Onward Security, a leader in IoT cybersecurity assessment solutions, announced that it has stood out from more than 500 entries and won 6 gold and 1 silver awards in the Cybersecurity Excellence Awards 2020. The company was granted the Gold Award for the Best Cybersecurity Company in Asia, while its automatic vulnerability assessment device (SecDevice) won 3 gold awards for Embedded Security, ICS / SCADA Security, and Internet of Things Security; and its product security management system (SecFlow) won 2 gold awards for Vulnerability Management and Incident Response, and 1 silver award for Risk Management.
Global Market Insights estimated the size of the cybersecurity market will reach USD300 billion by 2024, due to increasing cyber attacks and unprotected IoT devices. Morgan Hong, GM of Onward Security, said, "The speed of time to market for connected products is now accelerating, but the quality of cybersecurity is often ignored. With the increasing demand for teleworking, using products with cybersecurity vulnerabilities will expose customers to losses caused by cyber attacks, brand and business damages, and even lengthy legal proceedings. IoT device manufacturers should introduce the Secure Software Development Life Cycle (SSDLC) immediately to meet the cybersecurity requirements of governments, cybersecurity standards and buyers."
In this competition, Onward Security displayed the AI features of the products. With the core technology of machine learning, SecFlow and SecDevice can assist the secure software development and product security test more accurately and effectively. The AI-based SecFlow can speed up the processing of SSDLC, using intelligent security incident and vulnerability information collection to compile and optimize the most valuable product security database for the customers, and find out the affected products and related software through proactive security risk analysis and correlation so as to help customers rapidly take appropriate response actions. AI also enables SecDevice to greatly improve the speed and quality of IoT product vulnerability detection. Besides reducing the time for manual setting and intervention, it can also provide security tests for customized protocols using the AI-based fuzzing technology, thereby effectively reducing the cybersecurity risks of connected products caused by network open access and teleworking.
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