Today is the era of the Internet of Things (IoT). The recent advances in hardware and information technology have accelerated the deployment of billions of interconnected, smart and adaptive devices in critical infrastructures like health, transportation, environmental control, and home automation. Transferring data over a network without requiring any kind of human-to-computer or human-to-human interaction, brings reliability and convenience to consumers, but also opens a new world of opportunity for intruders, and introduces a whole set of unique and complicated questions to the field of Digital Forensics. Although IoT data could be a rich source of evidence, forensics professionals cope with diverse problems, starting from the huge variety of IoT devices and non-standard formats, to the multitenant cloud infrastructure and the resulting multi-jurisdictional litigations. A further challenge is the end-to-end encryption which represents a trade-off between users' right to privacy and the success of the forensics investigation. Due to its volatile nature, digital evidence has to be acquired and analyzed using validated tools and techniques that ensure the maintenance of the Chain of Custody. Therefore, the purpose of this paper is to identify and discuss the main issues involved in the complex process of IoT-based investigations, particularly all legal, privacy and cloud security challenges. Furthermore, this work provides an overview of the past and current theoretical models in the digital forensics science. Special attention is paid to frameworks that aim to extract data in a privacy-preserving manner or secure the evidence integrity using decentralized blockchain-based solutions. In addition, the present paper addresses the ongoing Forensics-as-a-Service (FaaS) paradigm, as well as some promising cross-cutting data reduction and forensics intelligence techniques. Finally, several other research trends and open issues are presented, with emphasis on the need for proactive Forensics Readiness strategies and generally agreed-upon standards.

Network Functions Virtualization (NFV) is a concept, which has attracted significant attention as a promising approach towards the virtualization/“softwarisation” of network infrastructures. With the aim of promoting NFV, this paper outlines an integrated architecture, designed and developed within the context of the EU FP7 T-NOVA project, which allows network operators not only to deploy virtualized Network Functions (NFs) for their own needs, but also to offer them to their customers, as value-added services (Network Functions as-a-Service, NFaaS). Virtual network appliances (gateways, proxies, firewalls, transcoders, analyzers etc.) can be provided on-demand as-a-Service, eliminating the need to acquire, install and maintain specialized hardware at customers' premises. A “NFV Marketplace” is also introduced, where network services and functions created by a variety of developers can be published, acquired and instantiated on-demand

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Cognitive radio (CR) paradigm was introduced, towards addressing challenges,related with radio spectrum scarcity and increased needs for wireless networking services provision. In this direction, CR networks exploit novel networking architectures, as well as dynamic radio spectrum access techniques and methods, alleviating problems, regarding limited wireless networking resources and their inefficient usage/exploitation. CR terminals exploit innovative mechanisms to identify unused parts of radio spectrum, such as TV white spaces (TVWS) in ultra-high frequency/ frequency bands following an interference-free opportunistic manner. However, introduction of CR networks creates new challenges that are highly related to the fluctuation of TVWS, as they vary over time and location, as well as issues related to diverse Quality of Service requirements. In this context, this paper proposes two radio resource management (RRM) algorithms, enabling for the opportunistic exploitation of TVWS in a centralised CR networking architecture. Efficient administration of radio spectrum resources is achieved, by exploiting a novel RRM framework, adopted in a spectrum broker, which is in charge to effectively orchestrate the available wireless networking resources. Efficient RRM algorithms performance, as a matter of maximum-possible spectrum broker benefit and radio spectrum utilisation, as well as minimum-possible spectrum fragmentation is evaluated, by considering a fixed-price and an auction-based optimization approach. Experimental tests that were conducted under controlled simulation conditions, confirmed the validity of both RRM algorithms adopted in the proposed CR networking architecture, identifying fields for further research and experimentation.

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