PUF is a Hardware Solution for the Sunburst Hack
By Albert Jeng, PUFSecurity
EETimes (January 25, 2021)
On December 14, 2020, SolarWinds, which provides network monitoring software to the US government and private businesses, reported one of the largest cyberattacks in history, breaching the data of as many as 18,000 organizations and companies. The so-called ‘Sunburst’ attack by a still unknown group probably backed by a foreign government began in March 2020 and penetrated US intelligence and defense organizations as well as companies such as Microsoft and Cisco Systems.
Because Sunburst went undetected for so many months, cybersecurity experts are still assessing the impact and whether the attack has been fully contained. Former US Homeland Security Advisor Thomas P. Bossert warned that evicting the attackers from US networks may take years, allowing them to continue to monitor, destroy, or tamper with data in the meantime. While few have attempted to evaluate the cost of recovery, it’s certain to be in the billions of dollars. US Senator Richard Durbin described the attack as a declaration of war.
To read the full article, click here
Related Semiconductor IP
- Process/Voltage/Temperature Sensor with Self-calibration (Supply voltage 1.2V) - TSMC 3nm N3P
- USB 20Gbps Device Controller
- SM4 Cipher Engine
- Ultra-High-Speed Time-Interleaved 7-bit 64GSPS ADC on 3nm
- Fault Tolerant DDR2/DDR3/DDR4 Memory controller
Related White Papers
- PUF: A Crucial Technology for AI and IoT
- SRAM PUF is Increasingly Vulnerable
- Understanding Physical Unclonable Function (PUF)
- NeoPUF, A Reliable and Non-traceable Quantum Tunneling PUF
Latest White Papers
- Fault Injection in On-Chip Interconnects: A Comparative Study of Wishbone, AXI-Lite, and AXI
- eFPGA – Hidden Engine of Tomorrow’s High-Frequency Trading Systems
- aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on RawAudio
- Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference
- Hardware Acceleration of Kolmogorov-Arnold Network (KAN) in Large-Scale Systems