Donald Huang is the director of product marketing at Macronix International Co., Ltd., headquartered in Taiwan. In this role, he is responsible for driving product innovation, analysis and positioning to meet Macronix customers’ evolving needs, and developing go-to-market product strategies. A 25-year veteran of the high-technology industry, Donald previously served as customer quality engineering manager at Taiwan Semiconductor Manufacturing Company (TSMC) and at Nanya Technology Corp. as technology development manager. He earned his bachelor of science degree in mechanical engineering at National Yang Ming Chiao Tung University, then his Ph.D. at Tsinghua University.
Premiere: 5/15 13:20 - 13:50
Replays: 5/15 19:20 - 19:50, 5/16 01:20 - 01:50
Threats to digitally stored data have existed ever since punch cards were the primary storage medium.The difference now is that data are as much currency as mere information, and therefore a rich target for thieves.
Artificial intelligence (AI) has ushered in an age in which data are expansive, ever-evolving and increasingly at risk of manipulation, if not downright theft.
A fast-growing and logical application of AI is autonomous driving, a.k.a., driverless vehicles. “Bad actors” are hard at work attempting to steal such autonomous-driving AI data through tampering, “key cracking” of flash storage to gain authentication, and outright theft from flash storage.
However, protection strategies can ward off these threats: anti-tampering actions; blocking key cracking; and theft-protection techniques.
In this presentation, Macronix will demonstrate how developers of AI-based autonomous-driving applications can identify attack methods, then take the necessary steps to provide protection against them.
Threats to digitally stored data have existed ever since punch cards were the primary storage medium.The difference now is that data are as much currency as mere information, and therefore a rich target for thieves.
Artificial intelligence (AI) has ushered in an age in which data are expansive, ever-evolving and increasingly at risk of manipulation, if not downright theft.
A fast-growing and logical application of AI is autonomous driving, a.k.a., driverless vehicles. “Bad actors” are hard at work attempting to steal such autonomous-driving AI data through tampering, “key cracking” of flash storage to gain authentication, and outright theft from flash storage.
However, protection strategies can ward off these threats: anti-tampering actions; blocking key cracking; and theft-protection techniques.
In this presentation, Macronix will demonstrate how developers of AI-based autonomous-driving applications can identify attack methods, then take the necessary steps to provide protection against them.
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