When it comes to the enterprise technology and cybersecurity challenges modern businesses face, it’s hard to think of two areas that create more concerns for IT professionals than information protection and artificial intelligence (AI).
The risk of an outsider attack remains an ever-present danger, with year-over-year increases in cybersecurity threats. Meanwhile, the malicious use of AI to adapt to existing defensive mechanisms has also become a threat.
But while there are risks, there are also opportunities, as businesses can use the power of AI to deal with their cybersecurity challenges. AI can help companies recognize malicious patterns automatically to identify more vicious attacks. Let’s find out more.
Fears over the potential replacement of IT professionals with machines might be understandable, given the level of exposure in media, but—at least in the case of cybersecurity challenges—such concerns are probably misplaced. Rather, increased attention is being focused on AI as a new threat vector. Experts suggest businesses should be concerned that a rising number of hackers are using the power of AI to automate cyberanalytics to learn behaviors and plan more sophisticated attacks.
The Harvard Business Review acknowledges that hackers might use these analytical techniques to become more humanlike in nature, fooling and overcoming the cybersecurity defenses that enterprises build. It is not hard to visualize an AI-based arms race, with hackers, governments, and enterprises battling to overcome cybersecurity challenges.
On the flip side, what if AI is put in the hands of good people for a noble purpose of defending against cyber threats? The positive impact of AI on cybersecurity is beyond measurable that may triumph over its malicious usage. While humans play a crucial role in preventing cyberattacks, experts recognize that businesses face a significant capability gap. Fifty-one percent of organizations have a shortage of cybersecurity skills, according to research from ESG and ISSA and AI can help fill this gap.
The report suggests that smart IT leaders are turning to automation and orchestration. Rather than relying solely on their IT staff, businesses can use AI to process millions of events per second, a feat that would otherwise be impossible, given the paucity of talent, never mind the exponential growth in connections and data.
Business leaders should be wary because cybersecurity automation remains a nascent area. Deep learning provides huge potential for transformational change in data protection techniques, yet experts recognize also that it would take huge computing resources to process and learn how all business data is being used.
Smart executives will take a progressive stance. They will apply AI incrementally, using advanced technologies in stages. Rather than worrying about deep learning right from the outset, your organization should focus on AI applications and start building a smarter approach to cybersecurity.
With AI searching for errant activity automatically, your valuable professionals can focus on higher-order tasks and help you identify suspicious trends and hone in on the key targets. By matching algorithms with human ability, your organization can fill the cybersecurity skills gap and help combat external threats.
While cybersecurity used to be focused on trawling through logs to look for suspicious activity, machine learning promises a new, automated approach to data protection. In order to properly train the machine learning models for reliable predictions, organizations must be able to access, retain, and use all relevant security data.
The challenge evolves with the rise of the Internet of Things and its plethora of sensors; firms have access to more information than ever before, with analyst Gartner predicting 20.4 billion connected things will be in use by 2020. But the explosion of data and data sources doesn’t have to put the brakes on your AI efforts. Your business can draw on big data to effectively manage long-term historical data as well as data-in-motion as events are streaming in.
IT professionals must work to aggregate as many useful security data sources as possible, including security endpoint devices, machine-generated logs, intrusion detection systems (IDS), network data, and threat intelligence feeds, to help understand the broader cybersecurity picture. With more data, you can create an iterative feedback loop in which patterns are automatically identified.
Yes, automation is coming, but the rise of AI doesn’t herald the end of cybersecurity professionals. Despite the hype, your company is not about to abandon its security operations center and leave protection in the hands of a mysterious black box.
Your business still needs human expertise. The goal for your business should be to draw on the best of AI. Take a consolidated view that helps bring people and tools together. Focus on the algorithms and data that help make your staff more effective and efficient. At a time when the fear surrounding cybersecurity and automation is at an all-time high, take a deep breath and aim for a progressive approach to machine learning, where the right technologies are applied at the right level for your business.
To learn more about how cybersecurity can leverage machine learning, download this guide.