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Edge computing is a paradigm that shifts data processing services to the network edge, where data are generated.
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Advanced encryption standard (aes), 2001-11-26 2001
M. Dworkin, E. Barker, J. Nechvatal, J. Foti, L. Bassham, E. Roback, and J. Dray · 2001
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Implementing selinux as a linux security module
S. Smalley, C. Vance, and W. Salamon · 2001
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Using the fluhrer, mantin, and shamir attack to break wep
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K-anonymity: A model for protecting privacy
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Anonymous usage of location-based services through spatial and temporal cloaking
M. Gruteser and D. Grunwald · 2003
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An experimental study of file permission vulnerabilities caused by single-bit errors in the selinux kernel policy file
M. Ihde and T. Brown · 2004
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Real-time operating systems
J. A. Stankovic and R. Rajkumar · 2004
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Automatic diagnosis and response to memory corruption vulnerabilities
J. Xu, P. Ning, C. Kil, Y. Zhai, and C. Bookholt · 2005
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Cache-collision timing attacks against aes
J. Bonneau and I. Mironov · 2006
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Trusted platform module basics: using TPM in embedded systems
S. L. Kinney · 2006
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Fast collision attack on md5, 2006
M. Stevens · 2006
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Advanced message queuing protocol
S. Vinoski · 2006
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Balancing the insider and outsider threat
R. Walton · 2006
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Freertos
R. Barry et al · 2008
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Robust defenses for cross-site request forgery
A. Barth, C. Jackson, and J. C. Mitchell · 2008
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The transport layer security (tls) protocol version 1.2
T. Dierks and E. Rescorla · 2008
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Advances in password cracking
S. Marechal · 2008
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Static detection of cross-site scripting vulnerabilities
G. Wassermann and Z. Su · 2008
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Analysis and design of a hardware/software trusted platform module for embedded systems
N. Aaraj, A. Raghunathan, and N. K. Jha · 2009
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Message Authentication Codes
M. Blanton · 2009
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Looper: Lightweight detection of infinite loops at runtime
J. Burnim, N. Jalbert, C. Stergiou, and K. Sen · 2009
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Silicon photomultiplier technology at stmicroelectronics
M. Mazzillo, G. Condorelli, D. Sanfilippo, G. Valvo, B. Carbone, G. Fallica, S. Billotta, M. Belluso, G. Bonanno, L. Cosentino, et al · 2009
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Local heating attacks on flash memory devices
S. Skorobogatov · 2009
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Attacking intel trusted execution technology
R. Wojtczuk and J. Rutkowska · 2009
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https://www.coresecurity.com/products
Coresecurity iam · 2010
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Grover vs. mceliece
D. J. Bernstein · 2010
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Tensorflow lite micro: Embedded machine learning on tinyml systems. arxiv 2020
R. David, J. Duke, A. Jain, V. Reddi, N. Jeffries, J. Li, N. Kreeger, I. Nappier, M. Natraj, S. Regev, et al · 2010
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A formally verified os kernel. now what?
G. Klein · 2010
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Key lengths contribution to the handbook of information security
A. K. Lenstra · 2010
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When good randomness goes bad: Virtual machine reset vulnerabilities and hedging deployed cryptography
T. Ristenpart and S. Yilek · 2010
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Optical fault masking attacks
S. Skorobogatov · 2010
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Transfer learning
L. Torrey and J. Shavlik · 2010
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Evolution of the ibm cloud: Enabling an enterprise cloud services ecosystem
A. Kochut, Y. Deng, M. R. Head, J. Munson, A. Sailer, H. Shaikh, C. Tang, A. Amies, M. Beaton, D. Geiss, et al · 2011
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LTE-the UMTS long term evolution: from theory to practice
S. Sesia, I. Toufik, and M. Baker · 2011
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Design of security enhanced tpm chip against invasive physical attacks
P. Choi and D. K. Kim · 2012
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Mining your ps and qs: Detection of widespread weak keys in network devices
N. Heninger, Z. Durumeric, E. Wustrow, and J. A. Halderman · 2012
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Securing legacy mobile medical devices
V. Pournaghshband, M. Sarrafzadeh, and P. Reiher · 2012
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Intel transactional synchronization extensions
R. Rajwar and M. Dixon · 2012
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Concurrency attacks
J. Yang, A. Cui, S. Stolfo, and S. Sethumadhavan · 2012
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Digital signature standard (dss), 2013-07-19 2013
E. Barker · 2013
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When firmware modifications attack: A case study of embedded exploitation
