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Secure Multiparty Computation and Trusted Hardware: Examining Adoption Challenges and Opportunities
2019
Security and Communication Networks
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When two or more parties need to compute a common result while safeguarding their sensitive inputs, they use secure multiparty computation (SMC) techniques such as garbled circuits. ...
This paper revisits the history of improvements to SMC over the years and considers the possibility of coupling trusted hardware with SMC. ...
They show that adaptive security of garbled circuits supports one-time programs [24] and secure outsourcing [25] . ...
doi:10.1155/2019/1368905
fatcat:izynm6msrvehfa3ghkw7tykk34
Blazing Fast 2PC in the Offline/Online Setting with Security for Malicious Adversaries
2015
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security - CCS '15
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We design a highly optimized protocol in the offline/online setting that makes use of all state-of-the-art techniques, along with several new techniques that we introduce. ...
Recently, several new techniques were presented to dramatically improve key parts of secure two-party computation (2PC) protocols that use the cut-and-choose paradigm on garbled circuits for 2PC with security ...
given security parameter, is complex). ...
doi:10.1145/2810103.2813666
dblp:conf/ccs/LindellR15
fatcat:jyffjjnsurdxjdxz7c6tjjxrx4
Authenticated Garbling and Efficient Maliciously Secure Two-Party Computation
2017
Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security - CCS '17
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with malicious security in 37 ms with an online time of just 1 ms. ...
Previous work with the best online time (also 1 ms) requires 124 ms in total; previous work with the best total time requires 62 ms (with 14 ms online time). • If we amortize the computation over 1024 ...
[IKOS09] , we obtain a maliciously secure constant-round 2PC protocol with communication complexity O(|C|κ). ...
doi:10.1145/3133956.3134053
dblp:conf/ccs/WangRK17
fatcat:gaui5fypqnc6pm7e6mifd37cma
SoK: Privacy-Preserving Computation Techniques for Deep Learning
2021
Proceedings on Privacy Enhancing Technologies
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Deep Learning (DL) is a powerful solution for complex problems in many disciplines such as finance, medical research, or social sciences. ...
Recent advances in privacy-preserving computation techniques (i.e., Homomorphic Encryption and Secure Multiparty Computation) have enabled DL training and inference over protected data. ...
Several optimizations followed the initial proposal, including the point-and-permute optimization [72] , the half gates [73] , the free XOR gates [74, 75] or garbled row reduction [76, 77] . ...
doi:10.2478/popets-2021-0064
fatcat:hb3kdruxozbspnowy63gynuapy
Exploring Privacy Preservation in Outsourced K-Nearest Neighbors with Multiple Data Owners
2015
Proceedings of the 2015 ACM Workshop on Cloud Computing Security Workshop - CCSW '15
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In this work, we present the first framing and exploration of privacy preservation in an outsourced k-NN system with multiple data owners. ...
We discover that under a particularly practical threat model that covers numerous scenarios, there exists a set of adaptive attacks that breach the data privacy of any exact k-NN system. ...
There exists efficient implementations of garbled circuits [14, 6, 2, 22] , although naturally the garbled circuit's size and evaluation runtime increases with the complexity of the evaluated function's ...
doi:10.1145/2808425.2808430
dblp:conf/ccs/LiSP15
fatcat:5doyd7ar3veqnmbwowq4wfsjnq
A Review of Deep Learning Security and Privacy Defensive Techniques
2020
Mobile Information Systems
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survey of Deep Learning security and privacy security challenges and countermeasures in this paper. ...
costs, no need for data labeling, and identification of complex interactions, but it also has limitations like opaqueness, computationally intensive, need for abundant data, and more complex algorithms ...
complexity, and uniform stability. ...
doi:10.1155/2020/6535834
fatcat:37wc35bqcnavdd2u4622sxmiom
Maturity and Performance of Programmable Secure Computation
2016
IEEE Security and Privacy
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However, ongoing research and development is largely focused on active security and it is likely to gain more efficiency in the near future. ...
[HFKV12, KMsB13] ) that produce optimized circuits and software libraries implementing GC computation. ...
doi:10.1109/msp.2016.97
fatcat:6drshm66cvhsznobop2tb7g4ly
Exploring Privacy Preservation in Outsourced K-Nearest Neighbors with Multiple Data Owners
[article]
2015
arXiv
pre-print
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In this work, we present the first framing and exploration of privacy preservation in an outsourced k-NN system with multiple data owners. ...
We discover that under a particularly practical threat model that covers numerous scenarios, there exists a set of adaptive attacks that breach the data privacy of any exact k-NN system. ...
