Analysis: Is there an increase in account recovery request amidst scams and phishings in Steemit?

Introduction

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It is sad to say that there are peoples who take advantage with the other. In the recent increase in the scam and phishing applications and websites, many users lost their accounts to this websites. So, I want to know and share an analysis that will look into the trends of the Account Recovery in Steemit by looking into the following data:

• Daily counts of account recovery and status of recovery which is taken from the TxAccountRecovers table of the SteemSQL with in the timestamp, January 1 to March 31, 2018.

In this way, i could help give information on the chances of their account to be recovered. At the same time, present and interpret this data through visuals and statistical treatment.

Outline of the Analysis

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I. Scope of Analysis

II. Data Presentation and Analysis

III. Conclusion

IV. Tools and Query

I. Scope of Analysis

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The analysis performed using the data extracted from @arcange 's SteemSQL database on 11:00 am (UCT), April 20, 2018.

• The data extracted is the daily counts of account recovery and status of recovery which is taken from the TxAccountRecovers table of the SteemSQL with in the timestamp, January 1 to March 31, 2018. This is done to evaluate the effect of scam and phishing applications and website to the increase in the numbers of account recovery.

II. Data Presentation and Analysis

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A total of 707 account to be recovered was listed on the TxAccountRecovers table of the SteemSQL database for the timestamp between January 01, 2018 to March 31, 2018. On average, there are 235 account listed for recovery in the stated time frame per month. This is a bit higher as compared to the last year's 67 account per month. In December 2017, we can only identify 124 account for recovery. This 111 accounts short of the present average. (You can browse my earlier Account Recovery Analysis for 2017.)

The alarming increase in the numbers of account to be recovered entails that there is a good basis for developers to strength en the user's security and protection interface in Steemit. This surge could be attributed to the increasing numbers of scam and phishing applications and links, either internally or externally. You can visit @arcange's blog for some list of phishing apps and website.

It is sad to know that there is an increasing numbers of lost accounts in Steemit, excluding those who did not applied or requested for recovery. Fortunately, for users whom filed a request for recovery, there is a good chance of recovering your account as shown by the numbers.

For the total of 707 accounts listed, 75% of which where recovered which is equal to 533 against 25% of which was not recovered, amounting to 174. If you set your recovery account to @steem, close to 95.87% chance of recovery is to be expected. Within the timestamp clause of this analysis, @steem recovered a total of 511 which is good for 85% of all account listed under this recovery account. So, there are 19 more accounts recovered as to one uncovered for @steem on average. The other recovery account constitutes 14% of all recovery transactions whereas 65% odds of your account to be not recovered. It has a 35% success rate in recovering an account.

Generally, numbers of account listing for recovery will have a substantial increase in April 2018 based on the current listed accounts. A doubled increase in the average from the last year to date shows that there will be a projected increase in the number of accounts to be recovered. On the other hand, we can expect that @steem could sustain a better or equal to the current 95.87% recovery percentage for the coming months.

III. Conclusion

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The following conclusions can be drawn from the analysis:

• On average, there are 235 account listed for recovery on top of 707 total listed accounts. There is a 75% chance of recovery against 25% odds of recovery.

• A 235 account to be recovered per month for the stated timestamp against 67 from the 2017 average. This indicates that there is sudden increase in the number of account lost in the platform in the start of 2018, which pump the numbers of recovery requests. .

• A close to 95.87% chance of recovery is to be expected for recovery account: @steem. It has recovered a total of 511 which is good for 85% of all account listed under this recovery account within the timestamp condition. By which, we can conclude that there are 19 more accounts recovered as to one uncovered for @steem on average. We can expect that @steem could sustain a good recovery success rate.

• There is an alarming increase in the number of request for recovery that could be co-related to the increasing numbers of scam and phishing application and websites in Steemit. In addition, We can draw a doubled increase in the average from the last year to date shows that there will be a projected increase in the number of accounts to be recovered.

IV. Tools and Query

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I extracted the data from SteemSQL by importing it on Microsoft Excel using SQL Queries. I used Microsoft Excel to analyze, visualize and create a graph for the data. The data is extracted by using COUNT() function from TxAccountRecovers. The query was varied depending on the where clause. To take the full count of all request, I set the TxAccountRecovers.recovered='FALSE' while TxAccountRecovers.recovered='TRUE' fro recovered account. In terms of the recovery account, I used the full data query and do post query data processing on excel.

    MONTH(TxAccountRecovers.timestamp) AS [MONTH],
    DAY(TxAccountRecovers.timestamp) AS [DAY],
    COUNT(TxAccountRecovers.ID) AS [TRANSACTION],
    COUNT(TxAccountRecovers.recovery_account) AS [RECOVERY_ACCOUNT],
    COUNT(TxAccountRecovers.account_to_recover) AS [ACCOUNT_TO_RECOVER]
FROM
    TxAccountRecovers (NOLOCK)
WHERE
    YEAR(TxAccountRecovers.timestamp) = 2018 AND
    TxAccountRecovers.recovered = 'FALSE' AND
    TxAccountRecovers.timestamp >= '2018/01/01' AND
    TxAccountRecovers.timestamp < '2018/04/01'
GROUP BY
    MONTH(TxAccountRecovers.timestamp),
    DAY(TxAccountRecovers.timestamp)

/* For full data */
SELECT
    MONTH(TxAccountRecovers.timestamp) AS [MONTH],
    DAY(TxAccountRecovers.timestamp) AS [DAY],
    TxAccountRecovers.ID,
    TxAccountRecovers.recovery_account,
    TxAccountRecovers.account_to_recover
FROM
    TxAccountRecovers (NOLOCK)
WHERE
    YEAR(TxAccountRecovers.timestamp) = 2018 AND
    TxAccountRecovers.timestamp >= '2018/01/01' AND
    TxAccountRecovers.timestamp < '2018/04/01'
GROUP BY
    MONTH(TxAccountRecovers.timestamp),
    DAY(TxAccountRecovers.timestamp),
   TxAccountRecovers.ID,
   TxAccountRecovers.recovery_account,
    TxAccountRecovers.account_to_recover

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Posted on Utopian.io - Rewarding Open Source Contributors

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