Security and Privacy for Cloud-Based IoT: Challenges

By Jun Zhou, Zhenfu Cao, Xiaolei Dong, Athanasios V. Vasilakos. IEEE Communications Magazine, 2017

536 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/caccd12f92967eee019bea8c45e34bda62a1c2d8

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Citations in the corpus

Toward Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions (2018, background): “Compared with the conventional communication systems, IoT systems are usually more vulnerable to various security issues including intrusions, spoofing attacks, jamming, malwares, eavesdropping, Denial of Service (DoS) attacks and distributed DoS [27].”
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security (2018, background): “The injected malicious software has a dynamic nature, and new types of attacks are constantly introduced to violate IoT components remarkably because IoT systems have a naturally large, well-connected surface [22], [88].”
IoT Security Techniques Based on Machine Learning: How Do IoT Devices Use AI to Enhance Security? (2018, background): “It’s generally prohibitive for IoT devices with restricted computation, memory, radio bandwidth, and battery resources to execute computational-intensive and latency-sensitive security tasks, especially under heavy data streams [7].”
Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks (2017, background): “For example, drones and connected vehicles [9]–[12] will place autonomy at the heart of the IoT.”
Advanced lightweight encryption algorithms for IoT devices: survey, challenges and solutions (2017, unknown): “In addition, IoT utilizes the cloud computing concept, which has many security issues and challenges (Sajid et al. 2016; Singh et al. 2016a, b, c; Kar and Mishra 2016; Zhou et al. 2017).”
A Survey on 5G Networks for the Internet of Things: Communication Technologies and Challenges (2018, background): “forward and backward security should be supported for effective deployment of IoT use cases [60].”
Survey of Fog Computing: Fundamental, Network Applications, and Research Challenges (2018, unknown): “However, as services [178]–[180] with”
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial (2017, background): “etworks must be able to deliver ultra-reliable, low-latency communication [5]–[8], that is adaptive, in real-time to a rich and dynamic IoT environment. For example, drones and connected vehicles [9]–[12] will place autonomy at the heart of the IoT. This, in turn, will necessitate the deployment of ”
Applications of Blockchains in the Internet of Things: A Comprehensive Survey (2019, background): “This data may be collected without any explicit user consent and exposed to third parties when shared by supporting IoT platforms, depriving users about control on which data and to whom his personal data is given access [72].”
Blockchain for Internet of Things: A Survey (2019, methodology): “However, uploading the confidential IoT data to the third-party cloud servers may also compromise the vulnerable privacy of IoT [15].”
IoT security: Review, blockchain solutions, and open challenges (2017, background): “Privacy violation on cloud-based IoT Different attacks which mayviolate identity and locationprivacymaybe launchedon cloud or delay tolerant network based IoT [20,59].”
Federated Learning in Smart City Sensing: Challenges and Opportunities (2020, unknown): “Furthermore, by using user devices for sensing, the users are exposed to potential privacy leaks [35–39].”
Machine Learning Based Solutions for Security of Internet of Things (IoT): A Survey (2020, background): “devices such as financial loss, power dissipation, degradation of the wireless network performance [6], [51], [52] (see Fig.”
Blockchain for 5G and Beyond Networks: A State of the Art Survey (2019, background): “Indeed, in the 5G era, the massive data traffic outsourced from IoT devices to the cloud has brought about a series of new security challenges, mainly including data availability, data privacy management, and data integrity [60].”