Efficient hardware trojan diagnosis in SRAM based on FPGA processors using inject detect masking algorithm for multimedia signal Processors

The multimedia processor is the most powerful and challenging application in real-time world where Hardware Trojans (HTs) is a significant threat in most of the electronic devices which use Integrated Circuit (IC) as a crucial component. Since IC is manufactured by most of the untrusted designers, t...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Microprocessors and microsystems Ročník 77; s. 103168
Hlavní autori: Swamynathan, S.M., Bhanumathi, V.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Kidlington Elsevier B.V 01.09.2020
Elsevier BV
Predmet:
ISSN:0141-9331, 1872-9436
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract The multimedia processor is the most powerful and challenging application in real-time world where Hardware Trojans (HTs) is a significant threat in most of the electronic devices which use Integrated Circuit (IC) as a crucial component. Since IC is manufactured by most of the untrusted designers, there is a possibility of inserting malicious attacks in any stages of fabrication. It is mainly added by an antagonist into the storage cell to make a detection process is a complex task, which creates an impact in the function of the device. To mitigate these issues, an IDM (Inject Detect Masking) algorithm is proposed, and it is implemented in a Look-Up Table (LUT) design, which exploited Stability Enhancing Static Random Access Memory (SESRAM) cell for storing the data bits. HT is injected at the output of the SESRAM cell, and then masking is applied to mitigate the HT. The proposed Inject Detect Masking (IDM) algorithm is designed and simulated in Tanner EDA with 125 nm technology. It is used to multimedia signal processors world in real-time applications to achieve better response in processor end solutions. It increases the detection rate by 8.88%, 8.88%, 5.37%, 4.25% and correction coverage by 5.26%, 28.20%, 21.95%, 13.63%, 11.11%, 7.52% when compared with Online Checking Technique, Simultaneous Orthogonal Matching Pursuit (SOMP) algorithm, Multiple Excitation of Rare Switching (MERS), LMDet and Clustering Ensemble-based Detection respectively.
AbstractList The multimedia processor is the most powerful and challenging application in real-time world where Hardware Trojans (HTs) is a significant threat in most of the electronic devices which use Integrated Circuit (IC) as a crucial component. Since IC is manufactured by most of the untrusted designers, there is a possibility of inserting malicious attacks in any stages of fabrication. It is mainly added by an antagonist into the storage cell to make a detection process is a complex task, which creates an impact in the function of the device. To mitigate these issues, an IDM (Inject Detect Masking) algorithm is proposed, and it is implemented in a Look-Up Table (LUT) design, which exploited Stability Enhancing Static Random Access Memory (SESRAM) cell for storing the data bits. HT is injected at the output of the SESRAM cell, and then masking is applied to mitigate the HT. The proposed Inject Detect Masking (IDM) algorithm is designed and simulated in Tanner EDA with 125 nm technology. It is used to multimedia signal processors world in real-time applications to achieve better response in processor end solutions. It increases the detection rate by 8.88%, 8.88%, 5.37%, 4.25% and correction coverage by 5.26%, 28.20%, 21.95%, 13.63%, 11.11%, 7.52% when compared with Online Checking Technique, Simultaneous Orthogonal Matching Pursuit (SOMP) algorithm, Multiple Excitation of Rare Switching (MERS), LMDet and Clustering Ensemble-based Detection respectively.
The multimedia processor is the most powerful and challenging application in real-time world where Hardware Trojans (HTs) is a significant threat in most of the electronic devices which use Integrated Circuit (IC) as a crucial component. Since IC is manufactured by most of the untrusted designers, there is a possibility of inserting malicious attacks in any stages of fabrication. It is mainly added by an antagonist into the storage cell to make a detection process is a complex task, which creates an impact in the function of the device. To mitigate these issues, an IDM (Inject Detect Masking) algorithm is proposed, and it is implemented in a Look-Up Table (LUT) design, which exploited Stability Enhancing Static Random Access Memory (SESRAM) cell for storing the data bits. HT is injected at the output of the SESRAM cell, and then masking is applied to mitigate the HT. The proposed Inject Detect Masking (IDM) algorithm is designed and simulated in Tanner EDA with 125 nm technology. It is used to multimedia signal processors world in real-time applications to achieve better response in processor end solutions. It increases the detection rate by 8.88%, 8.88%, 5.37%, 4.25% and correction coverage by 5.26%, 28.20%, 21.95%, 13.63%, 11.11%, 7.52% when compared with Online Checking Technique, Simultaneous Orthogonal Matching Pursuit (SOMP) algorithm, Multiple Excitation of Rare Switching (MERS), LMDet and Clustering Ensemble-based Detection respectively.
