{"id":11528,"date":"2023-09-07T07:33:40","date_gmt":"2023-09-07T07:33:40","guid":{"rendered":"http:\/\/intelliworx.wpenginepowered.com\/au\/?p=11528"},"modified":"2025-04-07T03:23:08","modified_gmt":"2025-04-07T03:23:08","slug":"emerging-trends-in-cybersecurity-consulting-what-you-need-to-know","status":"publish","type":"post","link":"https:\/\/intelliworx.co\/au\/blog\/emerging-trends-in-cybersecurity-consulting-what-you-need-to-know\/","title":{"rendered":"Emerging Trends in Cybersecurity Consulting: What You Need to Know"},"content":{"rendered":"\t\t
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The world is in constant flux, evident in the rapid shifts of new social media trends, financial market fluctuations, and technological advancements. The rise of IoT, interconnected devices, and the digital revolution has made life easier and more convenient for businesses, individuals, and corporations. More and more companies are embracing remote work arrangements, supporting the BYOD culture in their mobile workforces, and tapping into the gig economy.<\/p>

With cloud computing and the digital revolution sweeping the globe, these have also expanded the volume of cybercrime. Cybercriminals are constantly developing new and sophisticated techniques to exploit security vulnerabilities, with the latest cyber attacks becoming more aggressive, relentless, and expensive.<\/p>

As news of data breach, ransomware and hacks become the norm, staying attuned to the current trends in cyber security is crucial. Organisations can respond accordingly by adopting a stronger focus on prevention rather than merely detection to stay ahead of cybercriminals. In this article, we’ll be highlighting the top eight emerging trends in cyber security consulting so you can understand how they will impact your enterprise strategies in 2023 and beyond.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Hybrid Cloud and Multi-Cloud Security<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tA hybrid cloud environment combines public and private clouds to allow data segmentation and tailored usage, such as storing sensitive data on private servers and utilising public clouds for less sensitive tasks. Multi-cloud environment, on the other hand, involves using multiple public cloud services within a system, offering flexibility and resource segmentation. Despite being two distinct architectures, the fact remains: cloud security is a major concern for enterprises. Enterprises have moved their operations to the cloud for a number of excellent reasons such as industry competitiveness, growth acceleration, and cost optimisation<\/a>.\n\nHowever, in recent years, the trend has been to adopt a hybrid cloud or multi-cloud approach which aims to maintain critical workloads within the enterprise boundary while using service features from different cloud providers that best meet business requirements. Such architectural changes and migrations require hiring the right talent and engaging skilled cybersecurity professionals to put the right security defences and data protection mechanisms in place throughout the process. This is because each cloud adds to the attack surface exponentially, and each provider has its own data storage processes that can pose compliance risks.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Machine Learning<\/strong><\/h2>

Artificial intelligence (AI) is the ability of a computer or machine to learn and perform tasks that would normally require human intelligence. Machine learning (ML) is a subfield of AI that gives computers the ability to learn without being explicitly programmed. ML algorithms are trained on data, and then they can be used to make predictions or decisions without being explicitly told how to do so.<\/p>

In the early days of machine learning, there were concerns that the models would not be as accurate as human security researchers. However, machine learning models can be trained on massive amounts of data to achieve high levels of accuracy. Additionally, machine learning models can be used to detect unknown attacks that are difficult for humans to identify. Machine learning is a powerful tool for cyber security by using it to identify and profile devices, detect anomalies and zero-day attacks, and sort through complicated situations and scenarios at scale, which is essential in today’s dynamic threat landscape.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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IoT Vulnerability<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tIoT vulnerability is a weakness in an IoT device or system that can be exploited by attackers to gain unauthorised access to sensitive data or information. This can include credit card numbers, passwords, or other personal information.\n\nDid you know?<\/strong>\n