Claims:1. Impact of (AI) - Artificial Intelligence in the (IoT)-Internet of Things cyber
security has stated that the numerous attacks covered in this research.
2. Impact of Artificial Intelligence in the Internet of Things (IoT) cybersecurity of
claim 1, wherein said that Because IoT have many attack, there are numerous
assaults on them.
3. Impact of Artificial Intelligence in the Internet of Things (IoT) cybersecurity of
claim 1, wherein said System protection against these assaults must be
effective.
4. Impact of Artificial Intelligence in the Internet of Things (IoT) cybersecurity of
claim 1, wherein said As the speed of attacks increase, experts are focusing in
artificial intelligence (AI) to protect these systems.
5. Impact of Artificial Intelligence in the Internet of Things (IoT) cybersecurity of
claim 1, wherein said that this article investigates how the Internet of Things
(IoT) and artificial intelligence (AI) have been utilized for criminal objectives , Description:Descriptions:
Since its inception in 2008, the Internet of Things (IoT) has grown
exponentially, and it is now a common part of daily life, with devices in many
homes and businesses. Although defining the Internet of Things (IoT) is
difficult, it is best described as a network of digital and analogue computing
devices that can exchange data with one another without the need for human
intervention. Such an interaction typically occurs between an IoT edge device
or application and an end user, and is frequently a mobile app that transfers
data and instructions to other IoT edge devices. The use of fringe devices to
communicate with and transmit data back to the hub device when performing
tasks.
It has been demonstrated that using the Internet of Things will provide higher
levels of security and interoperability than any other technology previously
used. IoT systems are vulnerable to cyber-attacks due to their numerous attack
surfaces, newness, and, as a result, the lack of security standards and laws.
Because IoTs are vulnerable to a wide range of cyberattack types, it is critical
to understand which components of the system are being attacked and what
results the attacker hopes to achieve. As a result, a significant amount of IoT
cybersecurity research has been conducted. Artificial Intelligence (AI)
technologies that focus on detecting unusual behaviour that could indicate an
ongoing attack can help to improve IoT system security. IoT hackers have an
advantage over cybersecurity experts because they only need to find a single
flaw to launch an attack. Cybercriminals are increasingly turning to artificial
intelligence to avoid the complex algorithms that detect unusual behaviour and
allow it to go undetected. Artificial intelligence (AI) The popularity of the
Internet of Things (IoT) is increasing, as is interest in artificial intelligence (AI).
This article delves deeply into the security threats and countermeasures
associated with Internet of Things (IoT) applications. Authentication,
authorization, resilience, and self-organization are all factors considered by the
authors when evaluating various Internet of Things solutions. Deep learning
models with high accuracy (97.16 percent) can detect DDoS attacks on IoT
(Internet of Things) and can be used to improve IoT cybersecurity (Internet of
Things). The authors of this article are testing a gateway device that can detect
irregularities in data coming from edge devices. This research report puts ANNs
to the test. The study's findings indicate that the proposed approach has the
potential to increase the security of IoT. The study propose an artificial
intelligence-based control technique for detecting and quantifying cyber attacks
on industrial IoT systems, as well as compensating for them. Using the Internet
of Things, the authors build a powerful omnipresent detection system as well
as a slew of offensive and defensive measures. They also tested their method
using datasets from MNIST, CIFAR-10, and SVHN. When the authors of this
article examine how artificial intelligence has recently evolved, they discover
that it is nearly self-sustaining as a result of the IoT. Finally, it investigates
methods for collecting and evaluating cybersecurity risks associated with
Internet of Things (IoT) devices in order to standardise these processes so that
IoT-related hazards can be identified and addressed more efficiently.
Three sections follow, each focusing on a different aspect of cybersecurity. The
final section delves deeply into cyberattacks on Internet of Things (IoT) devices
and provides guidance on how to use artificial intelligence to defend against
these attacks (AI). A secondary goal of this paper will be to assist those
interested in researching these hot-button issues by summarising and linking
to relevant publications that provide a variety of perspectives on the subject.
Conclusions:
With so many IoT systems, a wide range of threats may target them, and as IoT
usage grows, more will be discovered. In the fight against such threats, it is
critical to protect as effectively. Experts are looking to artificial intelligence to
intelligently and in real time secure these systems in response to an increase in
the volume and speed of cyberattacks. However, hackers frequently find ways
to circumvent artificial intelligence systems, which they may then use to
launch attacks on other machines. This paper examines popular tactics for
disrupting or compromising the Internet of Things and describes these attacks
in detail (IoT). Extensive examples are provided where appropriate to aid
comprehension. Because these models are frequently in the early stages of
R&D or are extremely difficult to implement, they are difficult to find in
commercial use. As crude as these models are, they show a lot of promise and
could become widely used threat detection systems in the future. In the context
of IoT systems, researchers are also investigating artificial intelligence (AI)
attack methods and countermeasures. As AI-enabled massive networks, such
as smart cities, mature, the frequency of these attacks will increase. This is the
result of a combination of the increasing reliance on AI in daily life and safety,
as well as the difficulties in safeguarding vast networks. The risks discussed in
this paper are graphically summarised, along with the most common or
suggested defences against each of them. The goal of this project is to provide
researchers and cybersecurity experts with a useful tool for investigating the
Internet of Things from the perspectives of cybersecurity and artificial
intelligence in order to protect Internet of Things systems. As a result, it strives
to raise awareness of the implications of new technology, as well as the ripple
effects that each of these careers will have on the others. This includes
redirecting the technology away from its intended application or using it as a
tool for future attacks. Using IoT and AI as examples, this paper discusses how
these technologies have been used for criminal purposes or how their flaws
have been exploited, assisting readers in understanding current risks and
cultivating future to prevent cyber-attacks from occurring