Online Scams to Increase More in the approaching Times | CIO Applications Magazine

The number of online scams and money lost has increased significantly over the past year, states Scamadviser.com, on the basis of an analysis of scam data from 31 countries, covering 60 percent of the world population and 85 percent of global GDP.

Almost all countries researched report a growth in the number of money lost and scams. Only Sweden (-6 percent) and Italy (-9 percent) reported a reduction in the number of scams in 2019. Because of the coronavirus epidemic, an increase of 40 percent for 2020 can be expected as a growing number of consumers move to online shopping.

Several countries have admitted that online fraud is becoming the most reported crime. Singapore reported that scams took up 27 percent of overall crime in 2019, up from 19 percent in 2018. Similarly, fraud is the most experienced crime in the UK and the US. Russia reported that cybercrime’s share as part of all crimes might increase from 14 percent in 2019 to 30 percent in 2023.

Depending on the analysis of the 30+ countries, 140 million scams were reported. Extended to the global population, 3 percent of the global population was scammed in various ways. As per previous research by Scamadviser, anybody can be scammed. Astonishingly, high-income and higher educated consumers to get scammed more as they spend money more online and take more risks. The total amount of money lost was € 36 billion in 2019.

How to Use Machine Learning Against Email Phishing:

Phishing is one of the most fraudulent attacks which is found in malicious email traffic where a recipient will receive an email in the form of a message from a distinguished company that will require them to follow a link and login to a service or enter card details on a fake web page.

However, as phishing techniques develop, detection methods are also advancing quickly. Attackers will confront as long as their attempts are profitable. As such, phishing protection mechanisms need to work to minimize the response time to new scam strategies to make attacks unprofitable.

Manually-created dictionaries were used to identify phishing in email traffic about ten years ago, describing all of the possible variants that phishing texts may include. Heuristics were then introduced among the detection technologies. Heuristics search for signs that identify the nature of the message and how it might be dangerous.

Analyzing email headers is another method of detection. A header includes information about the email, its sender, and route to the recipient, such as data of creation, ID number, encoding type, mailing address, and IP address, which is visible in a message’s properties. Examining the headers help cybersecurity specialists detect suspicious senders.

A single phishing indicator does not help identify and be sure if the message is malicious or not. Instead, specialists look for sets of indicators that are combined into signatures that can uniquely detect if a message is malicious.

Today, an increasing number of attacks are being carried out by masking their malicious messages as emails from new online services, taking advantage of popular events. To safeguard users from such attacks, the need for technology that can quickly identify new types of phishing emails through automation is required. This technology utilizes statistics and machine learning, allowing automatic extraction of the necessary information to identify and prevent phishing and train and retrain itself as required.

Check This Out :

I am a technology blogger, who loves to read and write on the latest in technology.