ArticleNumber 103168
Author Bhanumathi, V.
Swamynathan, S.M.
Author_xml – sequence: 1
  givenname: S.M.
  surname: Swamynathan
  fullname: Swamynathan, S.M.
  email: swamynathan2019phd@gmail.com
  organization: Department of ECE, SNS College of Technology, Coimbatore, Tamil Nadu, India
– sequence: 2
  givenname: V.
  surname: Bhanumathi
  fullname: Bhanumathi, V.
  organization: Department of ECE, Anna University Regional Campus, Coimbatore, Tamil Nadu, India
BookMark eNqFkcFu1DAQhi3USmxb3oCDJc5ZPLHjTTggraq2IBW1Kr1bE9vZOiR2sb0gnoGXxlEQBw5wGmn0___MfHNGTnzwlpDXwLbAQL4dt7PTzzFsa1YvLQ6yfUE20O7qqhNcnpANAwFVxzm8JGcpjYyxhsl6Q35eDYPTzvpMnzCa7xgtzTGM6KlxePAhuUSdp58f9p9oj8kaGjy9vr_Z0zJQ25RCTPSYnD8U2Wh1psbmpcyYvixdnA4huvw00yFEOh-n7GZbsmlyB48Tvf8Tc0FOB5ySffW7npPH66vHyw_V7d3Nx8v9baU5F7kytewADfZcS0Tbg7V1NzRiEJ1set7JVnLkTbMTYte3_WAaqAeNAIIhGODn5M0aWw74erQpqzEcY1klqVpIkNBAu6jEqtIxpBTtoJ6jmzH-UMDUQl2NaqWuFupqpV5s7_6yaZcxu-BzRDf9z_x-Ndty_Tdno0rLa3TBFQtSZYL7d8Av8aykmg
CitedBy_id crossref_primary_10_1109_ACCESS_2023_3294282
Cites_doi 10.1109/TCAD.2016.2638442
10.1109/TCSII.2018.2858798
10.1109/TIFS.2018.2833059
10.1016/j.neucom.2017.10.009
10.1109/TVLSI.2017.2727985
10.1109/TVT.2017.2686853
10.1109/TCAD.2017.2748021
10.1049/iet-cdt.2018.5108
10.1109/TETC.2017.2654268
10.1109/TSM.2017.2763088
10.1016/j.compeleceng.2017.09.027
10.1109/TVLSI.2018.2879878
10.1109/ACCESS.2019.2896479
10.1109/TVLSI.2017.2781423
10.1109/TDSC.2017.2654352
10.1109/TVLSI.2018.2844180
ContentType Journal Article
Copyright 2020
Copyright Elsevier BV Sep 2020
Copyright_xml – notice: 2020
– notice: Copyright Elsevier BV Sep 2020
DBID AAYXX
CITATION
7SC
7SP
8FD
F28
FR3
JQ2
L7M
L~C
L~D
DOI 10.1016/j.micpro.2020.103168
DatabaseName CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ANTE: Abstracts in New Technology & Engineering
Engineering Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Technology Research Database
Computer and Information Systems Abstracts – Academic
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Engineering Research Database
Advanced Technologies Database with Aerospace
ANTE: Abstracts in New Technology & Engineering
Computer and Information Systems Abstracts Professional
DatabaseTitleList Technology Research Database

DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 1872-9436
ExternalDocumentID 10_1016_j_micpro_2020_103168
S0141933120303355
GroupedDBID --K
--M
-~X
.DC
.~1
0R~
123
1B1
1~.
1~5
29M
4.4
457
4G.
