An Energy-Efficient Trusted FSM Design Technique to Thwart Fault Injection and Trojan Attacks

Rathor, Vijaypal Singh; Garg, Bharat; Sharma, Govind

doi:10.1109/vlsid.2018.40

Cited by 9 publications

(3 citation statements)

References 11 publications

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“…Without knowing the state registers of the netlist, brute force checking of manufactured chips is time consuming, making it hard to detect the malicious circuit of the afflicted core. Some fault injection attacks [6], [7] also target FSM state registers to crack the cipher key used to encrypt the sensitive information. Such attacks usually assume knowledge about the FSM.…”

Section: Introductionmentioning

confidence: 99%

Identification of FSM State Registers by Analytics of Scan-Dump Data

Cui

Chang

et al. 2021

IEEE Trans.Inform.Forensic Secur.

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Big data analytics have gained tremendous successes in mining valuable information in various fields. However, its potential to solve complex problems in hardware security has not been adequately tapped. This paper presents a non-invasive approach to identify the state registers of a finite state machine (FSM) in an integrated chip. The state registers of the FSM are mined from the scan-dump data by exploiting the strongly connected property and chronologically correlated state codes of the FSM. The sequence of data scanned out of each scan register is partitioned into non-overlapping strings of high weighted frequencies by a string-matching algorithm. A coherency between a pair of registers is defined and computed based on the partitioned strings. The dimension of the coherency matrix is first reduced by pruning some registers of low influence by a regression analysis. The registers are then clustered to minimize the within-cluster variances based on their coherency values. The proposed scheme is applied to some IP cores from OpenCores. The experimental results show that our scheme can correctly identify the FSM state registers in most designs with high hit rate.

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Section: Introductionmentioning

confidence: 99%

Identification of FSM State Registers by Analytics of Scan-Dump Data

Cui

Chang

et al. 2021

IEEE Trans.Inform.Forensic Secur.

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show abstract

“…Due to the intuitive description of Mealy [1] and Moore [2] machines, FSMs are widely adopted in various operational models [3][4][5]. In particular, modern digital circuits generally employ FSMs to build control paths that control the data path efficiently [6,7]. Furthermore, FSMs should be carefully dealt with because even a minute variation in them could completely alter the overall operation of the digital circuits [6,7].…”

Section: Introductionmentioning

confidence: 99%

Area-Efficient Differential Fault Tolerance Encoding for Finite State Machines

Park

Yoo

2020

Electronics

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A differential fault tolerance encoding is presented for finite state machines (FSMs) to improve their area efficiency. As the manufacturing technology for semiconductors continues to scale down, the probability of the occurrence of unexpected faults in integrated circuits has been increasing. Because an FSM controls an entire digital circuit, the faults in FSMs should be carefully addressed. Whereas the previous encoding applies a fault tolerance scheme to all the states in an FSM, the proposed encoding applies a fault tolerance scheme to only specific states depending on their importance. Compared with the previous complete fault tolerance encoding, the proposed encoding provides a comparable failure probability with a small hardware by applying the fault tolerance scheme differently to each state. The proposed method improves the area efficiency by 36.1%, 43.8%, 49.2%, and 74.6% compared with that by the non-fault tolerance, previous hardware redundancy, information redundancy, and time redundancy methods, respectively. Consequently, the proposed method can provide a flexible solution by applying the fault tolerance differently depending on the importance of the states.

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“…It is also noted that some fault injection [8,9] attacks have been proposed to inject faults into the FSM to crack the cipher key that is used to encrypt sensitive information. The success of such attack relies on the fact that the FSM design structure is not kept secret.…”

Section: Introductionmentioning

confidence: 99%

Identification of State Registers of FSM Through Full Scan by Data Analytics

Cui

Chang

2019

2019 Asian Hardware Oriented Security and Trust Symposium (AsianHOST)

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Finite-state machine (FSM) is widely used as control unit in most digital designs. Many intellectual property protection and obfuscation techniques leverage on the exponential number of possible states and state transitions of large FSM to secure a physical design with the reason that it is challenging to retrieve the FSM design from its downstream design or physical implementation without knowledge of the design. In this paper, we postulate that this assumption may not be sustainable with big data analytics. We demonstrate by applying a data mining technique to analyze sufficiently large amount of data collected from a full scan design to identify its FSM state registers. An impact metric is introduced to discriminate FSM state registers from other registers. A decision tree algorithm is constructed from the scan data for the regression analysis of the dependency of other registers on a chosen register to deduce its impact. The registers with the greater impact are more likely to be the FSM state registers. The proposed scheme is applied on several complex designs from OpenCores. The experiment results show the feasibility of our scheme in correctly identifying most FSM state registers with a high hit rate for a large majority of the designs.

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An Energy-Efficient Trusted FSM Design Technique to Thwart Fault Injection and Trojan Attacks

Cited by 9 publications

References 11 publications

Identification of FSM State Registers by Analytics of Scan-Dump Data

Identification of FSM State Registers by Analytics of Scan-Dump Data

Area-Efficient Differential Fault Tolerance Encoding for Finite State Machines

Identification of State Registers of FSM Through Full Scan by Data Analytics

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