filefilego

FileFileGo Decentralized Storage & Data Sharing Network

The FileFileGo protocol is a peer-to-peer storage & data-sharing network designed for the web3 era, with an incentive mechanism, full-text search and a storage engine. Its decentralized architecture enables users to store and share data without censorship or a single point of failure. By leveraging game-theory concepts, FileFileGo incentivizes participation and ensures data availability while achieving fault-tolerance and preserving privacy.

FileFileGo is an open-source community project, with no centralized control or ownership. Its coin distribution is designed to be fair, with an emission of 40 FFG per block that decreases by half every 24 months. The protocol is launched without ICO/STO/IEO or pre-mine, relying on a Proof of Authority consensus algorithm that will eventually transition to Proof of Stake to allow more stakeholders to participate.

By supporting FileFileGo, users can help promote digital rights, privacy, freedom of information, and net neutrality. We encourage contributions and innovative ideas to ensure that the internet remains an open and decentralized platform.

The Innovation: Proof of Transfer with Zero-Knowledge Proof (ZK-Proof)

Problem

Let us suppose that node_1 needs to download some data_x, owned by node_2, and pay for the fees required by node_2. What happens in the case of Byzantine fault nodes? How do we verify successful data transfer to destination nodes and prevent the following malicious cases:

1. node_1 is a dishonest node that reports data_x as invalid, to avoid paying the fees.
2. node_2 is a dishonest node that serves data_y to node_1 and claims that it's data_x.

Solution

The network can resist Byzantine faults if node_x can broadcast (peer-to-peer) a value x, and satisfy the following:

1. If node_x is an honest node, then all honest nodes agree on the value x.
2. In any case, all honest nodes agree on the same value y.

The Proof of Transfer mechanism addresses the aforementioned issues by enabling honest nodes in the network to verify and reach consensus on the successful transfer of data_x from node_2 to node_1. This is accomplished through the use of verifiers, which are responsible for challenging participating nodes. While a straightforward approach would involve sending the required data to a verifier and then forwarding it to the destination node, this method can lead to bandwidth and storage bottlenecks, thereby reducing the overall network throughput. Therefore, the Proof of Transfer solution has been designed to minimize the bandwidth and storage/memory requirements associated with this process.

              ┌───────────┐
     ┌────────►[verifiers]◄─────────┐
     │        └───────────┘         │
┌────┴───┐                     ┌────┴───┐
│        │                     │        │
│ node_1 ◄─────────────────────► node_2 │
│        │                     │        │
└────────┘                     ├────────┤
                               │ data_x │
                               └────────┘

Algorithm

Let $x$ be the input file containing content divided into $N = 1024$ segments.

1. Divide the content of file $x$ into $N$ segments: $x = (x_1, x_2, \ldots, x_N)$

2. Calculate the Merkle Tree hash of the segments: Let $h(x_i)$ represent the hash of segment $x_i$. Construct the Merkle Tree by hashing adjacent segments in a binary tree structure:

   $h(x_i) = \text{HashFunction}(x_i)$ $h(x_{i,j}) = \text{HashFunction}(h(x_i) | h(x_j))$ where $|$ denotes concatenation. The root hash of the Merkle Tree is $h_{\text{root}} = h(x_{1,2})$, representing the overall content.

3. Shuffle the segments: Let $\pi$ be a permutation representing the shuffling of segments. $\pi : {1, 2, \ldots, N} \rightarrow {1, 2, \ldots, N}$ The shuffled segments are: $x_{\pi(1)}, x_{\pi(2)}, \ldots, x_{\pi(N)}$

4. Encrypt 1 percent of the shuffled segments: Let $M = \lfloor 0.01 \times N \rfloor$ be the number of segments to be encrypted. Let $E(x_i)$ represent the encryption of segment $x_i$. The encrypted segments are: $E(x_{\pi(1)}), E(x_{\pi(2)}), \ldots, E(x_{\pi(M)})$

The verification process

1. Decryption of Encrypted Segments: For each of the $M$ encrypted segments, apply the decryption function $D(E(x_{\pi(i)}))$ to obtain the decrypted version of the segment $x_{\pi(i)}$:

   $x_{\pi(i)}' = D(E(x_{\pi(i)}))$

2. Restoring the Shuffled Order: Since the segments were shuffled during the encryption process, they need to be restored to their original order using the inverse permutation $\pi^{-1}$:

   $x' = (x_{\pi^{-1}(1)}', x_{\pi^{-1}(2)}', \ldots, x_{\pi^{-1}(M)}')$

3. Merkle Tree Hash Calculation: Recalculate the Merkle Tree hash of the decrypted segments in the restored order. Construct the hash tree similarly to the original construction, but use the decrypted segments $x'$:

   $h'(x_i') = \text{HashFunction}(x_i')$ $h'(x_{i,j}') = \text{HashFunction}(h'(x_i') | h'(x_j'))$

4. Finally, the derived original Merkle root hash $h'_ \text{root}$ is obtained by hashing the two children of the root hash $h'_ \text{root} = \text{HashFunction}(h'(x_{1,2}') | h'(x_{3,4}'))$.