5VS
7-5
71M
8P~
9JN
AACTN
AAEDT
AAEDW
AAIAV
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AAXUO
AAYFN
ABBOA
ABJNI
ABMAC
ABXDB
ABYKQ
ACDAQ
ACGFS
ACIWK
ACNNM
ACRLP
ACZNC
ADBBV
ADEZE
ADJOM
ADMUD
ADTZH
AEBSH
AECPX
AEKER
AENEX
AFKWA
AFTJW
AGHFR
AGUBO
AGYEJ
AHHHB
AHJVU
AHZHX
AIALX
AIEXJ
AIKHN
AITUG
AJBFU
AJOXV
ALMA_UNASSIGNED_HOLDINGS
AMFUW
AMRAJ
AOUOD
AXJTR
BJAXD
BKOJK
BLXMC
CS3
DU5
EBS
EFJIC
EFLBG
EJD
EO8
EO9
EP2
EP3
F5P
FDB
FEDTE
FGOYB
FIRID
FNPLU
FYGXN
G-2
G-Q
G8K
GBLVA
GBOLZ
HLZ
HVGLF
HZ~
IHE
J1W
JJJVA
KOM
LG9
LY7
M41
MO0
N9A
O-L
O9-
OAUVE
OZT
P-8
P-9
P2P
PC.
PQQKQ
Q38
RIG
ROL
RPZ
SBC
SDF
SDG
SDP
SES
SET
SEW
SPC
SPCBC
SST
SSV
SSZ
T5K
T9H
TN5
UHS
WUQ
XOL
XPP
ZMT
~G-
9DU
AATTM
AAXKI
AAYWO
AAYXX
ABDPE
ABWVN
ACLOT
ACRPL
ACVFH
ADCNI
ADNMO
AEIPS
AEUPX
AFJKZ
AFPUW
AIGII
AIIUN
AKBMS
AKRWK
AKYEP
ANKPU
APXCP
CITATION
EFKBS
~HD
7SC
7SP
8FD
F28
FR3
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c334t-d2691adab3c6aaeb1ee29f54f4965b396863a3557447b8bfd512fca1140a1d13
ISICitedReferencesCount 1
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000571471000004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 0141-9331
IngestDate Sun Nov 30 04:13:20 EST 2025
Tue Nov 18 21:32:38 EST 2025
Sat Nov 29 07:24:57 EST 2025
Fri Feb 23 02:48:31 EST 2024
IsPeerReviewed true
IsScholarly true
Keywords Inject Detect Masking algorithm
Fpga
Processors
Look up table, Sesram
Hardware trojans
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c334t-d2691adab3c6aaeb1ee29f54f4965b396863a3557447b8bfd512fca1140a1d13
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
PQID 2461615181
PQPubID 2045426
ParticipantIDs proquest_journals_2461615181
crossref_primary_10_1016_j_micpro_2020_103168
crossref_citationtrail_10_1016_j_micpro_2020_103168
elsevier_sciencedirect_doi_10_1016_j_micpro_2020_103168
PublicationCentury 2000
PublicationDate September 2020
2020-09-00
20200901
PublicationDateYYYYMMDD 2020-09-01
PublicationDate_xml – month: 09
  year: 2020
  text: September 2020
PublicationDecade 2020
PublicationPlace Kidlington
PublicationPlace_xml – name: Kidlington
PublicationTitle Microprocessors and microsystems
PublicationYear 2020
Publisher Elsevier B.V
Elsevier BV
Publisher_xml – name: Elsevier B.V
– name: Elsevier BV
References Chakraborty, Pagliarini, Mathew, Rajendran, Devi (bib0004) 2017; 5
Shen, Tan, Li, Zhang, Li (bib0016) 2018; 26
Aranda, Reviriego, Maestro (bib0018) 2018; 7
