An approach to cross-domain situation-based context management and highly adaptive services in pervasive environments

The concept of context-awareness is widely used in mobile and pervasive computing to reduce explicit user input and customization through the increased use of implicit input. It is considered to be the corner stone technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of the user. This requires the applications to take advantage of the context in order to infer the user’s objective and relevant environmental features. However, context-awareness introduces various software engineering challenges such as the need to provide developers with middleware infrastructure to acquire the context information available in distributed domains, reasoning about contextual situations that span one or more domains, and providing tools to facilitate building context-aware adaptive services. The separation of concerns is a promising approach in the design of such applications where the core logic is designed and implemented separately from the context handling and adaptation logics. In this respect, the aim of this dissertation is to introduce a unified approach for developing such applications and software infrastructure for efficient context management that together address these software engineering challenges and facilitate the design and implementation tasks associated with such context-aware services. The approach is based around a set of new conceptual foundations, including a context modelling technique that describes context at different levels of abstraction, domain-based context management middleware architecture, cross-domain contextual situation recognition, and a generative mechanism for context-aware service adaptation.Prototype tool has been built as an implementation of the proposed unified approach. Case studies have been done to illustrate and evaluate the approach, in terms of its effectiveness and applicability in real-life application scenarios to provide users with personalized services

SklCoin: Toward a Scalable Proof-of-Stake and Collective Signature Based Consensus Protocol for Strong Consistency in Blockchain

The proof-of-work consensus protocol suffers from two main limitations: waste of energy and offering only probabilistic guarantees about the status of the blockchain. This paper introduces SklCoin, a new Byzantine consensus protocol and its corresponding software architecture. This protocol leverages two ideas: 1) the proof-of-stake concept to dynamically form stake proportionate consensus groups that represent block miners (stakeholders), and 2) scalable collective signing to efficiently commit transactions irreversibly. SklCoin has immediate finality characteristic where all miners instantly agree on the validity of blocks. In addition, SklCoin supports high transaction rate because of its fast miner election mechanis

TRUSTD: Combat Fake Content using Blockchain and Collective Signature Technologies

The growing trend of sharing news/contents, through social media platforms and the World Wide Web has been seen to impact our perception of the truth, altering our views about politics, economics, relationships, needs and wants. This is because of the growing spread of misinformation and disinformation intentionally or unintentionally by individuals and organizations. This trend has grave political, social, ethical, and privacy implications for society due to 1) the rapid developments in the field of Machine Learning (ML) and Deep Learning (DL) algorithms in creating realistic-looking yet fake digital content (such as text, images, and videos), 2) the ability to customize the content feeds and to create a polarized so-called "filter-bubbles" leveraging the availability of the big-data. Therefore, there is an ethical need to combat the flow of fake content. This paper attempts to resolve some of the aspects of this combat by presenting a high-level overview of TRUSTD, a blockchain and collective signature-based ecosystem to help content creators in getting their content backed by the community, and to help users judge on the credibility and correctness of these contents.Comment: arXiv admin note: text overlap with arXiv:1812.00315, arXiv:1807.06346, arXiv:1904.05386 by other author

Jabber-based cross-domain efficient and privacy-ensuring context management framework.

In pervasive environments, context-aware applications require a global knowledge of the context information distributed in different spatial domains in order to establish context-based interactions. Therefore, the design of distributed storage, retrieval, and dissemination mechanisms of context information across domains becomes vital. In such environments, we envision the necessity of collaboration between different context servers distributed in different domains; thus, the need for generic APIs and protocol allowing context information exchange between different entities: context servers, context providers, and context consumers. As a solution this paper proposes ubique, a distributed middleware for contextaware computing that allows applications to maintain domain-based context interests to access context information about users, places, events, and things - all made available by or brokered through the home domain server. This paper proposes also a new cross-domain protocol for context management which ensures the privacy and the efficiency of context information dissemination. It has been robustly built upon the Jabber protocol which is a widely adopted open protocol for instant messaging and is designed for near real-time communication. Simulation and experimentation results show that ubique framework well supports robust cross-domain context management and collaboratio

The Impact of Mobile DIS and Rank-Decreased Attacks in Internet of Things Networks

