As any business grows, data sharing increases in both volume and frequency. Every one of these digital relationships presents an expanding set of cyber risks. Cyber security has become a major priority for every organisation. The right controls and procedures must be put in place to detect potential attacks and protect against them. However, with the ever increasing risk of a cyber-attack businesses are finding it increasingly difficult to keep up with the rapidly evolving cyber threats?
Budget available for deployment of “Defence in depth” is being stretched to the limits and thus Security professionals are expected to spend more on tools that use AI and machine learning, which would help with the extra workload caused by the increasing risk of an attack, and improve defences.
Malware is often transferred to ICT Systems within encrypted web traffic, and sensitive data sent through Cloud systems. This suggest that the most effective way to manage the concomitant exposures is to deploy the relevant tools which encompass deep learning capability and embedded artificial intelligence to timeously and effectively monitor, detect and prevent the use of encryption for masking malicious activity.
It is often suggested that, over time, artificial intelligence will be able to learn how to automatically detect unusual patterns in encrypted web traffic and the Internet of things (IoT) environments. Neural Networks facilitating artificial intelligence will soon be available for deployment in the struggle to substantially improve network security defences. Businesses, Governments and other organisations have not been able to find staff with the necessary skills required for effective control of network and computer security. The deployment of automated system controls which rely on artificial intelligence and machine learning tools will certainly reduce the demand for skilled network security professional staff / administrators to help overcome these substantial skill gaps.
It is a well-established fact, that Chief Information Security Officers (CISOs), are eager to deploy and use artificial intelligence and machine learning tools, to enhance the effectiveness of that their security infrastructure which is rapidly growing in “sophistication and intelligence”. Artificial intelligence does however potentially provide a significant number of false positives, which can increase the workload. With time and as the tools gain more experience, the rate at which these false positives are generated and the overall count of the false positives will substantially decrease.
An analysis of the rate at which cyber threats are increasing coupled with the complexity of cyber threats and attacks it is clearly confirmed that without the implementation of automated “defence in depth”, controls which rely on sophisticated algorithms which support machine learning in cyber security, businesses and governments will be unable to detect and protect against malicious cyber-attacks, within the constraints of security budgets.
Although artificial intelligence, is rapidly developing, organisations are far from safe and resilience remains somewhat compromised. According to Gartner, “Organizations and businesses will be forced to pay particular attention to artificial intelligence based solutions that include managed services like artificial intelligence based threat hunting or file classification.” Without such intelligence, the rate of business failure due to defective defence will drastically increase to the extent that sustainability will be severely compromised.
Resilience as a managed service allows our clients to focus maximum attention and resources on the most critical aspects of cyber security using Artificial Intelligence and deep learning algorithms to support BDO’s specialist capabilities.
It also allows clients to benefit from a level of resilience and defense that they would struggle to achieve alone.
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