May 2017 Cyber Attacks Statistics

It’s time to publish the statistics derived from the cyber attacks timelines of May (Part I and Part II).

As usual, the first chart is the Daily Trend of Attacks: after an initial peak the trend seems quite stable with two spikes in the last two weeks.

Cyber Crime leads the Motivations chart, with 76.1% essentially stable (was 74.1% in April). Cyber Espionage is equally stable to 20.9% (was 21.2% in April). Cyberwarfare grows from 1.2% to 3%, whereas in May I haven’t recorded any Hacktivism event.

And guess what? Account Hijackings and Malware events rank on top of the Attack Vectors with 19.4% (were respectively 21.2% and 24.7% in May). Targeted attacks drop to 14.9% from 23.5%.

The Distribution of Targets Chart is led by Industries (26.9% vs 23.5%) ahead of Single Individuals, just line in April (16.4% vs 20%), Education (14.9% vs. 10.6%) and Governments (7.5% vs 10.6%).

The Industry Drill Down Chart is led by Retail (16.7%).

As always, bear in mind that the sample refers exclusively to the attacks included in my timelines, aiming to provide an high level overview of the “cyber landscape”.

If you want to have an idea of how fragile our data are inside the cyberspace, have a look at the timelines of the main Cyber Attacks in 2011, 2012, 2013, 2014, 2015 and 2016 (regularly updated). You may also want to have a look at the Cyber Attack Statistics.

Of course follow @paulsparrows on Twitter for the latest updates, and feel free to submit remarkable incidents that in your opinion deserve to be included in the timelines (and charts).

 

2 thoughts on “May 2017 Cyber Attacks Statistics

  • July 14, 2017 at 10:06 am
    Permalink

    Dear Paolo, In your posts you mention references to the source data being provided at the end of your slides. I am wanting to understand, in this world of ‘false news’, whether your information is credible, or perhaps to understand how the data is aggregated to assess it’s credibility. Can you help me with this? Is there an outline of the process you use for data aggregation or data sourcing that would help understand the credibility of your posts? Thank you in advance.

    Reply
    • July 14, 2017 at 10:08 am
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      Look at the timelines and click on the link. There is the source.

      Reply

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