scispace - formally typeset
Open AccessJournal ArticleDOI

Security Threats and Artificial Intelligence Based Countermeasures for Internet of Things Networks: A Comprehensive Survey

TLDR
In this paper, a comprehensive layer-wise survey on IoT security threats, and the AI-based security models to impede security threats is presented, and open challenges and future research directions are addressed for the safeguard of the IoT network.
Abstract
The Internet of Things (IoT) has emerged as a technology capable of connecting heterogeneous nodes/objects, such as people, devices, infrastructure, and makes our daily lives simpler, safer, and fruitful. Being part of a large network of heterogeneous devices, these nodes are typically resource-constrained and became the weakest link to the cyber attacker. Classical encryption techniques have been employed to ensure the data security of the IoT network. However, high-level encryption techniques cannot be employed in IoT devices due to the limitation of resources. In addition, node security is still a challenge for network engineers. Thus, we need to explore a complete solution for IoT networks that can ensure nodes and data security. The rule-based approaches and shallow and deep machine learning algorithms– branches of Artificial Intelligence (AI)– can be employed as countermeasures along with the existing network security protocols. This paper presented a comprehensive layer-wise survey on IoT security threats, and the AI-based security models to impede security threats. Finally, open challenges and future research directions are addressed for the safeguard of the IoT network.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

A survey on security in internet of things with a focus on the impact of emerging technologies

TL;DR: In this paper , the authors introduce a comprehensive study on IoT security threats and solutions and outline how emerging technologies such as machine learning and blockchain are integrated in IoT, challenges resulted from this integration, and potential solutions to these challenges.
Journal ArticleDOI

Static Analysis of Information Systems for IoT Cyber Security: A Survey of Machine Learning Approaches

TL;DR: A hypothesis to this end is posed that assumes the applicability of machine-learning solutions for IoT system static analysis, and a proposal of an intelligent framework concept for the static analysis of IoT systems is proposed.
Journal ArticleDOI

SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals

TL;DR: SANTIA as discussed by the authors is a toolbox that applies neural network-based machine learning techniques to label and train models to detect artifacts from the invasive neuronal signals known as local field potentials.
Journal ArticleDOI

Healthcare Data Security Using IoT Sensors Based on Random Hashing Mechanism

TL;DR: An AI-based intelligent feature learning mechanism named Probabilistic Super Learning- (PSL-) Random Hashing (RH) for improving the security of healthcare data stored in IoT-cloud and reducing the cost of IoT sensors by implementing the proposed learning model.
Journal ArticleDOI

Collaborative Sensing in Internet of Things: A Comprehensive Survey

TL;DR: This article comprehensively survey the sensing mechanism, collaboration and applications in the context of IoT, and highlights that sensing application is coupled with sensing mechanism and sensing collaboration, and discusses promising sensing applications.
References
More filters
Proceedings ArticleDOI

Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures

TL;DR: A new class of model inversion attack is developed that exploits confidence values revealed along with predictions and is able to estimate whether a respondent in a lifestyle survey admitted to cheating on their significant other and recover recognizable images of people's faces given only their name.
Journal ArticleDOI

A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications

TL;DR: The relationship between cyber-physical systems and IoT, both of which play important roles in realizing an intelligent cyber- physical world, are explored and existing architectures, enabling technologies, and security and privacy issues in IoT are presented to enhance the understanding of the state of the art IoT development.
Book ChapterDOI

Evasion attacks against machine learning at test time

TL;DR: This work presents a simple but effective gradient-based approach that can be exploited to systematically assess the security of several, widely-used classification algorithms against evasion attacks.
Posted Content

Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

TL;DR: New transferability attacks between previously unexplored (substitute, victim) pairs of machine learning model classes, most notably SVMs and decision trees are introduced.
Journal ArticleDOI

Security for the Internet of Things: A Survey of Existing Protocols and Open Research Issues

TL;DR: This survey analyzes existing protocols and mechanisms to secure communications in the IoT, as well as open research issues and analyzes the open challenges and strategies for future research work in the area.
Related Papers (5)