scholarly journals Think Smart, Play Dumb: Analyzing Deception in Hardware Trojan Detection Using Game Theory

2020 ◽  
Author(s):  
Tapadhir Das
Keyword(s):  
Integrated Circuits ◽  
Repeated Game ◽  
Third Party ◽  
Hardware Trojan ◽  
Hardware Trojans ◽  
Learning Stage ◽  
Hardware Trojan Detection ◽  
Trojan Detection ◽  
Utility Gain ◽  
Game Theoretic

In recent years, integrated circuits (ICs) have become<br>significant for various industries and their security has<br>been given greater priority, specifically in the supply chain.<br>Budgetary constraints have compelled IC designers to offshore manufacturing to third-party companies. When the designer gets the manufactured ICs back, it is imperative to test for potential threats like hardware trojans (HT). In this paper, a novel multilevel game-theoretic framework is introduced to analyze the interactions between a malicious IC manufacturer and the tester. In particular, the game is formulated as a non-cooperative, zerosum, repeated game using prospect theory (PT) that captures different players’ rationalities under uncertainty. The repeated game is separated into a learning stage, in which the defender<br><div>learns about the attacker’s tendencies, and an actual game stage, where this learning is used. Experiments show great incentive for the attacker to deceive the defender about their actual rationality by “playing dumb” in the learning stage (deception). This scenario is captured using hypergame theory to model the attacker’s view of the game. The optimal deception rationality of the attacker is analytically derived to maximize utility gain. For the defender, a first-step deception mitigation process is proposed to thwart the effects of deception. Simulation results show that the attacker can profit from the deception as it can successfully insert HTs in the manufactured ICs without being detected.</div><div><br></div><div>This paper has been accepted for publication in <b>IEEE Cyber Science Conference 2020</b><br></div>

scholarly journals Think Smart, Play Dumb: Analyzing Deception in Hardware Trojan Detection Using Game Theory

2020 ◽  
Author(s):  
Tapadhir Das ◽  
AbdelRahman Eldosouky ◽  
Shamik Sengupta
Keyword(s):  
Integrated Circuits ◽  
Repeated Game ◽  
Third Party ◽  
Hardware Trojan ◽  
Hardware Trojans ◽  
Learning Stage ◽  
Hardware Trojan Detection ◽  
Trojan Detection ◽  
Utility Gain ◽  
Game Theoretic

In recent years, integrated circuits (ICs) have become<br>significant for various industries and their security has<br>been given greater priority, specifically in the supply chain.<br>Budgetary constraints have compelled IC designers to offshore manufacturing to third-party companies. When the designer gets the manufactured ICs back, it is imperative to test for potential threats like hardware trojans (HT). In this paper, a novel multilevel game-theoretic framework is introduced to analyze the interactions between a malicious IC manufacturer and the tester. In particular, the game is formulated as a non-cooperative, zerosum, repeated game using prospect theory (PT) that captures different players’ rationalities under uncertainty. The repeated game is separated into a learning stage, in which the defender<br><div>learns about the attacker’s tendencies, and an actual game stage, where this learning is used. Experiments show great incentive for the attacker to deceive the defender about their actual rationality by “playing dumb” in the learning stage (deception). This scenario is captured using hypergame theory to model the attacker’s view of the game. The optimal deception rationality of the attacker is analytically derived to maximize utility gain. For the defender, a first-step deception mitigation process is proposed to thwart the effects of deception. Simulation results show that the attacker can profit from the deception as it can successfully insert HTs in the manufactured ICs without being detected.</div><div><br></div><div>This paper has been accepted for publication in <b>IEEE Cyber Science Conference 2020</b><br></div>

scholarly journals Think Smart, Play Dumb: Analyzing Deception in Hardware Trojan Detection Using Game Theory

2020 ◽  
Author(s):  
Tapadhir Das ◽  
AbdelRahman Eldosouky ◽  
Shamik Sengupta
Keyword(s):  
Integrated Circuits ◽  
Repeated Game ◽  
Third Party ◽  
Hardware Trojan ◽  
Hardware Trojans ◽  
Learning Stage ◽  
Hardware Trojan Detection ◽  
Trojan Detection ◽  
Utility Gain ◽  
Game Theoretic

