in step 3, we put the public key in the Lambda@Edge deployment package. This is a permitted practice because public keys in asymmetric cryptographic systems are not secret and can be freely distributed to entities that need to perform encryption. Alternatively, you can use Lambda@Edge to query KMS for the public key at runtime. However, this introduces latency, increases the load compared to your KMS account quota, and increases your costs. General patterns of using external data in Lambda@Edge are described in Using external data in Lambda@Edge. Step 2 – Processing HTTP API requests with CloudFront

CloudFront receives an HTTP(S) request from the client. CloudFront then calls Lambda@Edge while processing origin requests and includes the HTTP request body in the invocation.

Pdf) Cspcr: Cloud Security, Privacy And Compliance Readiness

The Lambda@Edge function processes the HTTP request body. The function extracts sensitive data fields and performs RSA encryption on their values.

The event structure passed to the Lambda@Edge function is described in Lambda@Edge Event Structure. After the event structure, you can extract the HTTP request body. In this example, the HTTP payload is assumed to carry a JSON document based on a specific schema defined as part of the API contract. The input JSON document is parsed by the function and converted into a Python dictionary. Python’s native dictionary operators are then used to extract the values ​​of the sensitive fields.

Note: If you don’t know the structure of the API payload in advance, or you’re dealing with an unstructured payload, you can use techniques like regular expression searches and checksums to look for patterns of sensitive data and target them accordingly. For example, primary credit card account numbers include a programmatically detectable Luhn checksum. In addition, services such as Amazon Comprehend and Amazon Macie can be used for detection

Cloud Hosting Privacy Php

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