With a predicted 50 billion devices by the end of 2020, the Internet of things has grown exponentially in the last few years. This growth has seen an increasing demand for mobility support in low power and lossy sensor networks, a type of network characterized by several limitations in terms of their resources including CPU, memory and batter, causing manufactures to push products out to the market faster, without the necessary security features. IoT networks rely on the Routing Protocol for Low Power and Lossy Network (RPL) for communication, designed by the Internet Engineering Task Force (IETF). This protocol has been proven to be efficient in relation to the handling of routing in such constrained networks, However, research studies revealed that RPL was inherently designed for static networks, indicating poor handling of mobile or dynamic topologies which is worsen when introducing mobile attacker. In this paper, two IoT routing attacks are evaluated under a mobile attacker with the aim of providing a critical evaluation of the impact the attacks have on the network in comparison to the case with static attacker. The first attack is the Rank attack in which the attacker announces false routing information to its neighbour attracting them to forward their data via the attacker. The second attack is the DIS attack in which the attacker floods the network with DIS messages triggering them to reset their transmission timers and sending messages more frequently. The comparison were conducted in terms of average power consumption and also the packet delivery ratio (PDR). Based on the results collected from the simulations, it was established that when an attacking node is mobile, there’s an average increase of 36.6 in power consumption and a decrease of 14 for packet delivery ratios when compared to a static attacking node

Recognize contextual situation in pervasive environments using process mining techniques

Research in pervasive computing and ambience intelligence aims to enable users to interact with the environment in a context-aware way. To achieve this, a complex set of features describing different aspects of the environment has to be captured and processed; in other words situation-awareness is needed. This article notes uniquely three points when modelling situations. Firstly, unlike most existing approaches, context information history should be considered when modelling the situations. We argue here that the current state cannot be understood in isolation from the previous states. Secondly, in order to track user’s behaviour there is a need to consider the context information available in the different domains the user visits. Thirdly, to identify situations it can be problematic to define situation patterns and looking for an exact match as most of the approaches does. We found that the combination of the flexibility of the user behaviour and automated capture of context events provide a very effective solution for contextual situation recognition. In this article we first provide a formalization of the situation recognition problem and then we focus on the potential use of process mining techniques for measuring situation alignment, i.e., comparing the real situations of users with the expected situations. To this end, we propose two ways to create and/or maintain the fit between them: linear temporal logic (LTL) analysis and conformance testing. We evaluate the effectiveness of the framework using a third party published smart home dataset. Our experiments prove the effectiveness of applying the proposed approach to recognizing situations in the flow of context informatio

An approach to domain-based scalable context management architecture in pervasive environments

In pervasive environments, context management systems are expected to administrate large volume of contextual information that is captured from spatial to nonspatial elements. Research in context-aware computing produced a number of middleware systems for context management to intermediate the communications between applications and context providers. In particular, in pervasive environments, the design of distributed storage, retrieval and propagation mechanisms of context information across domains is vital. In this paper, we propose a domain-based approach to address the requirements of scalable distributed context management, cross-domain efficient context information dissemination and domainbased privacy policy enforcement. We propose infinitum, a middleware architecture that incorporates the management and communication benefits of the Google Wave Federation Protocol, while also taking advantage of the semantic and inference benefits of ontology-based context models. This architecture establishes a robust cross-domain scalable context management and collaboration framework, which has been implemented and evaluated in a real-life application of ‘‘SMART University’’ to support virtual team collaboration

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and improve overall organisational security. An organisation’s vulnerabilities to attacks might change over time. It is utterly important to find a balance among a current threat, the potential countermeasures, their consequences and costs, and the estimation of the overall risk that this provides to the organisation. For enhancing organisational security and automation, applying threat intelligence technology is critical for detecting, classifying, analysing, and sharing new cyberattack tactics. Trusted partner organisations can then share newly identified threats to improve their defensive capabilities against unknown attacks. On this basis, organisations can help reduce the risk of a cyberattack by providing access to past and current cybersecurity events through blockchain smart contracts and the Interplanetary File System (IPFS). The suggested combination of technologies can make organisational systems more reliable and secure, improving system automation and data quality. This paper outlines a privacy-preserving mechanism for threat information sharing in a trusted way. It proposes a reliable and secure architecture for data automation, quality, and traceability based on the Hyperledger Fabric private-permissioned distributed ledger technology and the MITRE ATT&CK threat intelligence framework. This methodology can also be applied to combat intellectual property theft and industrial espionage

Preface for CEUR Workshop Proceedings

Summary: There were 58 papers submitted for peer-review to this conference. Out of these, 13 papers were accepted for this volume, 6 as regular papers and 7 as short papers. ACM 2021 Algorithms, Computing and Mathematics Conference 2021 Proceedings of Algorithms, Computing and Mathematics Conference 2021 (ACM 2021) Chennai, India, August 19 - 20, 2021 (Later changed to Online due to COVID-19 Pandemic)