Full text search on encrypted data

问题:

Suppose I have a server storing encrypted text (end-to-end: server never sees plain text).

I want to be able to do full text search on that text.
I know this is tricky, but my idea is to use the traditional full text design ("list" and "match" tables where words are stored and matched with ids from the content table). When users submit the encrypted text, they also send a salted MD5 of the words and respective matches. The salt used is unique for each user and is recovered from their password.
(in short: the only difference is that the "list" table will contain hashed words)

Now, how vulnerable would this system be?
Note that I said "how vulnerable" instead of "how safe", because I acknowledge that it can't be totally safe.
I DO understand the tradeoff between features (full text search) and security (disclosing some information from the word index). For example, I understand that an attacker able to get the list and match tables could get information about the original, encrypted text and possibly be able to decipher some words with statistical analysis (however, being the salt unique for each user, this would need to be repeated for each user).

How serious would this threat be? And would there be any other serious threats?

DISCLAIMER
What I'm trying to build (and with the help of a cryptographer for actual implementation; right now I'm just trying to understand wether this will be possible) is a consumer-grade product which will deal with confidential yet not totally secret data.
My goal is just to provide something safe enough, so that it would be easier for an attacker to try stealing users' passwords (e.g. breaching into clients - they're consumers, eventually) rather than spending a huge amount of time and computing power trying to brute force the index or run complicated statistical analysis.

Comments in response to @Matthew

(may be relevant for anyone else answering)

1. As you noted, other solutions are not viable. Storing all the data inside the client means that users cannot access their data from other clients. Server-side encryption would work, but then we won't be able to give users the added security of client-side encryption.
   The only "true alternative" is just to not implement search: while this is not a required feature, it's very important to me/us.

2. The salt will be protected in the exactly same way as the users' decryption key (the one used to decrypt stored texts). Thus, if someone was able to capture the salt, he or she would likely be able to capture also the key, creating a much bigger issue.
   To be precise, the key and the salt will be stored encrypted on the server. They will be decrypted by the client locally with the user's password and kept in memory; the server never sees the decrypted key and salt. Users can change passwords, then, and they just need to re-encrypt the key and the salt, and not all stored texts. This is a pretty standard approach in the industry, to my knowledge.

3. Actually, the design of the database will be as follow (reporting relevant entries only). This design is like you proposed in your comment. It disallows proximity searches (not very relevant to us) and makes frequency less accurate.

   • Table content, containing all encrypted texts. Columns are content.id and content.text.
   • Table words, containing the list of all hashes. Columns are words.id and words.hash.
   • Table match, that matches texts with hashes/words (in a one-to-many relationship). Columns are match.content_id and match.word_id.

4. We would have to implement features like removing stopwords etc. Sure. That is not a big issue (will, of course, be done on the client). Eventually, those lists have always been of limited utility for international (i.e. non English-speaking) users.
   We expect the lookup/insert ratio to be pretty high (i.e. many lookups, but rare inserts and mostly in bulk).

5. Decrypting the whole hash database is certainly possible, but requires a brute force attack.
   Suppose the salt is kept safe (as per point 2 above). If the salt is long enough (you cited 32 bits... but why not 320? - just an example) that would take A LOT of time.

To conclude... You confirmed my doubts about the possible risk of frequency analysis. However, I feel like this risk is not so high. Can you confirm that?
Indeed, first of all the salt would be unique per each user. This means that one user must be attacked at time.
Second, by reporting words only once per text (no matter how many times they appear), frequency analysis becomes less reliable.
Third... Frequency analysis on hashed words doesn't sound as something as good as frequency analysis on a Caesar-shift, for example. There are 250,000 words in English alone (and, again, not all our users will be English-speaking), and even if some words are more common than others, I believe it'd be hard to do this attack anyway.

PS: The data we'll be storing is messages, like instant messages. These are short, contain a lot of abbreviations, slang, etc. And every person has a different style in writing texts, further reducing the risk (in my opinion) of frequency attacks.

回答1:

TL;DR: If this needs to be secure enough that it requires per-user end-to-end encryption: Don't do it.

Too long for a comment, so here goes - if I understand correctly:

1. You have encrypted data submitted by the user (client side encrypted, so not using the DB to handle).
2. You want this to be searchable to the user (without you knowing anything about this - so an encrypted block of text is useless).
3. Your proposed solution to this is to also store a list (or perhaps paragraph) of hashed words submitted from the client as well.

So the data record would look like:

• Column 1: Encrypted data block
• Column 2: (space) delimited hashed, ordered, individual words from the above encrypted text

Then to search you just hash the search terms and treat the hashed terms as words to search the paragraph(s) of "text" in column 2. This will definitely work - just consider searching nonsense text with nonsense search terms. You would even still be able to do some proximity ranking of terms with this approach.