A. Cui, M. Costello, and S. Stolfo · 2013
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On the practicability of cold boot attacks
M. Gruhn and T. Müller · 2013
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Cve-2013-4134, 2013
MITRE · 2013
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An analytics framework to detect compromised iot devices using mobility behavior
M. Taneja · 2013
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Why privacy policies are so inscrutable, 2014
2014
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{ \{ ROP } \} is still dangerous: Breaking modern defenses
N. Carlini and D. Wagner · 2014
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Towards a systematic study of the covert channel attacks in smartphones
S. Chandra, Z. Lin, A. Kundu, and L. Khan · 2014
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On the effectiveness of nx, ssp, renewssp, and aslr against stack buffer overflows
H. M. Gisbert and I. Ripoll · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Qualcomm tips cortex-a57 plans: Snapdragon 810 combines eight 64-bit cpus, lte baseband
L. Gwennap · 2014
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Flipping bits in memory without accessing them: An experimental study of dram disturbance errors
Y. Kim, R. Daly, J. Kim, C. Fallin, J. H. Lee, D. Lee, C. Wilkerson, K. Lai, and O. Mutlu · 2014
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Efficient minimax strategies for square loss games
W. M. Koolen, A. Malek, and P. L. Bartlett · 2014
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Industry 4.0
H. Lasi, P. Fettke, H.-G. Kemper, T. Feld, and M. Hoffmann · 2014
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Why does cryptographic software fail? a case study and open problems
D. Lazar, H. Chen, X. Wang, and N. Zeldovich · 2014
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This poodle bites: exploiting the ssl 3.0 fallback
B. Möller, T. Duong, and K. Kotowicz · 2014
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Potential cyberattacks on automated vehicles
J. Petit and S. E. Shladover · 2014
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Microsoft services unaffected by openssl “heartbleed” vulnerability, 2014
M. Security · 2014
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The constrained application protocol (coap)
Z. Shelby, K. Hartke, and C. Bormann · 2014
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Anatomy of a goto fail – apple’s ssl bug explained, plus an unofficial patch for os x!, Feb. 2014
Sophos · 2014
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Toward inference attacks for k-anonymity
Y. Sun, L. Yin, L. Liu, and S. Xin · 2014
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The peril of fragmentation: Security hazards in android device driver customizations
X. Zhou, Y. Lee, N. Zhang, M. Naveed, and X. Wang · 2014
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Entropy poisoning from the hypervisor 6 . 857 final project
M. Alt, W. C. Barto, A. Fasano, and A. King · 2015
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Leakage-abuse attacks against searchable encryption
D. Cash, P. Grubbs, J. Perry, and T. Ristenpart · 2015
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Preventing man-in-the-middle attack in diffie-hellman key exchange protocol
A. S. Khader and D. Lai · 2015
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Last-level cache side-channel attacks are practical
F. Liu, Y. Yarom, Q. Ge, G. Heiser, and R. B. Lee · 2015
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Soc it to em: electromagnetic side-channel attacks on a complex system-on-chip
J. Longo, E. D. Mulder, D. Page, and M. Tunstall · 2015
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Don’t brick your car: Firmware confidentiality and rollback for vehicles
H. Mansor, K. Markantonakis, R. N. Akram, and K. Mayes · 2015
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Parallel active dictionary attack on wpa2-psk wi-fi networks
O. Nakhila, A. Attiah, Y. Jin, and C. Zou · 2015
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Mlaas: Machine learning as a service
M. Ribeiro, K. Grolinger, and M. A. Capretz · 2015
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Trusted execution environment: what it is, and what it is not
M. Sabt, M. Achemlal, and A. Bouabdallah · 2015
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A practical key exchange for the internet using lattice cryptography
V. Singh · 2015
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” i added’!’at the end to make it secure”: Observing password creation in the lab
B. Ur, F. Noma, J. Bees, S. M. Segreti, R. Shay, L. Bauer, N. Christin, and L. F. Cranor · 2015
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Controlled-channel attacks: Deterministic side channels for untrusted operating systems
Y. Xu, W. Cui, and M. Peinado · 2015
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Protecting endpoint devices in iot supply chain
K. Yang, D. Forte, and M. M. Tehranipoor · 2015
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Exploring iot application using raspberry pi
C. W. Zhao, J. Jegatheesan, and S. C. Loon · 2015
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Secure firmware validation and update for consumer devices in home networking
B.-C. Choi, S.-H. Lee, J.-C. Na, and J.-H. Lee · 2016
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Cisco fog director cross-site scripting vulnerability, Feb. 2016
Cisco · 2016
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Intel sgx explained
V. Costan and S. Devadas · 2016
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Cache qos: From concept to reality in the intel® xeon® processor e5-2600 v3 product family
A. Herdrich, E. Verplanke, P. Autee, R. Illikkal, C. Gianos, R. Singhal, and R. Iyer · 2016
Cited alongside, same era.
