Author: comptroller

DMARC Email Authentication

We all get far too many emails claiming to be from a well known company but actually sent by scammers and spammers. Internet Service Providers trap a large percentage of these fake messages and delete them before they they can get to their intended target, but a lot still get through to us.

What can be done?

There is a standard called DMARC used by many large organisations including Google, Facebook, Apple, Craigslist, Virgin Media, British Airways, Dropbox, Amazon and many more.

Implementing DMARC ensures that genuine emails can only be sent using specified company servers and hence any Internet Services Provider can filter out the messages claiming to be from these companies, but are fake.

Sending Out Emails

The sender sets up two pieces of machine readable information in advance

  1. A document that describes how the emails will be sent (e.g. which servers will be used for the outgoing mail). This is called SPF (Sender Policy Framework).
  2. A proof of identity document called DKIM (Domain Keys Identified Mail)

Receiving Emails

The email service provider in receipt of the message, checks the SPF and DKIM entries for the legitimate sender and compares the meta data for the messages against that. If it passes then the message is accepted but it there is a mismatch then the messages are marked as fake. That can mean they are deleted or can mean they are delivered to the users spam folder.

It does take effort to implement DMARC as a sender but the more large companies start using DMARC the better and the more email service providers start to check incoming mail for DMARC then the less rubbish will get through.

If you know anything more about this then let me know, by email.

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The Amazon Brushing Scam

This is a strange scam as it starts with unexpected packages being delivered to you, typically from Amazon but could be from other suppliers.

The fraud starts with a the scammer creating an account on Amazon using a real stranger’s name and address. Then the scammer orders products and they are delivered to the stranger’s home address, which is a surprise for the recipient.

Q. Why would anyone do this?

It’s all about getting good reviews. The scammers use the account they’ve set up to post fake ‘verified reviews’ on Amazon (or another service) that are positive about the products the scammers want to push or may be negative about competitor’s products. The scammers may be the sellers of the products or may be paid to specifically create these fake reviews, or to damage a sellers reputation.

Investigators believe it is largely third-party sellers on Amazon that are buying their own products in order to leave a  five-star review, and using stranger’s  names and addresses to appear as independent customers.

The recipients of the products may be very surprised at goods turning up on their doorstep but they are not charged for the items in questions, so it is theft as such.

Where the problems arise for the recipients is that they may not be able to turn off the deliveries and getting the account cancelled will be difficult as only the scammers know the passwords etc.

There is also a bigger worry – how did the scammers get their details in order to create the account?

If the scammers have that information about you then they may use it to carry out more damaging forms of identity theft.

If you receive packages from businesses such as Amazon that you did not order, then do contact the supplier and change any relevant logins and passwords.

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Are Consumer Reviews Biased

Research shows that it is often the people with strong opinions who leave reviews of products they’ve bought and service they’ve received and the majority without strong opinions tend not to leave so many reviews.

So what about that silent majority?

Research at MIT suggests that some reviewers may be systematically biased or easily manipulated by the presence of previous reviewers comments. This is commonly called “social proof” where people assume the actions of others are correct and duplicate them in an attempt to reflect correct behaviour in the situation.

Imagine you dine at a restaurant and aren’t too impressed by the food. When you get home and want to post a review, you find that the restaurant has very high ratings – people love the place. You may still post a negative review but it is quite likely you will assume your not so good dish was an exception for the restaurant and will hold off on posting that negative view or at least tone it down.

When we see that other people have appreciated a certain book, enjoyed a hotel or restaurant or liked a particular event — and given them a high rating online — this can cause us to feel the same positive feelings about the book, hotel, restaurant or event and to likewise provide a similarly high online rating,

If you had a moderate view on a restaurant meal or event etc. you’re likely not to bother leaving a review, thinking it not worth the time and effort.

An academic study titled “Understanding and Overcoming Biases in Customer Reviews.” had analysis of several hundred thousand reviews from four major online retailers, and highlighted evidence of two major types of bias in the online review system:  social influence bias and selection bias.

Social Influence Bias is when a user’s opinion is influenced by the opinion of others. So, if your business has bad reviews, people who post reviews are more likely to follow suit, and post more bad reviews. If your business has good reviews, people are more likely to post good reviews.

Selection Bias (also called voluntary response) is where the people that submit reviews feel motivated to do so, which usually means that the resulting sample over-represents individuals who have strong opinions.

There is also the problem of how to interpret rating scales. For example, does 5 out of 5 stars means exceptional or does it just mean very good?

A well designed mass survey will put considerable effort towards standardizing responses, as vague and inconsistent response criteria will make an otherwise legitimate survey meaningless.

It can be difficult to get wide ranging responses from  groups of people without ignoring the silent majority but use of incentives can make it possible.

Do you have an opinion on this matter? Please comment in the box below.

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