Fujimoto, Nin, Hayashi, Miura, Nagata, Matsumoto (bib0014) 2018; 65
Chen (bib0005) July 2018; 37
Xue, Bian, Liu, Wang (bib0017) 2018
He, Zhao, Guo, Jin (bib0007) 2017; 25
Sebt, Patooghy, Beitollahi, Kinsy (bib0010) 2018
Dong, He, Liu, Yang, Guo (bib0013) 2019; 7
Ding, Han, Xiang, Ge, Zhang (bib0020) 2018; 275
Huang, Bhuniay, Mishra (bib0008) 2018; 13
Khan, Rashid, Javaid (bib0019) 2018; 66
Saad, Sanjab, Wang, Kamhoua, Kwiat (bib0015) 2017; 66
Chen (bib0003) 2017; 36
Hoque, Wang, Basak, Karam, Bhunia (bib0002) 2018
Zhang, Njilla, Charles (bib0011) 2018; 27
Haider (bib0006) 2019; 16
Ranjbar, Bayat-Sarmadi, Pooyan (bib0001) 2019
Schulze, Beetner (bib0009) 2018; 26
Xue, Ren (bib0012) February 2018; 31
Chakraborty (10.1016/j.micpro.2020.103168_bib0004) 2017; 5
Haider (10.1016/j.micpro.2020.103168_bib0006) 2019; 16
Xue (10.1016/j.micpro.2020.103168_bib0017) 2018
Xue (10.1016/j.micpro.2020.103168_bib0012) 2018; 31
Saad (10.1016/j.micpro.2020.103168_bib0015) 2017; 66
Chen (10.1016/j.micpro.2020.103168_bib0005) 2018; 37
Khan (10.1016/j.micpro.2020.103168_bib0019) 2018; 66
He (10.1016/j.micpro.2020.103168_bib0007) 2017; 25
Hoque (10.1016/j.micpro.2020.103168_bib0002) 2018
Chen (10.1016/j.micpro.2020.103168_bib0003) 2017; 36
Huang (10.1016/j.micpro.2020.103168_bib0008) 2018; 13
Schulze (10.1016/j.micpro.2020.103168_bib0009) 2018; 26
Ranjbar (10.1016/j.micpro.2020.103168_bib0001) 2019
Dong (10.1016/j.micpro.2020.103168_bib0013) 2019; 7
Sebt (10.1016/j.micpro.2020.103168_bib0010) 2018
Shen (10.1016/j.micpro.2020.103168_bib0016) 2018; 26
Ding (10.1016/j.micpro.2020.103168_bib0020) 2018; 275
Zhang (10.1016/j.micpro.2020.103168_bib0011) 2018; 27
Fujimoto (10.1016/j.micpro.2020.103168_bib0014) 2018; 65
Aranda (10.1016/j.micpro.2020.103168_bib0018) 2018; 7
References_xml – volume: 66
  start-page: 7697
  year: 2017
  end-page: 7710
  ident: bib0015
  article-title: Hardware Trojan Detection Game: a Prospect-Theoretic Approach
  publication-title: IEEE Trans. Veh. Technol.
– volume: 275
  start-page: 1674
  year: 2018
  end-page: 1683
  ident: bib0020
  article-title: A survey on security control and attack detection for industrial cyber-physical systems
  publication-title: Neurocomputing
– volume: 31
  year: February 2018
  ident: bib0012
  article-title: Self-Reference-Based Hardware Trojan Detection
  publication-title: IEEE Trans. Semicond. Manuf.