Analysis and study on invasion threat and security measures for smart home services in iot environment
M. Lee and J. Park · 2016
Cited alongside, same era.
Demystifying the secure enclave processor
T. Mandt, M. Solnik, and D. Wang · 2016
Cited alongside, same era.
The limitations of deep learning in adversarial settings
N. Papernot, P. McDaniel, S. Jha, M. Fredrikson, Z. B. Celik, and A. Swami · 2016
Cited alongside, same era.
Shorter hash-based signatures
G. C. Pereira, C. Puodzius, and P. S. Barreto · 2016
Cited alongside, same era.
Identity and access management as security-as-a-service from clouds
D. H. Sharma, C. Dhote, and M. M. Potey · 2016
Towards the development of realistic botnet dataset in the internet of things for network forensic analytics: Bot-iot dataset
N. Koroniotis, N. Moustafa, E. Sitnikova, and B. Turnbull · 2019
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Oracle High Availability, Disaster Recovery, and Cloud Services: Explore RAC, Data Guard, and Cloud Technology
Y. R. Kumar, N. Basha, K. K. KM, B. M. Sharma, and K. Kerekovski · 2019
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How to include ethics in machine learning research
M. Loi and M. Christen · 2019
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libmpk: Software abstraction for intel memory protection keys (intel { \{ MPK } \} )
S. Park, S. Lee, W. Xu, H. Moon, and T. Kim · 2019
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Demystifying arm trustzone: A comprehensive survey
S. Pinto and N. Santos · 2019
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Generative adversarial network for wireless signal spoofing
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Cited alongside, same era.
Internet of things (iot) connected devices installed base worldwide from 2015 to 2025, Nov. 2016
Statista · 2016
Cited alongside, same era.
Users really do plug in usb drives they find
M. Tischer, Z. Durumeric, S. Foster, S. Duan, A. Mori, E. Bursztein, and M. Bailey · 2016
Cited alongside, same era.
Stealing machine learning models via prediction { \{ APIs } \}
F. Tramèr, F. Zhang, A. Juels, M. K. Reiter, and T. Ristenpart · 2016
Cited alongside, same era.
A methodology for formalizing model-inversion attacks
X. Wu, M. Fredrikson, S. Jha, and J. F. Naughton · 2016
Cited alongside, same era.
Lorawan™ 1.1 specification
L. Alliance · 2017
Cited alongside, same era.
Understanding the mirai botnet
M. Antonakakis, T. April, M. Bailey, M. Bernhard, E. Bursztein, J. Cochran, Z. Durumeric, J. A. Halderman, L. Invernizzi, M. Kallitsis, et al · 2017
Cited alongside, same era.
Y. Shi, K. Davaslioglu, and Y. E. Sagduyu · 2019
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Privacy risks of securing machine learning models against adversarial examples
L. Song, R. Shokri, and P. Mittal · 2019
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Mqtt version 5.0
O. Standard · 2019
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Adaptive federated learning in resource constrained edge computing systems
S. Wang, T. Tuor, T. Salonidis, K. K. Leung, C. Makaya, T. He, and K. Chan · 2019
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Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
Y. Wang, W.-L. Chao, D. Garg, B. Hariharan, M. Campbell, and K. Q. Weinberger · 2019
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Edge computing security: State of the art and challenges
Y. Xiao, Y. Jia, C. Liu, X. Cheng, J. Yu, and W. Lv · 2019
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Edge computing security: State of the art and challenges
Y. Xiao, Y. Jia, C. Liu, X. Cheng, J. Yu, and W. Lv · 2019
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Partially policy-hidden attribute-based broadcast encryption with secure delegation in edge computing
H. Xiong, Y. Zhao, L. Peng, H. Zhang, and K.-H. Yeh · 2019
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A first look at deep learning apps on smartphones
M. Xu, J. Liu, Y. Liu, F. X. Lin, Y. Liu, and X. Liu · 2019
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Adversarial examples: Attacks and defenses for deep learning
X. Yuan, P. He, Q. Zhu, and X. Li · 2019
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A survey on federated learning: The journey from centralized to distributed on-site learning and beyond
S. AbdulRahman, H. Tout, H. Ould-Slimane, A. Mourad, C. Talhi, and M. Guizani · 2020
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Ssd-assisted ransomware detection and data recovery techniques
S. Baek, Y. Jung, D. Mohaisen, S. Lee, and D. Nyang · 2020
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How to backdoor federated learning
E. Bagdasaryan, A. Veit, Y. Hua, D. Estrin, and V. Shmatikov · 2020
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Nvidia makes it easy to embed ai: The jetson nano packs a lot of machine-learning power into diy projects-[hands on]
S. Cass · 2020
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Security and privacy in iot: a survey
P. M. Chanal and M. S. Kakkasageri · 2020