5. Consensus is achieved if the derived merkle root hash matches the original merkle root hash.

Calculating Merkle Root Hash

Consider a scenario involving a file containing the subsequent content:

FileFileGo_Network

Upon uploading a file to a storage provider, the merkle root hash of the file is computed through the segmentation of its content into distinct data segments.

The ensuing illustration depicts a simplified manifestation of the file's arrangement on the storage medium. Each individual box within the illustration symbolizes 1 byte of data.

┌───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┬───┐
│ F │ i │ l │ e │ F │ i │ l │ e │ G │ o │ _ │ N │ e │ t │ w │ o │ r │ k │
└───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┴───┘

To find the merkle root hash of this file, we break the file into smaller parts. For example, let's split the file into nine sections, and each part will have only two bytes.

    0       1       2       3       4       5      6       7        8
┌───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┐
│ F   i │ l   e │ F   i │ l   e │ G   o │ _   N │ e   t │ w   o │ r   k │
└───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┘

Now we take the hash of each segment:

segment 0: hash("Fi"), denoted by h0
segment 1: hash("le"), denoted by h1
segment 2: hash("Fi"), denoted by h2
segment 3: hash("le"), denoted by h3
segment 4: hash("Go"), denoted by h4
segment 5: hash("_N"), denoted by h5
segment 6: hash("et"), denoted by h6
segment 7: hash("wo"), denoted by h7
segment 8: hash("rk"), denoted by h8

and then we calculate the merkle root hash of the file by applying the algorithm.

Here's an example of how this algorithm operates:

            ┌───┬───┬───┬───┬───┬───┬───┬───┐
Data Blocks:│ a │ b │ c │ d │ e │ f │ g │ h │
            └───┴───┴───┴───┴───┴───┴───┴───┘
              0   1   2   3   4   5   6   7
              │   │   │   │   │   │   │   │
              └───┘   └───┘   └───┘   └───┘
               h01     h23     h45     h67
                │       │       │       │
                └───────┘       └───────┘
                h(h01+h23)     h(h45+h67)
                    │               │
                    │               │
                    └───────────────┘
         Merkle root:  h(h(h01+h23)+h(h45+h67))

Now, we possess a merkle root hash for the file, represented as mt(f), which is essentially another hash value.

Data Request

When a request to retrieve data reaches a storage provider, the provider rearranges the data segments in a random order. For instance, consider the sequence of data segments:

random segments [ 1, 5, 2, 4, 7, 6, 3, 0, 8 ], which translates to the following arrangement:

   1       5        2       4      7        6       3       0       8

┌───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┐
│ l   e │ _   N │ F   i │ G   o │ w   o │ e   t │ l   e │ F   i │ r   k │
└───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┘

Subsequently, the provider generates a symmetric key and initialization vector (IV) to encrypt a portion of these segments. In this illustration, we'll opt for encrypting 25% of the segments, which equates to 2 segments. Furthermore, we'll encrypt every 4 segments, implying that we will encrypt the 0th and 4th segments:

                       25% Segment Encryption = 2 segments

┌───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┐
│ l   e │ _   N │ F   i │ *   * │ w   o │ e   t │ l   e │ *   * │ r   k │
└───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┘

Now, the aforementioned data will be provided to the data requester. Simultaneously, the key/IV, the randomized order of segments, and the contents of segments 0 and 4 are transmitted to the data verifier. It's important to highlight that the downloader possesses Zero-Knowledge regarding both the order of segments within the file and the encryption key/IV.

You might be concerned about the possibility of someone creating a script to attempt various combinations of segments to determine the original order, potentially leading to a security vulnerability and a potential attack.

