With the continuous development of distributed ledger and blockchain technologies, new use cases apart from cryptocurrencies have come into the spotlight. In this article, we evaluate whether an e-government service could be a suitable candidate for a blockchain transformation. We selected as a reference test system an existing cross-border e-government service that is used for supporting goods exchanges across the European Union. We show how such an indicative paradigm can be transformed into a blockchain system. In order to do so, we deployed it in an emulated architecture for evaluating its performance under various realistic conditions. Our results show that the deployed system is able to meet the requirements, both in terms of throughput and transaction speed. Moreover, it shows clear advantages in terms of usability and synchronization between all entities.

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Demand response (DR) services have the potential to enable large penetration of renewable energy by adjusting load consumption, thus providing balancing support to the grid. The success of such load flexibility provided by industry, communities, or prosumers and its integration in electricity markets, will depend on a redesign and adaptation of the current interactions between participants. New challenges are, however, bound to appear with the large scale contribution of smaller assets to flexibility, including, among others, the dispatch coordination, the validation of delivery of the DR provision, and the corresponding settlement of contracts, while assuring secured data access among interested parties. In this study we applied distributed ledger (DLT)/blockchain technology to securely track DR provision, focusing on the validation aspect, assuring data integrity, origin, fast registry, and sharing within a permissioned system, between all relevant parties (including transmission system operators (TSOs), aggregators, distribution system operators (DSOs), balance responsible parties (BRP), and prosumers). We propose a framework for DR registry and implemented it as a proof of concept on Hyperledger Fabric, using real assets in a laboratory environment, in order to study its feasibility and performance. The lab set up includes a 450 kW energy storage system, scheduled to provide DR services, upon a system operator request and the corresponding validations and verifications are done, followed by the publication on a blockchain. Results show the end to end execution time remained below 1 s, when below 32 requests/sec. The smart contract memory utilization did not surpass 1% for both active and passive nodes and the peer CPU utilization, remained below 5% in all cases simulated (3, 10, and 28 nodes). Smart Contract CPU utilization remained stable, below 1% in all cases. The performance of the implementation showed scalable results, which enables real world adoption of DLT in supporting the development of flexibility markets, with the advantages of blockchain technology.

Modern society depends on the smooth functioning of critical infrastructures which provide services of fundamental importance, e.g. telecommunications and water supply. These infrastructures may suffer from faults/malfunctions coming e.g. from aging effects or they may even comprise targets of terrorist attacks. Prompt detection and accommodation of these situations is of paramount significance. This paper proposes a probabilistic modeling scheme for analyzing malicious events appearing in interdependent critical infrastructures. The proposed scheme is based on modeling the relationship between datastreams coming from two network nodes by means of a hidden Markov model (HMM) trained on the parameters of linear time-invariant dynamic systems which estimate the relationships existing among the specific nodes over consecutive time windows. Our study includes an energy network (IEEE 30 model bus) operated via a telecommunications infrastructure. The relationships among the elements of the network of infrastructures are represented by an HMM and the novel data is categorized according to its distance (computed in the probabilistic space) from the training ones. We considered two types of cyber-attacks (denial of service and integrity/replay) and report encouraging results in terms of false positive rate, false negative rate and detection delay

Voice over IP (VoIP) is a key enabling technology, which provides new ways of communication. VoIP technologies take advantage of existing data networks to provide inexpensive voice communications worldwide as a promising alternative to the traditional telephone service. At the same time, VoIP provides the means for transmitting bulk unsolicited calls, namely SPam over Internet Telephony (SPIT). SPIT is, up to a given extend, similar to email spam. However, it is expected to be more frustrating because of the real-time processing requirements of voice calls. In this paper we set the foundations of an adaptive approach that handles SPIT through a policy-based management approach (aSPM). aSPM incorporates a set of rules for SPIT attacks detections, together with appropriate actions and controls that should be enforced so as to counter these attacks. Furthermore, the policy is formally described through an XML schema, which refers to both, the attack detection rules, and the corresponding defense actions.