Security Risk management
Risk management is the identification, assessment and prioritisation of risks followed by coordinated and economical application of resources to minimise, monitor, and control the probability and/or impact of unforeseen events.
Security risk management is the specific culture, processes and structures that are directed towards maximising the benefits of security in support of business objectives.
Adopting a risk based approach allows agencies to prioritise activities based on the likelihood and consequence of a risk being realised, to maximise business outcomes while minimising the occurrence or effects of events that may negatively affect outcomes.
Non-corporate Commonwealth entities (agencies) need to develop a security risk management process to identify:
- specific risks to their people, information and assets
- the agency’s level of risk tolerance
- appropriate protections to reduce or remove risks
- untreatable residual risks (such as doing business on the internet) and accept responsibility for the risk.
When companies started to talk about cybersecurity, they spoke in terms of potential dangers that essentially affected the integrity of their business’s IT systems.
Directors are more and more concerned
Corporate cybersecurity is no longer just a headache for heads of cybersecurity departments: it’s also a major concern for the company directors themselves. This was made quite clear with the cyberattacks on Equifax, or with the arrival of WannaCry.
And the future prospects speak for themselves: although companies are worried about maintaining their cybersecurity, the figures show that cyberattacks aren’t going to go away. Quite the opposite: they’re going to be an ever more present threat in the day-to-day of large companies.
This has led to an increase in corporate awareness of the matter, and directors of these large companies are more and more concerned about the integrity of their IT systems, since the short and medium term continuity of their companies, and even the future of their existence, could be called into question.
The Facebook and Cambridge Analytica scandal has brought to the fore something that is getting harder and harder to refute: not only must action be taken against companies that make fraudulent use of user data, but the measures that are taken must be stricter, and the sanctions larger. What’s more, as well as implementing harsher economic fines, these measures also need to regulate the protective actions that companies take.
In this vein, 2018 has been defined by the definitive implementation of the GDPR, which defines the steps that companies must take in order to ensure the protection of personal data. It also significantly increases the financial risks that companies will face if this personal data is compromised in any way.
Machine learning to boost security
Unfortunately, cybersecurity risks become obsolete every so often. If a company thinks that it is prepared to face up to the latest cyberattack methods that have been observed in the market, it can’t afford to be complacent: these techniques grow day by day, and their action protocol can change. This means that we’re facing a constantly shifting risk management scenario.
This is where machine learning comes into play. This kind of technology is more agile and adaptive, and is capable of learning in real time, detecting new security breaches, evaluating new attack methods and combining all of this knowledge to adapt and improve its cybersecurity processes in the least time possible.
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