To provide further insight, consider that a file is divided into approximately 1024 segments (or slightly fewer) in a real-world scenario, and these segments are then randomized. For an attacker to reconstruct the original segment order, they would need to carry out a "permutation without repetition." The total count of ways to arrange these file segments is given by n! (factorial), which amounts to 1024! in this instance. (https://coolconversion.com/math/factorial/What-is-the-factorial-of_1024_%3F)

The attacker's subsequent step involves attempting to acquire the key and IV used for encrypting the two segments. However, it's worth noting that this task is currently considered impossible based on existing vulnerabilities in the field.

Following this, the file downloader must request the encryption key/IV and the randomized order of file segments from a designated data verifier within the network.

Verification

The data downloader sends a request to the data verifier, seeking the encryption key/IV and the randomized segments. This request is accompanied by the segment hashes of the downloaded file, which are presented as follows:

h1
h5
h2
h(enc(4))
h7
h6
h3
h(enc(0))
h8

The data verifier undertakes encryption and hashing for segments 0 and 4, resulting in the following hash values:

h1
h5
h2
h4
h7
h6
h3
h0
h8

Lastly, the data verifier reorganizes the segments according to the randomized order generated by the file hoster during the data transfer to the requester. This process yields the original sequence of segment hashes:

h0
h1
h2
h3
h4
h5
h6
h7
h8

Ultimately, through the execution of the merkle root hash computation, the data verifier deduces the original merkle root hash without necessitating complete local access to the entire file content.

Upon confirming that the derived merkle root hash matches the original one, we have effectively established a mathematical proof that the data downloader possesses all the requested data. Subsequently, the data verifier transmits the encryption key/IV and the randomized segments order to the data downloader, leading to the automatic release of fees to the file hoster.

Flow

In this section, the complete life cycle of a data transfer verification is demonstrated.

1. Data Discovery: Numerous wire protocols have been developed to facilitate communication among nodes in a network. Among these protocols, the Data Query protocol is often the first utilized by nodes. This protocol enables nodes to broadcast queries throughout a gossip channel and retrieve responses via direct communication. Essentially, a node sends a request inquiring about which node hosts a particular piece of data.

             1. Data Query Request
                    ┌───────┐
    ┌───────────────►[nodes]├───────────────┐
    │               └───────┘               │
┌───┴────┐                             ┌────▼───┐
│        │                             │        │
│ node_1 │                             │ node_2 │
│        │                             │        │
└───▲────┘                             └───┬────┘
    │        2. Data Query Response        │
    └──────────────────────────────────────┘

1. Smart Contract: The Data Query Response payload contains all the information needed to prepare a smart contract transaction. This transaction is then broadcasted to the network which is then selected by a verifier.

┌──────────────────────────────────────┐
│              TRANSACTION             │
├──────────────────────────────────────┤
│  Data :                              │
│        - Data query response         │
│        - Remote node signature       │
│  Value:                              │
│        - Fees required by node       │
│                                      │
│  Fees :                              │
│        - Fees collected by verifier  │
│                                      │
│  To   :                              │
│        - Network verifier            │
└──────────────────────────────────────┘

1. Verification: Verifier(v1) communicates with the participating nodes and generates a challenge for the node which hosts the data(node_2). The challenge consists of the following steps:

• node_2 should create a Merkle tree that matches the original Merkle root of data_x uploaded in the first place.
• v1 decides the order and the number of blocks/data ranges to be sent to node_1 by node_2. We don't want to reveal the order of blocks to node_1 yet.
• v1 asks node_2 for a fixed range of data, which will be encrypted using a random key k1 as data_enc by v1 and sent to node_1.

In this stage, node_1 possesses some data_z and data_enc but lacks the knowledge of how to combine them to obtain the original file. The verifier, v1, is able to verify the integrity of the data transmitted to node_1 and, if they match the original Merkle tree's identity, the decryption key k1 is provided to node_1. Additionally, the block order is sent to node_1, enabling the reassembly of all the parts to form the original data. Once this process is complete, v1 releases the fees to node_2.

The use of this algorithm enables the simultaneous attainment of Proof of Transfer and Proof of Data Possession.

Installation

Follow the instructions to compile and install filefilego

https://filefilego.com/documentation/docs/installation.html#prerequisites

FileFileGo Components

Features

FileFileGo is a decentralized network that incorporates the robustness of Blockchain/Cryptocurrency, DHT, and BitTorrent's innovative technology to form an unassailable infrastructure.