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Main cloud security issues and threats in 2021, 2020
Checkpoint · 2020
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Local model poisoning attacks to { \{ Byzantine-Robust } \} federated learning
M. Fang, X. Cao, J. Jia, and N. Gong · 2020
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From pre-quantum to post-quantum iot security: A survey on quantum-resistant cryptosystems for the internet of things
T. M. Fernández-Caramés · 2020
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Adversarial attack against lstm-based ddos intrusion detection system
W. Huang, X. Peng, Z. Shi, and Y. Ma · 2020
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The heartbleed bug, 2020
S. Inc · 2020
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Real vulnerabilities in partial reconfigurable design cycles; case study for implementation of hardware security modules
H. Jafarzadeh and A. Jahanian · 2020
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Energy attacks on mobile devices
A. Kundu, Z. Lin, and J. Hammond · 2020
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Keystone: An open framework for architecting trusted execution environments
D. Lee, D. Kohlbrenner, S. Shinde, K. Asanović, and D. Song · 2020
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Everything old is new again: Binary security of { \{ WebAssembly } \}
D. Lehmann, J. Kinder, and M. Pradel · 2020
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Self-recovery service securing edge server in iot network against ransomware attack
I.-S. Lei, T. Su-Kit, I.-K. Chao, and R. Tse · 2020
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Integrating consortium blockchain into edge server to defense against ransomware attack
I.-S. Lei, S.-K. Tang, and R. Tse · 2020
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Stolen memories: Leveraging model memorization for calibrated { \{ White-Box } \} membership inference
K. Leino and M. Fredrikson · 2020
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Federated learning: Challenges, methods, and future directions
T. Li, A. K. Sahu, A. Talwalkar, and V. Smith · 2020
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Y. Li, B. Wu, Y. Jiang, Z. Li, and S.-T. Xia · 2020
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Mcunet: Tiny deep learning on iot devices
J. Lin, W.-M. Chen, Y. Lin, C. Gan, S. Han, et al · 2020
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Adversarial machine learning based partial-model attack in iot
Z. Luo, S. Zhao, Z. Lu, Y. E. Sagduyu, and J. Xu · 2020
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Evaluating webassembly enabled serverless approach for edge computing
P. Mendki · 2020
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Edge machine learning for ai-enabled iot devices: A review
M. Merenda, C. Porcaro, and D. Iero · 2020
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Darknetz: towards model privacy at the edge using trusted execution environments
F. Mo, A. S. Shamsabadi, K. Katevas, S. Demetriou, I. Leontiadis, A. Cavallaro, and H. Haddadi · 2020
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Improving data quality of low-cost iot sensors in environmental monitoring networks using data fusion and machine learning approach
N. U. Okafor, Y. Alghorani, and D. T. Delaney · 2020
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Power side-channel attack analysis: A review of 20 years of study for the layman
M. Randolph and W. Diehl · 2020
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Strengthening vm isolation with integrity protection and more
A. SEV-SNP · 2020
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Generative adversarial network in the air: Deep adversarial learning for wireless signal spoofing
Y. Shi, K. Davaslioglu, and Y. E. Sagduyu · 2020
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Byzantine-resilient secure federated learning
J. So, B. Güler, and A. S. Avestimehr · 2020
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Re-identification attack to privacy-preserving data analysis with noisy sample-mean
D. Su, H. T. Huynh, Z. Chen, Y. Lu, and W. Lu · 2020
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An embarrassingly simple approach for trojan attack in deep neural networks
R. Tang, M. Du, N. Liu, F. Yang, and X. Hu · 2020
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Data poisoning attacks against federated learning systems
V. Tolpegin, S. Truex, M. E. Gursoy, and L. Liu · 2020
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Analyzing the attack landscape of zigbee-enabled iot systems and reinstating users’ privacy
W. Wang, F. Cicala, S. R. Hussain, E. Bertino, and N. Li · 2020
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Wasmachine: Bring iot up to speed with a webassembly os
E. Wen and G. Weber · 2020
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Faster authenticated key agreement with perfect forward secrecy for industrial internet-of-things
Z. Yang, J. He, Y. Tian, and J. Zhou · 2020
