Page 183 - Trust in ICT 2017

Trust in ICT 3

• Complexity of ICT infrastructures

 A numerous number of ICT resources: Risks threaten us to cope with complexity of interactions
and mechanisms of ICT infrastructures. The access of a large number of ICT resources causes
irreparable damages and creates unpredictable dangers. It is essential to make ICT resources
accessible to all the people with promises but with unknown dangers.
 Complexity of network operation: There are a lot of algorithms for network resource
optimization including efficient routing, congestion avoidance, and guaranteeing Quality of
Service (QoS)/Quality of Experience (QoE). When the unpredictable situations are happened in
a network, the out-of-service possibility is increasing. Natural disaster and distributed denial-
of-service (DDoS) attacks are also a part of risks. While network control functions can arrange
the by-pass or de-tour route to cope with overflowed traffic, the unexpected side effects like
traffic fluctuation and domino effect may bring additional risks. To increase network
survivability during network operation, networking protocols and OAM&P (Operations,
Administrations, Maintenance, and Provisioning) functions should be re-designed to be
trustworthy. Moreover, when a network infrastructure includes a cloud platform with large
volume of storage and processing capabilities, network instability is not coming only from traffic
congestion. The operation of the cloud platform and high level applications are additional
harmful sources to increase network risks. The existing security functions including firewall and
Deep Packet Inspection (DPI) may be replaced to provide the certain level of trust, through the
implementation by a trust gateway system and trust-guaranteed network OAM functions.

 Data, information and knowledge process: Since future ICT infrastructures should provide
data, information and knowledge process, the trust provisioning is quite essential. Data
integrity refers to maintain and assure the accuracy and consistency of data. The failure of data
aggregation is coming from any unintended changes to data as the results of storage, retrieval
and processing operation for further information and knowledge. For example, if data stored in
a cloud platform are shared by anonymous users, there may be a possibility to happen
undesirable situations. With a certain level of trust, data delivery and cognitive data,
information, knowledge and wisdom (DIKW)1 process may be effective and meaningful.

 Complexity of convergence services and applications: ICT based services and applications will
continue to be heterogeneous, and this may lead to increase a number of convergence services
that cover multiple service domains. Especially, in Internet of Things (IoT) and CPS
environments, people, platforms and devices will be highly inter-connected by a dynamic
network of networks and operated in heterogeneous environments. These kinds of highly
connected environments increase the complexity of services and applications (which consume
data and information from connected sensors, devices, etc.), and the unknown potential risks
may be incurred due to complex interactions. As ICT based applications and services will scale
over multiple domains and involves multiple stakeholders, methods for assessing trust are
needed to enable the users to have confidence to these services and applications.

5.3 Trust for future ICT infrastructures and services

For evolving toward knowledge societies, ICT will be mainly used for the creation, dissemination and
utilization of knowledge in an open and collaborative manner. Although recent advances in ICT have brought
changes to our everyday lives, various problems exist due to the lack of trust. The large scale collection and
analysis of data from sensors and devices in physical spaces imposes difficult issues, ranging from the risks of
unanticipated uses of consumer data to the potential discrimination enabled by data analytics and the
insights offered into the movements, interests and activities of an individual. If knowledge is exploited for

DIKW (Data, Information, Knowledge and Wisdom): This refers loosely to a class of models for representing purported structural
1
and/or functional relationships between data, information, knowledge, and wisdom. “Typically information is defined in terms of
data, knowledge in terms of information, and wisdom in terms of knowledge”. (Source:
https://en.wikipedia.org/wiki/DIKW_Pyramid)

175