By Stefan Beissel
This e-book deals readers crucial orientation on cybersecurity safeguards, and primary and most well known is helping them locate the suitable stability among monetary expenses and hazard mitigation. this is often completed through pursuing a multi-disciplinary procedure that mixes well-founded tools from economics and the pc sciences. proven choice making ideas are embedded right into a walk-through for the full lifecycle of cybersecurity investments. Insights into the industrial point of the prices and advantages of cybersecurity are supplemented via proven and cutting edge monetary symptoms. Readers will locate sensible instruments and methods to help moderate choice making in cybersecurity investments. extra, they are going to be outfitted to motivate a standard figuring out utilizing financial features, and to supply fee transparency for the senior management.
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Extra info for Cybersecurity Investments: Decision Support Under Economic Aspects
Prior to a cybersecurity investment project, there is sometimes uncertainty about the stakeholders, their relationship and their influence. A technique that helps to make this information transparent is the stakeholder analysis. It facilitates to distinguish cooperating from competing stakeholders. A targeted addressing of stakeholder interests can stimulate cooperation and prevent resistance. Thereby, key stakeholders can be convinced and—in the best case—encouraged to support the project at senior management level.
In contrast, it would be inefﬁcient to protect all data in the same way. The overall protection level would be either too low or too high. In the ﬁrst situation, highly sensitive data would be not protected sufﬁciently. In the second situation, the costs and the complexity of operating processes would be far higher than necessary. The data classiﬁcation is implemented by assigning all data to appropriate classes. Common data classes are: • Public: This is the class with the lowest protection level.
G. a new consecutive number. In the multiple usage, always the same token is created for the same data. This usage facilitates cumulative evaluations. The type of usage must be taken into account when choosing the generation technique: Encryption and hashing techniques automatically create the same token for the same data. If numbers are generated as tokens, an additional procedure should be integrated in order to reuse the same token for the same data value. The above-mentioned generation techniques are characterized as follows: • If encryption technologies are used when generating tokens, the sensitive data will be encrypted and the resulting cipher text is used as a token.
Cybersecurity Investments: Decision Support Under Economic Aspects by Stefan Beissel