– volume: 37
  start-page: 1370
  year: July 2018
  end-page: 1383
  ident: bib0005
  article-title: “Hardware Trojan Detection in Third-Party Digital Intellectual Property Cores by Multi-Level Feature Analysis
  publication-title: IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
– volume: 7
  start-page: 322
  year: 2018
  ident: bib0018
  article-title: Protecting Image Processing Pipelines against Configuration Memory Errors in SRAM-Based FPGAs
  publication-title: Electronics (Basel)
– start-page: 1
  year: 2019
  end-page: 14
  ident: bib0001
  article-title: and Hossein Asadi “A Unified Approach to Detect and Distinguish Hardware Trojans and Faults in SRAM-based FPGAs”
  publication-title: J Electron. Test. Springer
– year: 2018
  ident: bib0002
  article-title: Hardware Trojan Attacks in Embedded Memory
  publication-title: IEEE 36th VLSI Test Symposium (VTS)
– volume: 5
  start-page: 260
  year: 2017
  end-page: 270
  ident: bib0004
  article-title: A Flexible Online Checking Technique to Enhance Hardware Trojan Horse Detectability by Reliability Analysis
  publication-title: IEEE Trans Emerg Top Comput
– year: 2018
  ident: bib0017
  article-title: Defeating Untrustworthy Testing Parties: a Novel Hybrid Clustering Ensemble Based Golden Models-Free Hardware Trojan Detection Method
  publication-title: IEEE Access
– volume: 26
  start-page: 2007
  year: 2018
  end-page: 2015
  ident: bib0009
  article-title: Combating Data Leakage Trojans in Commercial and ASIC Applications With Time-Division Multiplexing and Random Encoding
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
– volume: 7
  start-page: 23628
  year: 2019
  end-page: 23639
  ident: bib0013
  article-title: A Multi-Layer Hardware Trojan Protection Framework for IoT Chips
  publication-title: IEEE Access
– volume: 66
  start-page: 14
  year: 2018
  end-page: 29
  ident: bib0019
  article-title: A high performance processor architecture for multimedia applications
  publication-title: Comput Electr Eng
– volume: 16
  start-page: 18
  year: 2019
  end-page: 32
  ident: bib0006
  article-title: Advancing the State-of-the-Art in Hardware Trojans Detection
  publication-title: IEEE Trans Dependable Secure Comput
– volume: 27
  start-page: 665
  year: 2018
  end-page: 678
  ident: bib0011
  article-title: Kamhoua, and Qiaoyan Yu, “Thwarting Security Threats From Malicious FPGA Tools With Novel FPGA-Oriented Moving Target Defense
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
– volume: 26
  start-page: 720
  year: 2018
  end-page: 732
  ident: bib0016
  article-title: LMDet: a “Naturalness” Statistical Method for Hardware Trojan Detection
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
– volume: 25
  year: 2017
  ident: bib0007
  article-title: Hardware Trojan Detection Through Chip-Free Electromagnetic Side-Channel Statistical Analysis
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
– volume: 13
  start-page: 2746
  year: 2018
  end-page: 2760
  ident: bib0008
  article-title: Scalable Test Generation for Trojan Detection using Side Channel Analysis
  publication-title: IEEE Trans. Inf. Forensics Secur.
– volume: 65
  start-page: 1320
  year: 2018
  end-page: 1324
  ident: bib0014
  article-title: A demonstration of HT-detection method based on impedance measurements of the wiring around ICs
  publication-title: IEEE Trans. Circuits Syst. Express Br.
– year: 2018
  ident: bib0010
  article-title: Circuit enclaves susceptible to hardware Trojans insertion at gate-level designs
  publication-title: IET Comput Digit. Tech.
– volume: 36
  start-page: 1633
  year: 2017
  end-page: 1646
  ident: bib0003
  article-title: “A general Framework for Trojan Detection in Digital Circuits by Statistical Learning Algorithms
  publication-title: IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
– volume: 36
  start-page: 1633
  issue: 10
  year: 2017
  ident: 10.1016/j.micpro.2020.103168_bib0003
  article-title: “A general Framework for Trojan Detection in Digital Circuits by Statistical Learning Algorithms
  publication-title: IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
  doi: 10.1109/TCAD.2016.2638442
– volume: 65
  start-page: 1320
  issue: 10
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0014
  article-title: A demonstration of HT-detection method based on impedance measurements of the wiring around ICs
  publication-title: IEEE Trans. Circuits Syst. Express Br.
  doi: 10.1109/TCSII.2018.2858798
– volume: 13
  start-page: 2746
  issue: 11
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0008
  article-title: Scalable Test Generation for Trojan Detection using Side Channel Analysis
  publication-title: IEEE Trans. Inf. Forensics Secur.