In recent years, integrated circuits (ICs) have become<br>significant for various industries and their security has<br>been given greater priority, specifically in the supply chain.<br>Budgetary constraints have compelled IC designers to offshore manufacturing to third-party companies. When the designer gets the manufactured ICs back, it is imperative to test for potential threats like hardware trojans (HT). In this paper, a novel multilevel game-theoretic framework is introduced to analyze the interactions between a malicious IC manufacturer and the tester. In particular, the game is formulated as a non-cooperative, zerosum, repeated game using prospect theory (PT) that captures different players’ rationalities under uncertainty. The repeated game is separated into a learning stage, in which the defender<br><div>learns about the attacker’s tendencies, and an actual game stage, where this learning is used. Experiments show great incentive for the attacker to deceive the defender about their actual rationality by “playing dumb” in the learning stage (deception). This scenario is captured using hypergame theory to model the attacker’s view of the game. The optimal deception rationality of the attacker is analytically derived to maximize utility gain. For the defender, a first-step deception mitigation process is proposed to thwart the effects of deception. Simulation results show that the attacker can profit from the deception as it can successfully insert HTs in the manufactured ICs without being detected.</div><div><br></div><div>This paper has been accepted for publication in <b>IEEE Cyber Science Conference 2020</b><br></div>

scholarly journals FPGA Realization of Deep Neural Network for Hardware Trojan Detection

2020 ◽  
Vol 9 (3) ◽  
pp. 764
Author(s):  
Varun Reddy ◽  
Nirmala Devi M
Keyword(s):  
Neural Network ◽  
Integrated Circuits ◽  
Power Consumption ◽  
Deep Neural Network ◽  
Random Forest Classifier ◽  
Third Party ◽  
Hardware Trojan ◽  
Hardware Trojan Detection ◽  
Trojan Detection ◽  
Field Programmable

With the increase in outsourcing design and fabrication, malicious third-party vendors often insert hardware Trojan (HT) in the integrated Circuits(IC). It is difficult to identify these Trojans since the nature and characteristics of each Trojan differ significantly. Any method developed for HT detection is limited by its capacity on dealing with varied types of Trojans. The main purpose of this study is to show using deep learning (DL), this problem can be dealt with some extent and the effect of deep neural network (DNN) when it is realized on field programmable gate array (FPGA). In this paper, we propose a comparison of accuracy in finding faults on ISCAS’85 benchmark circuits between random forest classifier and DNN. Further for the faster processing time and less power consumption, the network is implemented on FPGA. The results show the performance of deep neural network gets better when a large number of nets are used and faster in the execution of the algorithm. Also, the speedup of the neuron is 100x times better when implemented on FPGA with 15.32% of resource utilization and provides less power consumption than GPU.

Design Space Exploration for Reducing Cost of Hardware Trojan Detection and Isolation during Architectural Synthesis

2020 ◽  
pp. 2150156
Author(s):  
Shathanaa Rajmohan ◽  
N. Ramasubramanian ◽  
Nagi Naganathan
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Detection Methods ◽  
Main Concern ◽  
Hardware Trojan ◽  
Hardware Trojans ◽  
Hardware Trojan Detection ◽  
Trojan Detection ◽  
The Cost

In past years, software used to be the main concern of computer security, and the hardware was assumed to be safe. However, Hardware Trojans, which are a malicious alteration to the circuit, pose a threat to the security of a system. Trojans may be distributed across different components of the system and can bring down the security by communicating with each other. Redundancy and vendor diversity-based methods exist to detect Hardware Trojans, but with an increase in the hardware overhead. This work proposes a novel vendor allocation procedure to reduce the hardware cost that comes with Trojan detection methods. To further reduce the cost by minimizing resource requirements, an evolutionary algorithm-based Design Space Exploration methodology is proposed with options for loop unrolling and operation chaining. For reducing the cost of hardware Trojan detection and isolation, the proposed algorithm extends an existing implementation of Firefly algorithm. The proposed method is compared with the existing algorithms, using cost-based and Pareto-based evaluations. The results obtained demonstrate the ability of the new algorithm in achieving better solutions with a 77% reduction in cost when compared to the previous solutions.

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