Confusion Matrix and Cyber Security

Hello All …

Here I come with another article in that we will clear all the confusion about Confusion Matrix and let see how it is used in Cyber Crime..?

Classification Accuracy is given by the relation:


Accuracy is the number of correctly (True) predicted results out of the total.

Out of the total predicted positive values, how many were actually positivePrecision = TP / (TP + FP) = 4/5 = 0.8


Out of the total actual positive values, how many were correctly predicted as positive

Recall= TP / (TP + FN) = 4/5 = 0.8

4. F beta SCORE

In some use cases, both precision and recall are important. Also, in some use cases even though precision plays an important role or recall plays is important, we should combine both to get the most accurate result.


Cybersecurity is the protection of internet-connected systems such as hardware, software and data from cyberthreats. The practice is used by individuals and enterprises to protect against unauthorized access to data centers and other computerized systems.

  • Phishing
  • Man-in-the-middle attack
  • Denial-of-service attack
  • SQL injection
  • Zero-day exploit
  • DNS Tunneling


With an increasing number of users, devices and programs in the modern enterprise, combined with the increased deluge of data, much of which is sensitive or confidential, the importance of cybersecurity continues to grow. The growing volume and sophistication of cyber attackers and attack techniques compound the problem even further.


What is the risk?

Risk is defined as the potential for loss or damage when a threat exploits a vulnerability. Examples of risk include:

  • Loss of privacy
  • Damage to your reputation Rep
  • Legal implications
  • Even loss of life
  • Conduct scaling on the data
  • Consider the RBF kernel K(x; y)
  • Use cross-validation to 2nd the best parameter C and
  • Use the best parameter C and to train the whole training set
  • Generate formatted data.
  • All the classes are represented

Four Major Examples of Cyber Crime

In 2013–2016, Yahoo experienced a data breach which resulted in the theft of 3 billion user accounts. For some of these accounts, the attackers got hold of private information and passwords, which could be used to access user accounts in other online services. Much of this data is available today, either free or for a price, on the dark web.

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