Applicability and Appropriateness of Distributed Ledgers Consensus Protocols in Public and Private Sectors: A Systematic Review

Advancement of consensus protocols in recent years has enabled distributed ledger technologies (DLTs) to find its application and value in sectors beyond cryptocurrencies. Here we reviewed 66 known consensus protocols and classified them into philosophical and architectural categories, also providing a visual representation. As a case study, we focus on the public sector and highlighted potential protocols. We have also listed these protocols against basic features and sector preference in a tabular format to facilitate selection. We argue that no protocol is a silver bullet, therefore should be selected carefully, considering the sector requirements and environment

Quality of Experience (QoE)-Aware Fast Coding Unit Size Selection for HEVC Intra-prediction

The exorbitant increase in the computational complexity of modern video coding standards, such as High Efficiency Video Coding (HEVC), is a compelling challenge for resource-constrained consumer electronic devices. For instance, the brute force evaluation of all possible combinations of available coding modes and quadtree-based coding structure in HEVC to determine the optimum set of coding parameters for a given content demand a substantial amount of computational and energy resources. Thus, the resource requirements for real time operation of HEVC has become a contributing factor towards the Quality of Experience (QoE) of the end users of emerging multimedia and future internet applications. In this context, this paper proposes a content-adaptive Coding Unit (CU) size selection algorithm for HEVC intra-prediction. The proposed algorithm builds content-specific weighted Support Vector Machine (SVM) models in real time during the encoding process, to provide an early estimate of CU size for a given content, avoiding the brute force evaluation of all possible coding mode combinations in HEVC. The experimental results demonstrate an average encoding time reduction of 52.38%, with an average Bjøntegaard Delta Bit Rate (BDBR) increase of 1.19% compared to the HM16.1 reference encoder. Furthermore, the perceptual visual quality assessments conducted through Video Quality Metric (VQM) show minimal visual quality impact on the reconstructed videos of the proposed algorithm compared to state-of-the-art approaches

Cost benefits of using machine learning features in NIDS for cyber security in UK small medium enterprises (SME)

Cyber security has made an impact and has challenged Small and Medium Enterprises (SMEs) in their approaches towards how they protect and secure data. With an increase in more wired and wireless connections and devices on SME networks, unpredictable malicious activities and interruptions have risen. Finding the harmony between the advancement of technology and costs has always been a balancing act particularly in convincing the finance directors of these SMEs to invest in capital towards their IT infrastructure. This paper looks at various devices that currently are in the market to detect intrusions and look at how these devices handle prevention strategies for SMEs in their working environment both at home and in the office, in terms of their credibility in handling zero-day attacks against the costs of achieving so. The experiment was set up during the 2020 pandemic referred to as COVID-19 when the world experienced an unprecedented event of large scale. The operational working environment of SMEs reflected the context when the UK went into lockdown. Pre-pandemic would have seen this experiment take full control within an operational office environment; however, COVID-19 times has pushed us into a corner to evaluate every aspect of cybersecurity from the office and keeping the data safe within the home environment. The devices chosen for this experiment were OpenSource such as SNORT and pfSense to detect activities within the home environment, and Cisco, a commercial device, set up within an SME network. All three devices operated in a live environment within the SME network structure with employees being both at home and in the office. All three devices were observed from the rules they displayed, their costs and machine learning techniques integrated within them. The results revealed these aspects to be important in how they identified zero-day attacks. The findings showed that OpenSource devices whilst free to download, required a high level of expertise in personnel to implement and embed machine learning rules into the business solution even for staff working from home. However, when using Cisco, the price reflected the buy-in into this expertise and Cisco’s mainframe network, to give up-to-date information on cyber-attacks. The requirements of the UK General Data Protection Regulations Act (GDPR) were also acknowledged as part of the broader framework of the study. Machine learning techniques such as anomaly-based intrusions did show better detection through a commercially subscription-based model for support from Cisco compared to that of the OpenSource model which required internal expertise in machine learning. A cost model was used to compare the outcome of SMEs’ decision making, in getting the right framework in place in securing their data. In conclusion, finding a balance between IT expertise and costs of products that are able to help SMEs protect and secure their data will benefit the SMEs from using a more intelligent controlled environment with applied machine learning techniques, and not compromising on costs.</p

Flexible Macroblock Ordering for Context-Aware Ultrasound Video Transmission over Mobile WiMAX

The most recent network technologies are enabling a variety of new applications, thanks to the provision of increased bandwidth and better management of Quality of Service. Nevertheless, telemedical services involving multimedia data are still lagging behind, due to the concern of the end users, that is, clinicians and also patients, about the low quality provided. Indeed, emerging network technologies should be appropriately exploited by designing the transmission strategy focusing on quality provision for end users. Stemming from this principle, we propose here a context-aware transmission strategy for medical video transmission over WiMAX systems. Context, in terms of regions of interest (ROI) in a specific session, is taken into account for the identification of multiple regions of interest, and compression/transmission strategies are tailored to such context information. We present a methodology based on H.264 medical video compression and Flexible Macroblock Ordering (FMO) for ROI identification. Two different unequal error protection methodologies, providing higher protection to the most diagnostically relevant data, are presented