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Building control box attached monitor based color grid recognition methods for user access authentication
S. H. Yoon, K. S. Lee, J. S. Cha, T. Khudaybergenov, M. S. Kim, D. G. Woo, and J. U. Kim · 2020
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Stackvault: Protection from untrusted functions
Q. Zhang, Z. Sura, A. Kundu, G. Su, A. Iyengar, and L. Liu · 2020
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Person re-identification attack on wearable sensing, 2021
M. A. U. Alam · 2021
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Zigbee document 05-3474-21
Z. Alliance · 2021
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Smart at what cost? characterising mobile deep neural networks in the wild
M. Almeida, S. Laskaridis, A. Mehrotra, L. Dudziak, I. Leontiadis, and N. D. Lane · 2021
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Certificate revocation list (crl), 2021
R. Awati and M. Cobb · 2021
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J. Blessing, M. A. Specter, and D. J. Weitzner · 2021
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Context-dependent anomaly detection for low altitude traffic surveillance
I. Bozcan and E. Kayacan · 2021
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Cryscanner: Finding cryptographic libraries misuse
A. Choudhari, S. Guilley, and K. Karray · 2021
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Darknight: An accelerated framework for privacy and integrity preserving deep learning using trusted hardware
H. Hashemi, Y. Wang, and M. Annavaram · 2021
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Model extraction and adversarial transferability, your bert is vulnerable!
X. He, L. Lyu, Q. Xu, and L. Sun · 2021
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Challenges and approaches for mitigating byzantine attacks in federated learning
S. Hu, J. Lu, W. Wan, and L. Y. Zhang · 2021
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Can i reach you? do i need to? new semantics in security policy specification and testing
C. Katsis, F. Cicala, D. Thomsen, N. Ringo, and E. Bertino · 2021
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Timing-based side-channel attack and mitigation on pcie connected distributed embedded systems
S. A. Khaliq, U. Ali, and O. Khan · 2021
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Porting rt-thread to annikasoc
Z. Li, J. Li, Y. Zhang, J. Zhou, and Z. Guo · 2021
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Byzantine resistant secure blockchained federated learning at the edge
Z. Li, H. Yu, T. Zhou, L. Luo, M. Fan, Z. Xu, and G. Sun · 2021
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A survey on bias and fairness in machine learning
N. Mehrabi, F. Morstatter, N. Saxena, K. Lerman, and A. Galstyan · 2021
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Ppfl: privacy-preserving federated learning with trusted execution environments
F. Mo, H. Haddadi, K. Katevas, E. Marin, D. Perino, and N. Kourtellis · 2021
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A survey on security and privacy of federated learning
V. Mothukuri, R. M. Parizi, S. Pouriyeh, Y. Huang, A. Dehghantanha, and G. Srivastava · 2021
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Edgedancer: Secure mobile webassembly services on the edge
M. Nieke, L. Almstedt, and R. Kapitza · 2021
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Side-channel attack on rainbow post-quantum signature
D. Pokorný, P. Socha, and M. Novotný · 2021
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Large scale firmware analysis for open source components, hard coding and weak passwords
S. Quanjiang, S. Yan, Y. Xiaohu, L. Tinghui, H. Daojing, and Y. Guisong · 2021
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Remote attackers can now reach protected network devices via nat slipstreaming, Jan. 2021
T. Seals · 2021
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On the robustness of backdoor-based watermarking in deep neural networks
M. Shafieinejad, N. Lukas, J. Wang, X. Li, and F. Kerschbaum · 2021
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Manipulating the byzantine: Optimizing model poisoning attacks and defenses for federated learning
V. Shejwalkar and A. Houmansadr · 2021
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Mind your weight (s): A large-scale study on insufficient machine learning model protection in mobile apps
Z. Sun, R. Sun, L. Lu, and A. Mislove · 2021
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Accessed: 2022-05-22
The 2021 tls telemetry report · 2022
Closest in time.
https://developer.apple.com/documentation/coreml
Core ml · 2022
Closest in time.
https://cwe.mitre.org/data/definitions/1240.html
Cwe-1240: Use of a cryptographic primitive with a risky implementation · 2022
Closest in time.
https://cwe.mitre.org/data/definitions/369.html
Cwe-369: Divide by zero · 2022
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https://safeatlast.co/blog/amazon-alexa-statistics/
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