Woman using smartphone and laptop with icon graphic Cyber security network of connected devices and personal data security from Shutterstock.com

75% of IT security teams in the Asia-Pacific region believe that their IoT devices are susceptible to infiltration, according to new global study

The inability to identify attacks targeting the internet of things (IoT) devices as a gateway was cited by IT security teams as a major loophole in their firms’ overall security blueprint, according to an announcement by the Ponemon Institute on Friday (5 Oct).
The Ponemon Institute — which carried out the global research study on behalf of Aruba, a subsidiary of Hewlett Packard Enterprise — has found that “more than three-quarters of respondents believe their IoT devices are not secure, with 75 percent stating even simple IoT devices pose a threat.”
Findings from the global study titled “Closing the IT Security Gap with Automation & AI in the Era of IoT” also revealed that “two-thirds of respondents admitted they have little to no ability to protect” their IoT devices and the information stored within those devices.
In the quest to protect data and other high-value assets, security systems incorporating machine learning and other AI-based technologies are essential for detecting and stopping attacks that target users and IoT devices. The majority of APAC respondents agree that security products with AI functionality will help to:
  • Reduce false alerts (66 percent)
  • Increase their team’s effectiveness (62 percent)
  • Provide greater investigation efficiencies (57 percent)
  • Advance their ability to more quickly discover and respond to stealthy attacks that have evaded perimeter defense systems (53 percent)
Twenty-nine percent of APAC respondents said they currently use some form of machine-learning or other AI-based security solution, with another 29 percent stating they plan on deploying these types of products within the next 12 months. Continuous monitoring of network traffic, closed-loop detection and response systems, and detecting behavioral anomalies among peer groups of IoT devices, were cited as the most effective approaches to better protect their environments.