Hardware security: side-channel attacks and hardware Trojans

2018 ◽  
pp. 191-214
Keyword(s):  
Hardware Security ◽  
Side Channel ◽  
Side Channel Attacks ◽  
Hardware Trojans

Hardware Primitives-Based Security Protocols for the Internet of Things

2019 ◽  
pp. 117-141 ◽  
Author(s):  
Muhammad Naveed Aman ◽  
Kee Chaing Chua ◽  
Biplab Sikdar
Keyword(s):  
Low Cost ◽  
Security Analysis ◽  
Security Protocols ◽  
Hardware Security ◽  
Side Channel ◽  
Data Provenance ◽  
Side Channel Attacks ◽  
Sensitive Data ◽  
Physically Unclonable Functions ◽  
Iot Devices

IoT is the enabling technology for a variety of new exciting services in a wide range of application areas including environmental monitoring, healthcare systems, energy management, transportation, and home and commercial automation. However, the low-cost and straightforward nature of IoT devices producing vast amounts of sensitive data raises many security concerns. Among the cyber threats, hardware-level threats are especially crucial for IoT systems. In particular, IoT devices are not physically protected and can easily be captured by an adversary to launch physical and side-channel attacks. This chapter introduces security protocols for IoT devices based on hardware security primitives called physically unclonable functions (PUFs). The protocols are discussed for the following major security principles: authentication and confidentiality, data provenance, and anonymity. The security analysis shows that security protocols based on hardware security primitives are not only secure against network-level threats but are also resilient against physical and side-channel attacks.

Countermeasure for Cryptographic Chips to Resist Side-Channel Attacks

2009 ◽  
Vol 19 (11) ◽  
pp. 2990-2998 ◽  
Author(s):  
Tao ZHANG ◽  
Ming-Yu FAN
Keyword(s):  
Side Channel ◽  
Side Channel Attacks

scholarly journals ThermalAttackNet: Are CNNs Making It Easy to Perform Temperature Side-Channel Attack in Mobile Edge Devices?

2021 ◽  
Vol 13 (6) ◽  
pp. 146
Author(s):  
Somdip Dey ◽  
Amit Kumar Singh ◽  
Klaus McDonald-Maier
Keyword(s):  
Information Flow ◽  
Heat Dissipation ◽  
Side Channel ◽  
Side Channel Attack ◽  
Side Channel Attacks ◽  
Information Flow Control ◽  
On Chip ◽  
Temperature Side ◽  
Over Time ◽  
Memory Efficient

Side-channel attacks remain a challenge to information flow control and security in mobile edge devices till this date. One such important security flaw could be exploited through temperature side-channel attacks, where heat dissipation and propagation from the processing cores are observed over time in order to deduce security flaws. In this paper, we study how computer vision-based convolutional neural networks (CNNs) could be used to exploit temperature (thermal) side-channel attack on different Linux governors in mobile edge device utilizing multi-processor system-on-chip (MPSoC). We also designed a power- and memory-efficient CNN model that is capable of performing thermal side-channel attack on the MPSoC and can be used by industry practitioners and academics as a benchmark to design methodologies to secure against such an attack in MPSoC.

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