10 Predictions how AI will Improve Cybersecurity in 2020

AI and machine learning advances are driving technological advances to a greater level. Real-time data and analytics enable stronger business cases to be built, leading to higher adoption. Expenditure on cybersecurity has rarely been linked to increased revenue or cost reduction, but this is about to change in 2020.

• AI systems will continue to improve the drawing of wildly different types of data sets, enabling the "bigger picture" to be gathered from, say, static configuration data, historical local logs, global threat landscapes, and current event streams. Enterprise executives will concentrate their budgets and resources on detecting cyber threats using AI over predicting and reacting. As businesses grow in their use and implementation of AI as part of their strategies for cybersecurity, prediction and response will increase accordingly.
• Artificial Intelligence and machine learning will continue to enable advancements in asset management that will also drive exponential IT security gains by providing improved endpoint resilience in 2020. It is observed that "Keeping computers up-to-date is an IT management job, but it is a security result. And knowing what's going on, what processes are going on, and what network bandwidth consumption is an IT management issue, but it's a security outcome. I don't see these as distinct behaviors to the degree that I see them as multiple facets of the same problem space, accelerating in 2020 as more businesses choose greater resilience to safe endpoints.
• By 2020, there will be a greater need for adversarial machine learning to fight corruption in the supply chain. It is predicted that "the need for adverse machine learning to counter corruption in the supply chain will increase by 2020. Also, it is predicted that determining who has access to what data is the big problem with remote coworking spaces. As a result, AI will become more prevalent in traditional business processes and will be used to identify a corrupted supply chain.
• Threat actors will expand the use of AI to analyze mechanisms of defense and model behavioral patterns to bypass security controls, using analytics and machine learning to hack into organizations. Protection mechanisms of organizations and target threats to different areas of weakness should be well protected. There is also the threat that bad actors can plug in organizations ' data streams and use the data to orchestrate further sophisticated attacks.

• Bringing artificial intelligence into account will become more prevalent— both its development and its mitigation. Josh Johnston, Kount's AI Manager, predicts that "the average consumer will know that passwords do not provide adequate account security and that they are vulnerable to any account. Neither will Captcha be accurate, because while it can say if someone is a bot, it can't be consistent. AI will identify a consumer who returns. AI will be critical to protecting the customer's entire journey from account formation to account development to the payment transactions. And, AI will allow businesses to create a partnership that is secured by more than just a password with their account holders
• Because of the severe shortage of qualified security operations personnel and the sheer volume of data that most organizations are trying to work through, companies are likely to seek AI / ML technologies to simplify their security operations processes. Craig Sanderson, Infoblox's Vice President of Security Products also predicts that' Increasingly, AI and machine learning will be used to identify new threats that still leave organizations with the challenge of knowing the nature, magnitude, and veracity of that threat to provide an effective response.
• In 2020, consumers will take more responsibility for their data sharing and privacy. Brian Foster, MobileIron's Senior Vice President Product Management, states that we have seen some of the largest violations of privacy and data over the past few years. As a result of the backlash, tech giants like Apple, Google, Facebook, and Amazon have strengthened their privacy controls to regain customer trust. The tables have now turned on consumers and businesses will have to put privacy first in order to stay in business. Customers will continue to own their data, which means they will be able to share it freely with third parties, but most significantly, they will get their data back after sharing, unlike in previous years.
• AI and machine learning can prevent compromised equipment from reaching the supply chains of organizations. Increasing demand for electronic components will expand the market for falsified components and cloned products, increasing the risk of compromised hardware entering the supply chains of organizations. The avenues for supply chain attacks on hardware are growing as market demand for more and cheaper chips, and components are driving a booming business for counterfeiters and cloners of hardware. The growth is likely to create more incentives for national-state and cyber-crime threat actors to compromise.

• As cyber threats rise, we're going to fight AI with AI. Brian Foster, Senior Vice President Product Management at MobileIron, states that highly professional criminal networks use AI and ML to exploit weaknesses such as user behavior or security holes to access valuable business systems and data. All this makes keeping up with these threats extremely difficult for IT protection organizations— much less staying ahead of them. While an intruder only has to find one open door in the security of an undertaking, the undertaking has to run to lock all the doors. AI performs this at a rate, which human capacity is no longer able to compete with completely, and companies will eventually recognize it in 2020.
• Capgemini estimates that 63 percent of organizations intend to implement AI to enhance cybersecurity by 2020, with network security being the most common application. Capgemini found that before 2019, almost one out of five companies used AI to enhance cybersecurity. In addition to network security, data security, endpoint security, identity, and access management are today's top priority use cases to strengthen cybersecurity with AI in businesses.