A Learned Polyalphabetic Decryption Cipher

This paper examines the use of machine learning algorithms to model polyalphabetic ciphers for decryption. The focus of this research is to train and evaluate different machine learning algorithms to model the polyalphabetic cipher. The algorithms that have been selected are: (1) hill climbing; (2) genetic algorithm; (3) simulated annealing; and (4), random optimisation. The resulting models were deployed in a simulation to decrypt sample codes. The resulting analysis showed that the genetic algorithm was the most effective technique used in with hill climbing as second. Furthermore, both have the potential to be useful for larger problems

A Decoding-Complexity and Rate-Controlled Video-Coding Algorithm for HEVC

Video playback on mobile consumer electronic (CE) devices is plagued by fluctuations in the network bandwidth and by limitations in processing and energy availability at the individual devices. Seen as a potential solution, the state-of-the-art adaptive streaming mechanisms address the first aspect, yet the efficient control of the decoding-complexity and the energy use when decoding the video remain unaddressed. The quality of experience (QoE) of the end-users’ experiences, however, depends on the capability to adapt the bit streams to both these constraints (i.e., network bandwidth and device’s energy availability). As a solution, this paper proposes an encoding framework that is capable of generating video bit streams with arbitrary bit rates and decoding-complexity levels using a decoding-complexity–rate–distortion model. The proposed algorithm allocates rate and decoding-complexity levels across frames and coding tree units (CTUs) and adaptively derives the CTU-level coding parameters to achieve their imposed targets with minimal distortion. The experimental results reveal that the proposed algorithm can achieve the target bit rate and the decoding-complexity with 0.4% and 1.78% average errors, respectively, for multiple bit rate and decoding-complexity levels. The proposed algorithm also demonstrates a stable frame-wise rate and decoding-complexity control capability when achieving a decoding-complexity reduction of 10.11 (%/dB). The resultant decoding-complexity reduction translates into an overall energy-consumption reduction of up to 10.52 (%/dB) for a 1 dB peak signal-to-noise ratio (PSNR) quality loss compared to the HM 16.0 encoded bit streams

Blockchain: A Panacea for Trust Challenges In Public Services? A Socio-technical Perspective

Trust in corporations, governments and public services has been steadily declining over the last few decades. L ack of transparency and auditability has been a key driver for this decline. Blockchain technology has been co mmended as a solution that can h elp with disintermediat ion and fill ing the consistently increasing trust challenges faced by the corporate and public s ector s . Public services are seeking solutions that can help establish trust and increase transpar e n c y with its citizens and b usinesses are undertaking extensive business analysis to determine the need and effectiveness of blockchain - like platforms as the basis for transforming their existing platforms. Due to the decisive nature, most of the analysis results thus indicate that if a trusted third party is an option, then blockchain should not be used. Here we highlight the challenges a nd opportunities of establishing trust and how blockchain technology can help public services bridge the trust gap with its citizens . We argue that all information technology systems rely on a suite of technologies , thus blockchain should be added to the c urrent technology stack rather than taking an ‘ all or nothing ’ approach. We also argue that analysing the effectiveness of futuristic technology like blockchain with industrial age methodology and mindset may limit th e realisation of its impact on society and economy . Therefore, we propose to take a heuristic approach , where different properties of blockchain technology need to be mapped against different aspects of current business process with a futuristic view in mind. Taking Com panies House – a governme nt organisation that holds over 4 million UK - based companies ’ records – as an example, we demonstrate how certain business processes in Companies House can benefit from adapting a blockchain - based solution

Public service operational efficiency and blockchain - A case study of Companies House, UK

Despite the increasing interest and exploration of the use of blockchain technology in public service organisations (PSOs), academic understanding of its transformative impact on the operational excellence of PSOs remains limited. This study adopts an action design science research methodology to develop a proof of concept (POC) blockchain based application for Companies House, a government agency that is registering companies across UK. The application addresses the operational challenges of Companies House as well as issues citizens face when accessing its services. We draw from the public value framework proposed by Twizeyimana and Andersson (2019) and demonstrate the significance of the emerging blockchain technology in relation to their democratic practices based on six dimensions. We further discuss the related challenges and barriers for its implementation and evaluate the POC with the stakeholders of Companies House. We also present an illustrative case study, where we explored the appropriateness of the POC in relation to the draft legislation, “Registration of Overseas Entities and Beneficial Owners” (ROEBO) bill which proposes the introduction of a register of the beneficial owners of overseas legal entities that own real estate in the UK. Our research is one of the few studies that will provide in-depth empirical insights about the relationship between blockchain and operational excellence of PSOs