The DOD View of IP Theft

2013 ◽  
pp. 173-182
Keyword(s):  
Ip Theft

IP Theft & Corporate Espionage: Remedies

2003 ◽  
Vol 2003 (9) ◽  
pp. 9-12
Author(s):  
Steven Philippsohn ◽  
Samantha Thomas
Keyword(s):  
Ip Theft

scholarly journals Review on Logic Encryption Strategy Ensuring Key Interdependency

2018 ◽  
Vol 7 (03) ◽  
pp. 23705-23711
Author(s):  
M. Padmaa ◽  
S. Divyadarshini ◽  
M. Keerthana ◽  
T.S. Mohana Parameswari ◽  
K. Mohana Priya
Keyword(s):  
Hardware Trojans ◽  
Security Vulnerabilities ◽  
Additional Equipment ◽  
Pros And Cons ◽  
The Creation ◽  
Ip Theft

With the globalization of IC outline flow, numerous fables organizations outsource the creation of their plan to off-site foundries. As these foundries may not generally be believed, it brings about security vulnerabilities and dangers, for example, forging, IP theft, figuring out, overbuilding and Hardware Trojans. Logic encryption has developed to be a potential answer for secure the plan against these dangers. It presents some additional equipment (key-gates) into the plan to conceal the usefulness from unapproved clients, utilizing security keys. The areas of addition of key-gates decide the nature of the security gave by the subsequent plan. In this paper, we examined pros and cons of few papers and propose a productive technique to defeat the IP theft

scholarly journals DANA Universal Dataflow Analysis for Gate-Level Netlist Reverse Engineering

2020 ◽  
pp. 309-336
Author(s):  
Nils Albartus ◽  
Max Hoffmann ◽  
Sebastian Temme ◽  
Leonid Azriel ◽  
Christof Paar
Keyword(s):  
Integrated Circuits ◽  
Reverse Engineering ◽  
Dataflow Analysis ◽  
Hardware Trojans ◽  
On Chip ◽  
Perfect Recovery ◽  
High Level ◽  
And Control ◽  
Hardware Designs ◽  
Ip Theft

Reverse engineering of integrated circuits, i.e., understanding the internals of Integrated Circuits (ICs), is required for many benign and malicious applications. Examples of the former are detection of patent infringements, hardware Trojans or Intellectual Property (IP)-theft, as well as interface recovery and defect analysis, while malicious applications include IP-theft and finding insertion points for hardware Trojans. However, regardless of the application, the reverse engineer initially starts with a large unstructured netlist, forming an incomprehensible sea of gates.This work presents DANA, a generic, technology-agnostic, and fully automated dataflow analysis methodology for flattened gate-level netlists. By analyzing the flow of data between individual Flip Flops (FFs), DANA recovers high-level registers. The key idea behind DANA is to combine independent metrics based on structural and control information with a powerful automated architecture. Notably, DANA works without any thresholds, scenario-dependent parameters, or other “magic” values that the user must choose. We evaluate DANA on nine modern hardware designs, ranging from cryptographic co-processors, over CPUs, to the OpenTitan, a stateof- the-art System-on-Chip (SoC), which is maintained by the lowRISC initiative with supporting industry partners like Google and Western Digital. Our results demonstrate almost perfect recovery of registers for all case studies, regardless whether they were synthesized as FPGA or ASIC netlists. Furthermore, we explore two applications for dataflow analysis: we show that the raw output of DANA often already allows to identify crucial components and high-level architecture features and also demonstrate its applicability for detecting simple hardware Trojans.Hence, DANA can be applied universally as the first step when investigating unknown netlists and provides major guidance for human analysts by structuring and condensing the otherwise incomprehensible sea of gates. Our implementation of DANA and all synthesized netlists are available as open source on GitHub.

Preventing DNN Model IP Theft via Hardware Obfuscation

2021 ◽  
pp. 1-1
Author(s):  
Brunno F. Goldstein ◽  
Vinay C. Patil ◽  
Victor C. Ferreira ◽  
Alexandre S. Nery ◽  
Felipe M. G. Franca ◽  
...  
Keyword(s):  
Ip Theft
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