Encryption – What is Cloud KMS? What is his purpose / advantage of KMS? How it works? How can I use it? (AWS KMS, KMS GCP, Azure Key Vault)

What is the purpose / benefit of KMS?

  1. The KMS prevents the leakage of decryption keys, similar to an HSM, but HSMs are expensive and difficult to use. KMSs are inexpensive and easy to use because they have API endpoints.
  2. KMS shifts the problem of access control to encrypted data from a decryption key management problem (where granular access to impossible access and the ability to revoke it) is replaced by a identity and access management problem (where ACLs can be used to easily manage access, grant granular access, etc. and revoke access.)
  3. Increased auditability and control of access to encrypted data.

Give me a concrete example of a problem that KMS solves and has the advantage of using KMS:

KMS allows you to securely store encrypted secrets in git, so as to avoid leakage of decryption keys. You can control access to encrypted secrets at a specific level and revoke access without having to modify encrypted files.

What is Cloud KMS? How it works?

KMS is an encryption technique that corrects symmetric, asymmetric and HSM encryption faults. This is the basis of future encryption techniques such as encryption anchors.

Abrupt evolution of cryptography

  1. Symmetric encryption keys:
    • The long password is used for both encryption and decryption.
  2. Pairs of public-private key of asymmetric encryption:
    • The public key encrypts the data, the private key decrypts the encrypted data with the public key.
  3. HSM (hardware security modules):
    • Make sure the private key is not disclosed.
    • HSMs are expensive.
    • HSMs are not user friendly or automation.
  4. KMS Cloud (Key Management Services):
    • KMS is a trusted service that encrypts and decrypts data on behalf of customers. It essentially allows a user or machine to encrypt and decrypt data using their identity rather than encryption / decryption keys. (A client authenticates with a KMS, which verifies its identity against an ACL .If it has decryption rights, it can send encrypted data in a request to the KMS, which then decrypt them on behalf of the client and send the decrypted data to the client through a secure TLS tunnel.)
    • KMS are cheap.
    • KMS are exposed via the REST API, which makes them easy to use and automate.
    • KMS are extremely secure, they allow to spend a decade without leaving a key decryption.
    • The invention of the KMS encryption technique introduced 3 deadly features:
      1. When responding to a known violation:
        Before KMS decryption keys are disclosed: You can not revoke a decryption key, which means that you need to rotate multiple decryption keys, re-encrypt all data with the new keys, and try your best to purge the keys. old encrypted data. While doing all of this, you will have to struggle with management to get permission to cause downtime for multiple production systems, minimize downtime, and even if everything is well done, you may not be able to completely purge old encrypted data, as in the case of git history, and backups.
        After KMS, the identity information that has been disclosed is disclosed: the identity information can be revoked, it is useless. The nightmare of re-encrypting the data and purging the old encrypted data disappears. You must always rotate the secrets (identification information as opposed to decryption key), but the act of rotation becomes economical enough to be automated and planned as a preventative.
      2. The management of encrypted data goes from an impossible task involving distributed decryption keys to a trivial task of managing a centralized access control list. It is now possible to easily revoke, edit and assign granular access to encrypted data; and, as a bonus, since the KMS Cloud, IAM, and SSO federations integrate, you can leverage pre-existing user identities.
      3. Cryptographic anchoring techniques become possible:
        • Network Access Control Lists can be applied to the KMS so that data can only be decrypted in your environment.
        • KMS decryption rates can be monitored for a baseline. When an abnormal rate occurs, alerts and a rate limit can be triggered.
    • KMS decryption keys can be secured by an HSM.
    • The leakage possibilities of the decryption keys are practically nil because the clients do not interact directly with the decryption keys.
    • Cloud computing providers can afford to hire the best security professionals and implement the costly business processes necessary to keep key systems as secure as possible. Thus, the possibilities of leakage of the main keys are also almost zero.

How to use KMS?

  • Mozilla SOPS is a tool that encapsulates / summarizes the KMS, it is ideal for securely storing encrypted secrets in git.
  • Helm Secrets Plugin encapsulates Mozilla SOPS to allow you to securely store encrypted Kubernetes yubls in git, and then, when to apply them, the secret values ​​are decrypted transparently at the last minute, just before they happen. pass into a TLS tunnel encrypted directly on kube-apiserver, then Kubernetes can use KMS to encrypt Kubernetes secrets again, so that they are encrypted in a database etcd.
  • You can use it with any tool, independent of the cloud, click here to learn more.

factorization – heuristic bound on a type of general purpose factorization algorithm

First opinion that $ exists d: 1 <d <n, d | n $ is equivalent to $ exists x: 1 < gcd (x, n) <n $.

Let $ A $ be a general purpose factorization algorithm that at every step $ 1, cdots, t $ draws a number without a replacement $ a_i in mathbb {N} $ of the urn $ {m_n, m_n + 1, cdots, M_n-1, M_n } $ and tests if $ 1 < gcd (a_i, n) <n $. Besides the heuristic that numbers are drawn without replacement, some general purpose algorithms work in this way, for example Fermat factorization, test division or even quadratic sieve. The point here is that the algorithm generates "candidate" numbers $ a_i $ at each step and test if this number represents a "solution". Let $ X $ the number of $ i $-s with $ 1 < gcd (a_i, n) <n $ $ i = 1, cdots, t $. By definition of the algorithm, we must have a non-trivial probability to succeed, hence:

$$ 0 <P (X age 1) = 1 – P (X = 0) $$
from which it follows that $ P (X = 0) <$ 1. Let $ N_n = M_n-m_n + 1 $, $ d_n: = | {k | m_n the k the M_n, 1 < gcd (k, n) <n }| Then for all $ n in mathbb {N} $: $ d_n the N_n $.
We have:

$$ P (X = 0) = frac { binom {N_n-d_n} {t}} { binom {N_n} {t}} $$
and since $ P (X = 0) <$ 1 we have

$$ binom {N_n-d_n} {t} < binom {N_n} {t} $$
Suppose that there are some $ c in mathbb {N} $ such as $ forall n in mathbb {N} $ we have:
$$ t le | n | ^ c $$

or $ | n | = $ (number of bits to store $ n $) $ = text {floor} ( frac { log (n)} { log (2)}) $.
Since the algorithm has to read the number $ n $ we have $ | n | $ t.

