Power analysis-based Hardware Trojan detection

Outsourcing of chip product chain makes hardware vulnerable to being attacked. For example, an attacker who has access to hardware fabrication process can alter the genuine hardware with the insertion of concealed hardware elements (Hardware Trojan). Therefore, microelectronic circuit Hardware Trojan detection becomes a key step of chip production. A power analysis-based power-analysis microelectronic circuit Hardware Trojan detection methodology is proposed in this paper. The detection method is implemented in 90nm CMOS process. Based on simulation results, our proposed technique can detect Hardware Trojans with areas that are 0.013% of the host-circuitry.

[1]  Dimitrios I. Gerogiorgis,et al.  Modeling and optimization of polygeneration energy systems , 2007 .

[2]  Mahmoud M. El-Halwagi,et al.  Fuzzy mathematical programming approach in the optimal design of an algal bioenergy park , 2015 .

[3]  Liuchen Chang,et al.  Operation and configuration optimization of a CCHP system for general building load , 2016, 2016 IEEE 8th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia).

[4]  Jiang-Jiang Wang,et al.  Economic analysis and optimization design of a solar combined cooling heating and power system in different operation strategies , 2012, 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA).

[5]  Efstratios N. Pistikopoulos,et al.  A Multi-Objective Optimization Approach to Polygeneration Energy Systems Design , 2010 .

[6]  Zacharias B. Maroulis,et al.  Design of a combined heating, cooling and power system: Sizing, operation strategy selection and parametric analysis , 2010 .

[7]  Zeng Ming,et al.  Economy Benefit Comparison of CCHP System and Conventional Separate Supply System , 2015, 2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA).

[8]  Andrew G. Alleyne,et al.  Modeling and optimization of a combined cooling, heating and power plant system , 2012, 2012 American Control Conference (ACC).

[9]  Denny K. S. Ng,et al.  Fuzzy mixed-integer linear programming model for optimizing a multi-functional bioenergy system with biochar production for negative carbon emissions , 2014, Clean Technologies and Environmental Policy.

[10]  Minlin Yang,et al.  Research, development and the prospect of combined cooling, heating, and power systems , 2010 .

[11]  Yier Jin,et al.  Privacy and Security in Internet of Things and Wearable Devices , 2015, IEEE Transactions on Multi-Scale Computing Systems.

[12]  Tim Güneysu,et al.  Trojan Side-Channels: Lightweight Hardware Trojans through Side-Channel Engineering , 2009, CHES.

[13]  Changwen Zheng,et al.  A novel thermal storage strategy for CCHP system based on energy demands and state of storage tank , 2017 .

[14]  Miodrag Potkonjak,et al.  CAD-based Security, Cryptography, and Digital Rights Management , 2007, 2007 44th ACM/IEEE Design Automation Conference.

[15]  Yang Shi,et al.  Combined cooling, heating and power systems: A survey , 2014 .

[16]  Xueqian Fu,et al.  Optimal allocation and adaptive VAR control of PV-DG in distribution networks , 2015 .

[17]  Y Zhao Application of the distributed energy system in a data center in Beijing , 2015 .

[18]  Muhammad Waseem,et al.  A Critical Analysis on the Security Concerns of Internet of Things (IoT) , 2015 .

[19]  H. Zimmermann Fuzzy programming and linear programming with several objective functions , 1978 .

[20]  Vladimir Mahalec,et al.  Optimal design, operation and analytical criteria for determining optimal operating modes of a CCHP with fired HRSG, boiler, electric chiller and absorption chiller , 2017 .

[21]  James Tschanz,et al.  Parameter variations and impact on circuits and microarchitecture , 2003, Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451).

[22]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[23]  F. Spellman Water & Wastewater Infrastructure: Energy Efficiency and Sustainability , 2013 .

[24]  Meng Liu,et al.  Proposal and assessment of a new CCHP system integrating gas turbine and heat-driven cooling/power cogeneration , 2017 .

[25]  Luis M. Serra,et al.  Operational strategy and marginal costs in simple trigeneration systems , 2009 .

[26]  S. Halgamuge,et al.  A review on optimization strategies of combined cooling heating and power generation , 2012, 2012 IEEE 6th International Conference on Information and Automation for Sustainability.

[27]  Mahmoud M. El-Halwagi,et al.  Fuzzy mixed integer non-linear programming model for the design of an algae-based eco-industrial park with prospective selection of support tenants under product price variability , 2016 .

[28]  Hongwei Luo,et al.  Design of hardware trojan horse based on counter , 2011, 2011 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering.

[29]  Ramesh Karri,et al.  A Primer on Hardware Security: Models, Methods, and Metrics , 2014, Proceedings of the IEEE.

[30]  Geir M. Køien,et al.  Reflections on Trust in Devices: An Informal Survey of Human Trust in an Internet-of-Things Context , 2011, Wirel. Pers. Commun..

[31]  Pouria Ahmadi,et al.  Evaluation and sizing of a CCHP system for a commercial and office buildings , 2016 .

[32]  Efstratios N. Pistikopoulos,et al.  A mixed-integer optimization approach for polygeneration energy systems design , 2009, Comput. Chem. Eng..

[33]  Luis M. Serra,et al.  Polygeneration and efficient use of natural resources , 2009 .

[34]  Nelson Fumo,et al.  Benefits of thermal energy storage option combined with CHP system for different commercial building types , 2013 .