  doi: 10.1109/TIFS.2018.2833059
– volume: 275
  start-page: 1674
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0020
  article-title: A survey on security control and attack detection for industrial cyber-physical systems
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2017.10.009
– start-page: 1
  year: 2019
  ident: 10.1016/j.micpro.2020.103168_bib0001
  article-title: and Hossein Asadi “A Unified Approach to Detect and Distinguish Hardware Trojans and Faults in SRAM-based FPGAs”
  publication-title: J Electron. Test. Springer
– volume: 25
  issue: 10
  year: 2017
  ident: 10.1016/j.micpro.2020.103168_bib0007
  article-title: Hardware Trojan Detection Through Chip-Free Electromagnetic Side-Channel Statistical Analysis
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
  doi: 10.1109/TVLSI.2017.2727985
– year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0017
  article-title: Defeating Untrustworthy Testing Parties: a Novel Hybrid Clustering Ensemble Based Golden Models-Free Hardware Trojan Detection Method
  publication-title: IEEE Access
– volume: 7
  start-page: 322
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0018
  article-title: Protecting Image Processing Pipelines against Configuration Memory Errors in SRAM-Based FPGAs
  publication-title: Electronics (Basel)
– volume: 66
  start-page: 7697
  issue: 9
  year: 2017
  ident: 10.1016/j.micpro.2020.103168_bib0015
  article-title: Hardware Trojan Detection Game: a Prospect-Theoretic Approach
  publication-title: IEEE Trans. Veh. Technol.
  doi: 10.1109/TVT.2017.2686853
– volume: 37
  start-page: 1370
  issue: 7
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0005
  article-title: “Hardware Trojan Detection in Third-Party Digital Intellectual Property Cores by Multi-Level Feature Analysis
  publication-title: IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
  doi: 10.1109/TCAD.2017.2748021
– year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0010
  article-title: Circuit enclaves susceptible to hardware Trojans insertion at gate-level designs
  publication-title: IET Comput Digit. Tech.
  doi: 10.1049/iet-cdt.2018.5108
– volume: 5
  start-page: 260
  issue: 2
  year: 2017
  ident: 10.1016/j.micpro.2020.103168_bib0004
  article-title: A Flexible Online Checking Technique to Enhance Hardware Trojan Horse Detectability by Reliability Analysis
  publication-title: IEEE Trans Emerg Top Comput
  doi: 10.1109/TETC.2017.2654268
– volume: 31
  issue: 1
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0012
  article-title: Self-Reference-Based Hardware Trojan Detection
  publication-title: IEEE Trans. Semicond. Manuf.
  doi: 10.1109/TSM.2017.2763088
– volume: 66
  start-page: 14
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0019
  article-title: A high performance processor architecture for multimedia applications
  publication-title: Comput Electr Eng
  doi: 10.1016/j.compeleceng.2017.09.027
– year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0002
  article-title: Hardware Trojan Attacks in Embedded Memory
– volume: 27
  start-page: 665
  issue: 3
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0011
  article-title: Kamhoua, and Qiaoyan Yu, “Thwarting Security Threats From Malicious FPGA Tools With Novel FPGA-Oriented Moving Target Defense
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
  doi: 10.1109/TVLSI.2018.2879878
– volume: 7
  start-page: 23628
  year: 2019
  ident: 10.1016/j.micpro.2020.103168_bib0013
  article-title: A Multi-Layer Hardware Trojan Protection Framework for IoT Chips
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2896479
– volume: 26
  start-page: 720
  issue: 4
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0016
  article-title: LMDet: a “Naturalness” Statistical Method for Hardware Trojan Detection
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
  doi: 10.1109/TVLSI.2017.2781423
– volume: 16
  start-page: 18
  issue: 1
  year: 2019
  ident: 10.1016/j.micpro.2020.103168_bib0006
  article-title: Advancing the State-of-the-Art in Hardware Trojans Detection
  publication-title: IEEE Trans Dependable Secure Comput
  doi: 10.1109/TDSC.2017.2654352
– volume: 26
  start-page: 2007
  issue: 10
  year: 2018
  ident: 10.1016/j.micpro.2020.103168_bib0009
  article-title: Combating Data Leakage Trojans in Commercial and ASIC Applications With Time-Division Multiplexing and Random Encoding
  publication-title: IEEE Trans. Very Large Scale Integr. VLSI Syst.
  doi: 10.1109/TVLSI.2018.2844180
SSID ssj0005062
Score 2.1994288
Snippet The multimedia processor is the most powerful and challenging application in real-time world where Hardware Trojans (HTs) is a significant threat in most of...
