PFP Cybersecurity, a leader in embedded cybersecurity for IoT devices, will present “IoT Security – Power Analysis and AI” at the ST Developers Conference in Santa Clara, California, September 6, 2017. PFP’s CEO Steven Chen joins other cyber security thought leaders to present an interesting and unique approach to today’s problems at 11:45 am – 12:25 pm in the Mission City Ballroom.

According to Steven Chen, “PFP Cybersecurity’s unique approach for embedded integrity assessment utilizes side channel information, such as instantaneous power consumption to derive information about the internal execution status of the user’s ST Micro processor.”

Steven’s presentation showcases a security solution based on power analysis and Artificial Intelligence (AI) called Power Fingerprinting (PFP). Current hardware security features focus on protecting chip integrity. PFP protects the applications running on the chip. Power analysis has been used to steal cryptographic keys; PFP, however, uses it for detection, leveraging AI for scalability. Current MSSP security tools do not identify that a device has been hijacked. PFP can detect intrusions in machine time, enabling remediation within milliseconds, likely before damage can be done. Steven will look at how PFP technology works, its history, strengths and weaknesses, and its application on real IoT designs, as well as potential chip-level implementations to further reduce cost.

PFP Cybersecurity will also showcase its PowerIQ – Power Analytics through AI, which provides IoT security using machine learning to ferret out known good behavior. PFP’s embedded solution is effective for detecting both hardware and software threats and for detecting zero-day attacks on day zero, including malware, kernel rootkits, hardware Trojans and counterfeits. The PFP approach is independent of hardware, operating systems, applications, and context. While others attempt to “recognize” the attack signature, PFP detects minute changes in the electronic power profile to instantly detect and alert that an IoT device has changed its behavior.