There exists efficient implementations of garbled circuits [15, 6, 2, 23] , although naturally the garbled circuit's size and evaluation runtime increases with the complexity of the evaluated function's ...
arXiv:1507.08309v1
fatcat:7eslwnbdivf7nnxijk5wr22fje
Secure Similar Sequence Query on Outsourced Genomic Data
2018
Proceedings of the 2018 on Asia Conference on Computer and Communications Security - ASIACCS '18
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To address the challenges of security and efficiency, we propose two protocols in the mixed form, which combine twoparty secure secret sharing, garbled circuit, and partial homomorphic encryptions together ...
The final, definitive version of this document can be found online at ASIACCS '18: ABSTRACT The growing availability of genomic data is unlocking research potentials on genomic-data analysis. ...
It is important to note that we apply free-XOR [24] technique for garbled circuits optimization. ...
doi:10.1145/3196494.3196535
dblp:conf/ccs/ChengHW18
fatcat:lqpqosfxdvhzbb7fknmc5gok3u
High performance logistic regression for privacy-preserving genome analysis
2021
BMC Medical Genomics
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Our main contributions are a new protocol for computing the activation function that requires neither secure comparison protocols nor Yao's garbled circuits, and a series of cryptographic engineering optimizations ...
The implementation in this work is a further optimized version of the implementation with which we won first place in Track 4 of the iDASH 2019 secure genome analysis competition. ...
Funding
Rafael Dowsley was supported by the BIU Center for Research in Applied Cryptography and Cyber Security in conjunction with the Israel National Cyber Bureau in the Prime Minister's Office. ...
doi:10.1186/s12920-020-00869-9
pmid:33472626
fatcat:fitswbgp7rgrxjusjzn6tz3wmm
FUTURE DIRECTIONS IN CLOUD COMPUTING ENCRYPTION TECHNOLOGIES
2017
Scientific Bulletin of Naval Academy
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Searchable encryption is a promising research field with many practical applications and for that matter it is considered a near-to-market technology. ...
His idea was to seek an encryption scheme with a low decryption complexity -a decryption operation that requires only a few operations. ...
doi:10.21279/1454-864x-17-i1-065
fatcat:2z3o5u45yrg4xpwl6udt7hldni
Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computation
[article]
2021
arXiv
pre-print
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The distributed tensor representations are dispersed on multiple clouds / fogs or servers / devices with metadata privacy, this provides both distributed trust and management to seamlessly secure big data ...
Tensor network decomposition and distributed tensor computation have been widely used in signal processing and machine learning for dimensionality reduction and large-scale optimization. ...
and garbled circuit are expensive in terms of communication complexity and therefore routinely operate with low-latency networks, furthermore, garbled circuit involves symmetric encryption during the online ...
arXiv:2101.04194v1
fatcat:pay7hgk24jddnmvxrexefhd7di
Secure Machine Learning over Relational Data
[article]
2021
arXiv
pre-print
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In this paper, we describe secure protocols to compute the join results of multiple tables conforming to a general foreign-key acyclic schema, and how to feed the results in secret-shared form to a secure ...
Furthermore, existing secure ML systems reveal the PKs in the join results. We strengthen the privacy protection to higher levels and achieve zero information leakage beyond the trained model. ...
On the other hand, our method does not need such an upper bound while having a near-linear complexity irrespective of the FK multiplicities. ...
arXiv:2109.14806v1
fatcat:7ucq3eiu5jhuflwq42ndetfbhq
Analysis and Application of Verifiable Computation Techniques in Blockchain Systems for the Energy Sector
2021
Frontiers in Blockchain
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In decentralized energy markets especially, the optimized allocation of energy products demands complex computation. ...
Blockchain could provide a base infrastructure for new tools and platforms that address these tasks in various aspects—ranging from dispatch optimization or dynamic load adaption to (local) market mechanisms ...
Grid operators need to forecast and dynamically adapt to the grid load depending on complex load flow calculations. ...
doi:10.3389/fbloc.2021.725322
fatcat:q2ym7s6f6nebvijoilwvoq57ty
Countering GATTACA
2011
Proceedings of the 18th ACM conference on Computer and communications security - CCS '11
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This allows us to implement in in silico some operations that are currently performed via in vitro methods, in a secure fashion. ...
However, this progress also prompts significant privacy challenges associated with potential loss, theft, or misuse of genomic data. ...
A general technique for secure text processing is introduced, combining garbled circuits and secure pattern matching. ...
doi:10.1145/2046707.2046785
dblp:conf/ccs/BaldiBCGT11
fatcat:le7xzcowz5dv7e32egaai5pkbq
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