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The Internet of Things (IoT) is widely used as a
synonym for nearly every connected device. This makes it really
difficult to find the right kind of scientific publication for the
intended category of IoT. Conferences and other events for
IoT are confusing about the target group (consumer, enterprise,
industrial, etc.) and standardisation organisations suffer from
the same problem. To demonstrate these problems, this paper
shows the results of an analyses over IoT publications in different
research libraries. The number of results for IoT, consumer,
enterprise and industrial search queries were evaluated and a
manual study about 100 publications was done. According to
the research library or search engine, different results about
the distribution of consumer-, enterprise- and industrial- IoT
are visible. The comparison with the results of the manual
evaluation shows that some search queries do not show all desired
publications or that considerably more, unwanted results are
returned. Most researchers do not use the keywords right and
the exact category of IoT can only be accessed via the abstract.
This shows major problems with the use of the term IoT and its
minor limitations.
Increasing cyber-attacks on Internet of Things (IoT) environments are a growing problem of digitized households worldwide. The purpose of this study is to investigate how an intelligent Intrusion Detection System (iIDS) can provide more security in IoT networks with a novel architecture, combining
multiple classical and machine learning approaches. By combining classical security analysis methods and modern concepts of artificial intelligence, we increase the quality of attack detection and can therefore conduct dedicated attack suppression. The architectural image of the iIDS consists of different layers, which in parts achieve self-sufficient results. The results of
the different modules are calculated by means of statement variables and evaluation techniques adapted for the individual module elements and subsequently combined by limit value considerations. The architecture image combines approaches for the analysis and processing of IoT network traffic and
evaluates it to an aggregated score. From this result it can be determined whether the analyzed data indicates device misuse or attempted break-ins into the network. This study answers the questions whether a connection between classical and modern concepts for monitoring and analyzing IoT network traffic can be implemented meaningfully within a reliable architecture of an
iIDS.
Internet of Things (IoT) devices are critical to operate and maintain, because of their number and high connectivity.
A lot of security issues concern IoT devices and the networks they
are integrated. To help getting an overview of an IoT network,
the devices and the security, we propose a scoring system to get
a good impression of IT security. This system generates single
scores for each device, using features like encryption, update
behavior, etc. Furthermore, a summarized score for the whole
network is calculated, to show the status of the network security
in an easy way for the administrator. To enable the scoring
system, a precise list of the existing devices and their operating
status is necessary. To achieve this, we present an open standard
for the IoT Device IdentificAtion and RecoGnition (short IoTAG),
which requires that devices report, e.g., their name, an unique ID,
the firmware version and the supported encryption. The proposed
standard is described in detail and an implementation guideline
is given in this paper. Additionally, information about how to
realize the serialization, the integrity and the communication
with IoTAG.
To ensure the secure operation of IoT devices in the
future, they must be continuously monitored. This starts with
an inventory of the devices, checking for a current software
version and extends to the encryption algorithms and active
services used. Based on this information, a security analysis and
rating of the whole network is possible. To solve this challenge
in the growing network environments, we present a proposal for
a standard. With the IoT Device IdentificAtion and RecoGnition
(IoTAG), each IoT device reports its current status to a central
location as required and provides information on security. This
information includes a unique ID, the exact device name, the
current software version, active services, cryptographic methods
used, etc. The information is signed to make misuse more difficult
and to ensure that the device can always be uniquely identified.
In this paper, we introduce IoTAG in detail and describe the
necessary requirements.