SourceID proquest
crossref
elsevier
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 103168
SubjectTerms Algorithms
Clustering
Electronic design automation
Electronic devices
Fpga
Hardware
Hardware trojans
Inject Detect Masking algorithm
Integrated circuits
Look up table, Sesram
Lookup tables
Malware
Masking
Matched pursuit
Microprocessors
Multimedia
Processors
Random access memory
Real time
Signal processing
Static random access memory
Storage
Title Efficient hardware trojan diagnosis in SRAM based on FPGA processors using inject detect masking algorithm for multimedia signal Processors
URI https://dx.doi.org/10.1016/j.micpro.2020.103168
https://www.proquest.com/docview/2461615181
Volume 77
WOSCitedRecordID wos000571471000004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVESC
  databaseName: Elsevier SD Freedom Collection Journals 2021
  customDbUrl:
  eissn: 1872-9436
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0005062
  issn: 0141-9331
  databaseCode: AIEXJ
  dateStart: 19950101
  isFulltext: true
  titleUrlDefault: https://www.sciencedirect.com
  providerName: Elsevier
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lj9MwELZKlwMX3oiFBc2BW5Rq82hiHyvU5SF1VUEPvUVOnEBLk1Z97OO0P4A_zYwdJ9VWaAGJS1RZTZzk--yMx9_MMPYuCDORqUK5USEiN4xz7qZ91Xc9mUmks4x9xXWxifj8nE-nYtzp3NhYmItFXFX86kqs_ivU2IZgU-jsX8DdXBQb8DeCjkeEHY9_BPxQJ4WgLX4KqLokZdd2vZzjOFZGVjfTEtivXwYjh75hivYLzsYfBs7KBA1Q-Z3dxsS6kJfGUTntNDil3PzQIY2Lb8v1bPu91BJFrUjU8ScOaUEQ8XFzmX3Ld0TKv70eyGFfUttmL2c6uXouZXltPPraM9sb9RqXAbbtSpJLanVub99jgctTK8mq3WgHoTS1Z9NzhQ3fys1szGPfFaHJkGKna1P15WDmN06IeQ_vHJ-lR_1SQgHPFO25lVObJG0edebjHBegyXWPHflxX_AuOxp8Gk4_tyqhU12Ttrk7G32pJYKHff3Ourn1ndfGy-Qxe1ivOmBg2PKEdfLqKXtkK3pAPcE_Yz8b8oAlDxjyQEMemFVA5AFNHlhWQOSBFlrQ5AFDHjDkgZo80JAHkDzQkgcMeaAlz3M2ORtO3n9063IdbhYE4dZVfiQ8qWQaZJGUaAPkuS-KflhQSYI0EBHHsY_vOg7DOOVpodDWLDKJC_JT6SkveMG61bLKXzJII55mnAdpHPphlEuhCIlcyiwK0kLyYxbYt5xkdSp7qqiySKxmcZ4YbBLCJjHYHDO3OWtlUrnc8f_YApjU5qgxMxPk3B1nnli8k3pm2CSUuJGWD9x79c8Xfs0etAPqhHW3613-ht3PLrazzfptzd1fJaDBzw
linkProvider Elsevier
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Efficient+hardware+trojan+diagnosis+in+SRAM+based+on+FPGA+processors+using+inject+detect+masking+algorithm+for+multimedia+signal+Processors&rft.jtitle=Microprocessors+and+microsystems&rft.au=Swamynathan%2C+S.M.&rft.au=Bhanumathi%2C+V.&rft.date=2020-09-01&rft.pub=Elsevier+B.V&rft.issn=0141-9331&rft.eissn=1872-9436&rft.volume=77&rft_id=info:doi/10.1016%2Fj.micpro.2020.103168&rft.externalDocID=S0141933120303355
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0141-9331&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0141-9331&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0141-9331&client=summon