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Towards Security Threats of Deep Learning Systems: A Survey [article]

Yingzhe He and Guozhu Meng and Kai Chen and Xingbo Hu and Jinwen He
2020 arXiv   pre-print
In order to unveil the security weaknesses and aid in the development of a robust deep learning system, we undertake an investigation on attacks towards deep learning, and analyze these attacks to conclude  ...  However, deep learning systems are suffering several inherent weaknesses, which can threaten the security of learning models. Deep learning's wide use further magnifies the impact and consequences.  ...  RELATED WORK There is a line of works that survey and evaluate attacks toward machine learning or deep learning.  ... 
arXiv:1911.12562v2 fatcat:m3lyece44jgdbp6rlcpj6dz2gm

A Survey on Trustworthy Recommender Systems [article]

Yingqiang Ge, Shuchang Liu, Zuohui Fu, Juntao Tan, Zelong Li, Shuyuan Xu, Yunqi Li, Yikun Xian, Yongfeng Zhang
2022 arXiv   pre-print
Through this survey, we hope to deliver readers with a comprehensive view of the research area and raise attention to the community about the importance, existing research achievements, and future research  ...  due to non-transparency, unfair treatment of different consumers, or producers, privacy concerns due to extensive use of user's private data for personalization, just to name a few.  ...  As a crucial part of the modern paradigm AI, deep neural networks have increasingly contributed to the development of most state-of-the-art machine learning systems.  ... 
arXiv:2207.12515v1 fatcat:lsnuwdtl5rboznmhhux2n5y5om

Differential Privacy Techniques for Cyber Physical Systems: A Survey [article]

Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen
2019 arXiv   pre-print
In particular, we survey the application and implementation of differential privacy in four major applications of CPSs named as energy systems, transportation systems, healthcare and medical systems, and  ...  Modern cyber physical systems (CPSs) has widely being used in our daily lives because of development of information and communication technologies (ICT).With the provision of CPSs, the security and privacy  ...  deep learning algorithms with differential privacy is turning out to be a feasible solution.  ... 
arXiv:1812.02282v3 fatcat:bnapnprldnaetjnjedz473lrme

Elderly Fall Detection Systems: A Literature Survey

Xueyi Wang, Joshua Ellul, George Azzopardi
2020 Frontiers in Robotics and AI  
We approach this survey from different perspectives, including data collection, data transmission, sensor fusion, data analysis, security, and privacy.  ...  In this paper, we provide a literature survey of work conducted on elderly fall detection using sensor networks and IoT.  ...  SECURITY AND PRIVACY Because data generated by autonomous monitoring systems are security-critical and privacy-sensitive, there is an urgent demand to protect user's privacy and prevent these systems from  ... 
doi:10.3389/frobt.2020.00071 pmid:33501238 pmcid:PMC7805655 fatcat:iredkfo5qra7pbmdkjy4fsftya

Machine Learning Systems for Intelligent Services in the IoT: A Survey [article]

Wiebke Toussaint, Aaron Yi Ding
2020 arXiv   pre-print
With a multi-layered framework to classify and illuminate system design choices, this survey exposes fundamental concerns of developing and deploying ML systems in the rising cloud-edge-device continuum  ...  Machine learning (ML) technologies are emerging in the Internet of Things (IoT) to provision intelligent services.  ...  Machine learning systems are offering new attack surfaces that jeopardise system security. Poisoning and evasion attacks in particular exploit the dependence of machine learning systems on data.  ... 
arXiv:2006.04950v3 fatcat:xrjcioqkrrhpvgmwmutiajgfbe

System Optimization in Synchronous Federated Training: A Survey [article]

Zhifeng Jiang, Wei Wang
2021 arXiv   pre-print
Given a sufficient level of privacy guarantees, the practicality of an FL system mainly depends on its time-to-accuracy performance during the training process.  ...  The unprecedented demand for collaborative machine learning in a privacy-preserving manner gives rise to a novel machine learning paradigm called federated learning (FL).  ...  As FL features strict compliance to privacy regulations as opposed to traditional distributed learning, many survey efforts are directed to the unique challenges such as enforcing data privacy and system  ... 
arXiv:2109.03999v2 fatcat:oxmq44iuo5eexbjtq7xdj3quq4

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection [article]

Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He
2021 arXiv   pre-print
In this survey, we conduct a comprehensive review on federated learning systems.  ...  Similar to deep learning systems such as PyTorch and TensorFlow that boost the development of deep learning, federated learning systems (FLSs) are equivalently important, and face challenges from various  ...  Acknowledgement This work is supported by a MoE AcRF Tier 1 grant (T1 251RES1824), an SenseTime Young Scholars Research Fund, and a MOE Tier 2 grant (MOE2017-T2-1-122) in Singapore.  ... 
arXiv:1907.09693v6 fatcat:d3l2l664mjdfrjgyok43pfxnvq

Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges [article]

