The technology behind the internet of things is becoming even more smarter and complex. Smart device technology is progressing at a rapid rate. Companies are leveraging artificial intelligence or machine learning embedded within IoT applications to gain competitive advantages including increased operational productivity.
During the last decade, major corporations have turned their focus on acquiring smaller companies that are specialized in the convergence of artificial intelligence and IoT. Also, IoT service vendors are now offering advanced AI capabilities like machine learning-based analytics.
The Changing Face of Cybersecurity
It is crucial to understand that cybersecurity isn’t static. It is quick, volatile and constantly evolving. This makes it difficult to maintain an efficient defensive position without continually formulating and adopting new countermeasures. Security controls that worked previously might not be sufficient or capable today and the security measures taken today might be obsolete tomorrow.
Nowadays, we are tackling problems related to highly orchestrated cyber-crimes. There are two main limitations to traditional security systems. The first is that security systems tend to be incredibly rules-oriented and have been developed according to the understanding of what is considered to be a severe threat. The issue here is that cyber threats have only become stronger over time, malware can become incredibly complex and subversion techniques are constantly evolving.
The second limitation with traditional cybersecurity is the issues with scalability. Scalability issues arise due to many factors, such as:
- Organizational size and complexity: Bigger companies tend to experience greater difficulty in adapting to changing security conditions.
- Mixed-use of old and new systems and applications. Several companies continue to rely on a mix of old and new technology. This complicates any steps taken to provide a holistic approach to IoT security.
- Increased operational complexity: Conducting business today is a very complicated endeavor. IT companies are plagued with a vast array of complex responsibilities to ensure that an IoT ecosystem is functioning at optimum levels. This involves conducting frequent updates (software operating systems, applications etc.), network application updates, incorporating new assets, analyzing security threats, detecting potential targets etc.
All these aspects combined lead to IoT security becoming a very complicated proposition.
AI and Cybersecurity
Although cyberattacks are growing in terms of scale and scope, AI-based applications have been incredibly beneficial in analyzing and managing these increased risks. AI possesses the capabilities that allow companies to be a step ahead of these continually evolving cyber threats. AI provides instant feedback which enables companies to investigate and analyze several thousands of everyday alerts, making impactful decisions and react to situations much quicker.
Traditional cybersecurity methods are not effectively scalable to the speed or capability required to deal with today’s cybersecurity threats. Managing these escalating threats needs a new approach and new technologies. In the future, we can expect next-generation defenses to be powered by continued advances in AI. AI-powered IoT security solutions will be a leading contributor to creating IoT ecosystems that are more secure and reliable.