Concerns:

1. The column with the individually hashed words as text will incredibly weak in comparison to the encrypted text. You are greatly weakening your solution as not only are there limited words to work from, the resultant text will be susceptible to word frequency analysis, etc.
2. If you do this: separately store a salt unrelated to the password. Given that a rainbow table will be easy to create if your salt is captured (dictionary words only) store it encrypted somewhere.
3. You will lose many benefits of FTS like ignoring words like 'the' - you will need to re-implement this functionality on your own if you want it (i.e. remove these terms on the client side before submitting the data / search terms).

Other approaches that you imply are not acceptable/workable:

1. Implement searching client side (all data has to exist on the client to search)
2. Centralized encryption leveraging the databases built in functionality

I understand the argument being that your approach provides the user with the only access to their data (i.e. you cannot see/decrypt it). I would argue that this hashed approach weakens the data sufficiently that you could reasonably work out a users data (that is, you have lowered the effort required to the point that it is very plausible you could decrypt a user's information without any knowledge of their keys/salts). I wouldn't quite lower the bar to describe this as just obfuscation, but you should really think through how significant this is.

If you are sure that weakening your system to implement searching like this makes sense, and the another approach is not sufficient, one thing that could help is to store the hashes of words in the text as a list of uniquely occuring words only (i.e. no frequency or proximity information would be available). This would reduce the attack surface area of your implementation a little, but would also lose the benefits you are implying you want by describing the approach as FTS. You could get very fast results like this though as the hashed words essentially become tags attached to all the records that include them. The search lookup then could become very fast (at the expense of your inserts).

*Just to be clear - I would want to be REALLY sure my business needs demanded something like this before I implemented it...

EDIT:

Quick example of the issues - say I know you are using 32-bit salts and are hashing common words like "the". 2^32 possible salts = 4 billion possible salts (that is, not that many if you only need to hash a handful of words for the initial attack). Assume the salt is appended or prepended, this still is only 8 billion entries to pre-calculate. Even if it is less common words you do not need to create too many lists to ensure you will get hits (if this is not the case your data would not be worth searching).

Then lookup the highest frequency salts for a given block of text in our each of our pre-calculated salt tables and use the match to see if it correctly decrypts other words in the text. Once you have a plausible candidate generate the 250,000 word English language rainbow table for that salt and decrypt the text.

I would guess you could decrypt the hashed data in the system in hours to days with access to the database.

回答2:

First, you have all of the normal vulnerabilities of password-based cryptography, which stem from users picking predictable passwords. It is common to crack more than 50% of passwords from real-world applications in offline attacks with less than two hours of desktop computing time.

I assume the full text encryption key is derived from the password, or is encrypted by a password-derived key. So an attacker can test guesses against a selection of hashed index keys, and once she finds the password, decrypt all of the documents.

But, even if a user picks a high-entropy password, frequency analysis on the index could potentially reveal a lot about the plain text. Although word order is lost in indexing (if you don't support proximity searches), you are essentially creating an electronic code book for each user. This index would be vulnerable to centuries of well-developed cryptanalytical techniques. Modern encryption protocols avoid ECB, and provide "ciphertext indistinguishability"—the same plain text yields different cipher text each time it's encrypted. But that doesn't work with indexes.

A less vulnerable approach would be to index and search on the client. The necessary tables would be bundled as a single message and encrypted on the client, then transported to the server for storage. The obvious tradeoff is the cost of transmission of that bundle on each session. Client-side caching of index fragments could mitigate this cost somewhat.

In the end, only you can weigh the security cost of a breach against the performance costs of client-side indexing. But the statistical analysis enabled by an index is a significant vulnerability.

回答3:

MSSQL Enterprise TDE encrypts Full-Text index as well as other indices when you set whole database encryption (Since 2008). in practice, it works pretty well, without a huge performance penalty. Can't comment on how, b/c it's a proprietary algo, but heres the docs.

https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/transparent-data-encryption-tde

it doesn't cover any of your application stack besides your db, but your FTS indices will work like normal and won't exist in plain text like they do in MySQL or PostGres. MariaDB and of course Oracle have their own implementation as well, from what i remember. MySQL and PGSQL do not.

As for passwords, TDE on all the implementations use AES keys, which can be rotated (though not always easily) - so the password vulnerability fall on the DBA's.

The problem is you need to pay for full enterprise licensing for MSSQL TDE (ie features not available in "standard" or "basic" cloud and on premise editions), and you do probably for TDE in Oracle as well. But if what you need is a quick solution and have the cash for enterprise licensing (probably cheaper than developing your own implementation), implementations are out there.