Huaming Chen, M. Ali Babar
2022 arXiv   pre-print
Overall, we present a holistic review regarding the security for MLBSS, which covers a systematic understanding from a structure review of three distinct aspects in terms of security threats.  ...  Moreover, it provides a thorough state-of-the-practice for MLBSS secure development.  ...  ACKNOWLEDGMENT The work has been supported by the Cyber Security Research Centre Limited whose activities are partially funded by the Australian Government's Cooperative Research Centres Programme  ... 
arXiv:2201.04736v1 fatcat:5g3b2mbapjgelltogqiubv5kda

A Survey on Edge Computing Systems and Tools

Fang Liu, Guoming Tang, Youhuizi Li, Zhiping Cai, Xingzhou Zhang, Tongqing Zhou
2019 Proceedings of the IEEE  
A comparison of open source tools is presented according to their applicability. Finally, we highlight energy efficiency and deep learning optimization of edge computing systems.  ...  To explore new research opportunities and assist users in selecting suitable edge computing systems for specific applications, this survey paper provides a comprehensive overview of the existing edge computing  ...  of information and functionalities inside a sea zone, and iii) a shield protecting security and privacy of the sea zone.  ... 
doi:10.1109/jproc.2019.2920341 fatcat:rocspx5ziffblfzaye2xhebe3e

Demystifying In-Vehicle Intrusion Detection Systems: A Survey of Surveys and a Meta-Taxonomy

Georgios Karopoulos, Georgios Kambourakis, Efstratios Chatzoglou, José L. Hernández-Ramos, Vasileios Kouliaridis
2022 Electronics  
This work concentrates on in-vehicle IDS with the goal to deliver a fourfold comprehensive survey of surveys on this topic.  ...  To our knowledge, this work provides the first wholemeal survey on in-vehicle IDS, and it is therefore anticipated to serve as a groundwork and point of reference for multiple stakeholders at varying levels  ...  A machine-learning IDS detects anomalous behavior using machine learning (ML) algorithms, whereas physical characteristics-based systems work at the physical layer of CAN and use the signals and voltage  ... 
doi:10.3390/electronics11071072 fatcat:e4nia2dcuvfwzixvdf5sfq6nqq

Medical cyber-physical systems: A survey

Nilanjan Dey, Amira S. Ashour, Fuqian Shi, Simon James Fong, João Manuel R. S. Tavares
2018 Journal of medical systems  
The MCPS design faces numerous challenges, including inoperability, security/privacy, and high assurance in the system software.  ...  Medical cyber-physical systems (MCPS) are healthcare critical integration of a network of medical devices.  ...  Conflict of Interest: We are the authors confirm that no conflict of interest.  ... 
doi:10.1007/s10916-018-0921-x pmid:29525900 fatcat:wctzw4ilafgwjm5yrk53sl4ldy

Reinforcement Learning for Intelligent Healthcare Systems: A Comprehensive Survey [article]

Alaa Awad Abdellatif, Naram Mhaisen, Zina Chkirbene, Amr Mohamed, Aiman Erbad, Mohsen Guizani
2021 arXiv   pre-print
After that, we provide a deep literature review for the applications of RL in I-health systems.  ...  Thus, we conduct in this paper a comprehensive survey of the recent models and techniques of RL that have been developed/used for supporting Intelligent-healthcare (I-health) systems.  ...  ACKNOWLEDGMENT This work was made possible by NPRP grant # NPRP12S-0305-190231 from the Qatar National Research Fund (a member of Qatar Foundation).  ... 
arXiv:2108.04087v1 fatcat:ifdpiqwunrawbmpfy6ftjk43g4

A Survey on Blockchain-based IoMT Systems: Towards Scalability

Amirhossein Adavoudi Jolfaei, Seyed Farhad Aghili, Dave Singelee
2021 IEEE Access  
Survey on Blockchain-based IoMT Systems: Towards Scalability DR.  ...  Also, the paper [59] proposed a novel blockchain-based deep learning for secure image transmission.  ... 
doi:10.1109/access.2021.3117662 fatcat:oaw35at76vhqhf7co3sf5ijb34

A Survey of Analysis Methods for Security and Safety verification in IoT Systems [article]

Lobna Abuserrieh, Manar H. Alalfi
2022 arXiv   pre-print
In this paper, we study the problem of security and safety verification of IoT systems. We survey techniques that utilize program analysis to verify IoT applications' security and safety properties.  ...  Moreover, we discuss the main challenges considered in the surveyed work and potential solutions that could be adopted to ensure the security and safety of IoT systems.  ...  Deep Q learning is used to decide the best optimal actions concerning timing period and user goals, while agents are trained using a deep neural network (DNN).  ... 
arXiv:2203.01464v1 fatcat:4napk3wzlrhbrcfycvtaadi7ee

Privacy in Deep Learning: A Survey [article]

Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh
2020 arXiv   pre-print
In this survey, we review the privacy concerns brought by deep learning, and the mitigating techniques introduced to tackle these issues.  ...  The ever-growing advances of deep learning in many areas including vision, recommendation systems, natural language processing, etc., have led to the adoption of Deep Neural Networks (DNNs) in production  ...  [47] propose a new set of attacks to compromise the privacy of test-time inference queries, in collaborative deep learning systems where a DNN is split and distributed to different participants.  ... 
arXiv:2004.12254v5 fatcat:4w63htwzafhxxel2oq3z3pwwya
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