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Incorporating a Prevention Mindset into Threat Detection and ResponseThreat detection and response systems, by definition, are reactive because they have to wait for damage to be done before finding the attack. With a prevention-mindset, security teams can proactively anticipate the attacker's next move, rather than reacting to specific threats or trying to detect the latest techniques in real-time.
The report covers areas enterprises should focus on:
What positive response looks like.
Improving security hygiene.
Combining preventive actions with red team efforts.
Incident Readiness and Building Response Playbook
In this special report, learn the Xs and Os of any good security incident readiness and response playbook.
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User Rank: Apprentice
5/19/2015 | 1:36:42 PM
Google cannot protect privacy by definition: as the source of statistics (for gained from texts phrases) Google uses popularity, how popular are the phrases among people that typed the same search queries/ search for the same. Google cannot exist without spying.
However, there is structured data that can search for people - not people for information, but information for people. I discovered and patented how to structure any data: Language has its own Internal parsing, indexing and statistics. For instance, there are two sentences:
a) 'Sam!'
b) 'A loud ringing of one of the bells was followed by the appearance of a
smart chambermaid in the upper sleeping gallery, who, after tapping at
one of the doors, and receiving a request from within, called over the
balustrades -'Sam!'.'
Evidently, that the 'Sam' has different importance into both sentences, in regard to extra information in both. This distinction is reflected as the phrases, which contain 'Sam', weights: the first has 1, the second – 0.08; the greater weight signifies stronger emotional 'acuteness'.
First you need to parse obtaining phrases from clauses, restoring omitted words, for sentences and paragraphs.
Next, you calculate Internal statistics, weights; where the weight refers to the frequency that a phrase occurs in relation to other phrases.
After that data is indexed by common dictionary, like Webster, and annotated by subtexts.
This is a small sample of the structured data:
this - signify - <> : 333333
both - are - once : 333333
confusion - signify - <> : 333321
speaking - done - once : 333112
speaking - was - both : 333109
place - is - in : 250000
To see the validity of technology - pick up any sentence.
Do you have a pencil?
My technology came from Analytic Philosophy, Internal Relations Theory.