Since $ frac {a ^ b} {b ^ b} the binom {a} {b} the frac {a ^ b} {b!} forall a, b $ it results by applying this $ a, b $-in equality to the last inequality $ P (X = 0) <$ 1 this:

$$ frac {(N_n – d_n) ^ t} {t ^ t} < frac {N_n ^ t} {t!} $$
which equals
$$ t log (N_n-d_n) + log (t!) <t ( log (N_n) + log (t)) $$

By Stirling we have:
$$ log ( sqrt {2 pi t} ( frac {t} {e}) ^ t) < log (t!) $$

From where we get:
$$ t log (N_n-d_n) + 1/2 log (2 pi t) + t log ( frac {t} {e}) <t ( log (N_n) + log (t) ) $$
and bringing all the terms not containing $ t $ on the left, and all the terms containing $ t $ on the right we get:
$$ log (1- frac {d_n} {N_n}) < log (t) – log (t / e) -1/2 log ((2 pi t) ^ {1 / t}) $$

Use inequalities for $ t $: $ | n | le t le | n | ^ c $ we have:
$$ log (1- frac {d_n} {N_n}) < log ( frac {| n | ^ {c-1} e} {(2 pi | n |) ^ {2 | n |} }) $$

And it follows:
$$ 1- frac {d_n} {N_n} < frac {| n | ^ {c-1} e} {(2 pi | n |) ^ {2 | n |}} $$
$$ 1- frac {| n | ^ {c-1} e} {(2 pi | n |) ^ {2 | n |}} < frac {d_n} {N_n} $$

But for $ | n | rightarrow infty $ we have
$$ lim_ {| n | rightarrow infty} frac {| n | ^ {c-1} e} {(2 pi | n |) ^ {2 | n |}} = 0 $$
$$ 1 = lim_ {| n | rightarrow infty} 1- frac {| n | ^ {c-1} e} {(2 pi | n |) ^ {2 | n |}} < lim_ {| n | rightarrow infty} frac {d_n} {N_n} the 1 $$
And so we get the contradiction $ 1 <$ 1.

My question is: if it is possible to prove that a general purpose factorization algorithm must generate candidate numbers $ a_i $ and test if figures are a solution? (I'm not saying that numbers should be drawn with / without replacing an urn, which is a heuristic).

php – What is the name of an object whose only purpose is to take formatted data from another and display them in different places?

Suppose I have the following object, whose job is to extract the raw data from a container and format it in a more enjoyable way, ready to be displayed. First, the object that does the formatting:

the Formatter class implements FormatterInterface
public function formatData (Container $ container)

public function getFormattedData ()
return $ this-> formated_data;

then the actual output object itself:

Outputter class
public service __construct (formattedInterface $ trainer)
$ this-> trainer = $ trainer;

public function outputDataToLocation ()
$ data = $ this-> formatter-> getFormattedData ();

foreach ($ data as $ formated_data_bit) {
echoDataToLocation ($ formatted_data_bit-> data, $ formated_data_bit-> location);

I can not find a good name for this. I need the name to indicate the fact that its purpose is to only produce data to a location.

hover – What is the purpose of this effect similar to a flashlight in Windows Callendar?

Is there a specific reason for Windows callendar to have this flashover-like effect?


On the contrary, it seems distracting to me by spreading the area of ​​your current mouse position. Is it supposed to have benefits on a single flyby of the box, or is it purely decorative?

What is the main purpose of using keywords in SEO?

What is the main purpose of using keywords in SEO?

SQL Server – Window Functions: What is the purpose of Rows Unbounded Preceding?

What is the purpose of using the rows Without Borders Previous clause in a window function?
I understand that this essentially means that you should not limit yourself to looking for the aggregate function, but how does this differ from the total absence of use of the clause? ?

Could you please provide an example to illustrate the difference between:




Note: my question is in the context of no limit for the following rows.

What is the purpose of the Allocation Callstacks button in the Unity Profile window?

I have an idea of ​​what this button does, but I can not find any specific information in the documentation.

What information does this button add to the profiling data? How can I see this additional information?

Screen capture of the Allocation Callstacks button in the Unity profiler, in a verified state

apache – Is there a certificate extensions manual, their purpose, their current usage, and conversion between formats?

I have a number of certificates in various binary formats and I would like to understand what these formats mean, their intended use and how to convert them (if possible).

For example, I have a .CER, a p12, a .pvkand one .pfx. I can recognize which one contains the private key and the public key, but think I would gain a better understanding of these formats, their history and the reason things are as they are.

If new standards are being developed or if a format has "flaws" (such as the inclusion / omission of intermediate certificates), this would also be useful.

Is such a concise guide available?

What is the main purpose of using keywords in SEO?

What is the main purpose of using keywords in SEO?

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  1. What is the main purpose of using keywords in SEO?

    What is the main purpose of using keywords in SEO?

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What is the main purpose of using keywords in SEO?

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