• The platform employs Blockchain technology for indexing and other network metadata and logic, ensuring a secure and efficient system.
• Encrypted traffic protects user data from third-party traffic inspection, while a privacy-centric design relays traffic through a set of intermediate peers.
• The peer-to-peer design replicates the network's state on each full node, enhancing data reliability.
• The network's native cryptocurrency serves as the "fuel" and guarantees an extremely low and conditional transaction fee compared to Ethereum/Bitcoin.
• With a dynamic block size and block-time of 10 seconds, FileFileGo ensures quick and seamless transactions.
• FileFileGo also offers an RPC interface that allows developers to build DApps on the network.

Blockchain Consensus Algorithm

To achieve a block-time of 10 seconds, FileFileGo requires a consensus algorithm that is both efficient in processing a high volume of transactions and conserves processing power. For the initial phase, we have selected Proof of Authority (PoA) as our consensus algorithm. In the future, a Proof of Stake (PoS) mechanism will replace the current algorithm.

Using PoW-based algorithms for new blockchains poses a risk, as there are already substantial pools of computing power available that could be used for 51% attacks. Therefore, we have opted for PoA, which is safe by design and provides the necessary efficiency to support our high transaction volume requirements.

Proof of Authority / Validator+Verifier Algorithms

The identities of validators are hardcoded into the blockchain and can be verified by examining the Genesis block's coinbase transaction. Participating nodes can easily verify the authenticity of these identities by checking the block's signatures.

Proof of Stake

As we move forward, the current PoA mechanism will be replaced by proof-of-stake to enable multiple parties to participate in the block mining process. Our goal for blockchain governance is to encourage more parties and developers to become involved and increase stakeholder engagement. One of the incentives for achieving this goal is the Proof-of-Stake mechanism.

Blockchain and Metadata/Accounting

To simplify transaction and state mutation, FileFileGo adopts a different approach than UTXO-like structures. Rather than using such structures, we store accounting and metadata as regular database rows, while retaining the raw blocks in their original format within the database. This approach helps to eliminate unnecessary complexity.

Technical Details

In this section, we will provide an overview of technical terms and concepts used in FileFileGo.

Channels

Channels in FileFileGo enable users to organize and group data into distinct buckets or folders. For instance, all content on ubuntu.com could be placed in a channel named "Ubuntu Official." The user who creates a channel receives all permissions necessary for updates and other channel-related operations.

Channels are structured in a node-chain format and can be identified as a node without a ParentHash.

Sub Channel

The concept of a sub-channel is to be able to categorize data even further. For instance, documents, pictures, or music.

Entry & File/Directory

In filefilego an Entry represents a post or a piece of data that contains more information about the entry itself rather than categorization/ordering. File and Directory can be placed into an Entry.

Data Storage Layer

Storage Engine is the storage layer that tracks binary data, which are used by hash pointers within the blockchain to refer to a piece of data. The NodeItem structure has a field called FileHash which refers to the binary hash and is in the form of "{HASH_ALGORITHM}:>{DATA_HASH}". We would like to keep the metadata of the hashing algorithm used as it might be useful in the future.

Full-text Index/Search

In FileFileGo, search accuracy and flexibility are equally important as the core blockchain functionality. We aim to enable users to construct complex queries, including binary searches, using a specific query language. For example, queries of the following types should be possible:

1. Required or inclusive ("filefilego coin"), which means both "filefilego" and "coin" are required in the search results.
2. Optional or exclusive ("filefilego currency"), which means one of those words can be excluded from the search results.

Developing a query language that supports such complex queries is a powerful tool that can significantly enhance the search engine's accuracy.

It is also possible to enable a node's full-text indexing functionality using the --search CLI flag.

Storage Engine

The storage layer keeps track of binary files and uses hashes to represent a piece of information within the blockchain. This feature can be turned on by using the following flags:

... --storage --storage_dir="/somewhere/to/store/data" --storage_token="somelongtokenhere" --storage_fees_byte="10000" ...

--storage_dir should be a directory that exists with appropriate read/write permissions. Please note that full nodes can work without this mechanism. storage_token is a token that grants admin rights to a token so it can create other tokens using the HTTP API. This is useful when access right is needed by web apps or distinct users and --storage_fees_byte="10000" is the fees charged per byte of data.

Coin Distribution

The Coin

Unit	Value
FFGOne	1
KFFG	1.000
MFFG	1.000.000
GFFG	1.000.000.000
MicroFFG	1.000.000.000.000
MiliFFG	1.000.000.000.000.000
FFG (Default unit)	1.000.000.000.000.000.000
ZFFG	1.000.000.000.000.000.000.000

Total Supply: 500 Million FFG Validation/Stake Reward: 40 FFG per Block Supply Decrease Rate: Divide by 2 every 24 months