Biblio

Big data is a buzzword used to describe massive volumes of data that provides opportunities of exploring new insights through data analytics. However, big data is mostly structured but can be semi-structured or unstructured. It is normally so large that it is not only difficult but also slow to process using traditional computing systems. One of the solutions is to format the data as graph data structures and process them on shared memory architecture to use fast and novel policies such as transactional memory. In most graph applications in big data type problems such as bioinformatics, social networks, and cybersecurity, graphs are sparse in nature. Due to this sparsity, we have the opportunity to use Transactional Memory (TM) as the synchronization policy for critical sections to speedup applications. At low conflict probability TM performs better than most synchronization policies due to its inherent non-blocking characteristics. TM can be implemented in Software, Hardware or a combination of both. However, hardware TM implementations are fast but limited by scarce hardware resources while software implementations have high overheads which can degrade performance. In this paper, we develop a low overhead, yet simple, dynamically adaptive (i.e., at runtime) hybrid (i.e., combines hardware and software) TM (DyAd-HyTM) scheme that combines the best features of both Hardware TM (HTM) and Software TM (STM) while adapting to application's requirements. It performs better than coarse-grain lock by up to 8.12x, a low overhead STM by up to 2.68x, a couple of implementations of HTMs (by up to 2.59x), and other HyTMs (by up to 1.55x) for SSCA-2 graph benchmark running on a multicore machine with a large shared memory.

A recent paper (Oakland 2017) discussed science and security research in the context of the government-funded Science of Security movement, and the history and prospects of security as a scientific pursuit. It drew on literature from within the security research community, and mature history and philosophy of science literature. The paper sparked debate in numerous organizations and the security community. Here we consider some of the main ideas, provide a summary list of relevant literature, and encourage discussion within the Moving Target Defense (MTD) sub-community1.

Process anomaly is used for detecting cyber-physical attacks on critical infrastructure such as plants for water treatment and electric power generation. Identification of process anomaly is possible using rules that govern the physical and chemical behavior of the process within a plant. These rules, often referred to as invariants, can be derived either directly from plant design or from the data generated in an operational. However, for operational legacy plants, one might consider a data-centric approach for the derivation of invariants. The study reported here is a comparison of design-centric and data-centric approaches to derive process invariants. The study was conducted using the design of, and the data generated from, an operational water treatment plant. The outcome of the study supports the conjecture that neither approach is adequate in itself, and hence, the two ought to be integrated.

In a world of ever-increasing systems interdependence, effective cybersecurity policy design seems to be one of the most critically understudied elements of our national security strategy. Enterprise cyber technologies are often implemented without much regard to the interactions that occur between humans and the new technology. Furthermore, the interactions that occur between individuals can often have an impact on the newly employed technology as well. Without a rigorous, evidence-based approach to ground an employment strategy and elucidate the emergent organizational needs that will come with the fielding of new cyber capabilities, one is left to speculate on the impact that novel technologies will have on the aggregate functioning of the enterprise. In this paper, we will explore a scenario in which a hypothetical government agency applies a complexity science perspective, supported by agent-based modeling, to more fully understand the impacts of strategic policy decisions. We present a model to explore the socio-technical dynamics of these systems, discuss lessons using this platform, and suggest further research and development.

The U.S. federal governments and agencies face increasingly sophisticated and persistent cyber threats and cyberattacks from black hat hackers who breach cybersecurity for malicious purposes or for personal gain. With the rise of malicious attacks that caused untold financial damage and substantial reputational damage, private-sector high-tech firms such as Google, Microsoft and Yahoo have adopted an innovative practice known as vulnerability reward program (VRP) or bug bounty program which crowdsources software bug detection from the cybersecurity community. In an alignment with the 2016 U.S. Cybersecurity National Action Plan, the Department of Defense adopted a pilot VRP in 2016. This paper examines the Pentagon's VRP and examines how it may fit with the national cybersecurity policy and the need for new and enhanced cybersecurity capability development. Our case study results show the feasibility of the government adoption and implementation of the innovative concept of VRP to enhance the government cybersecurity posture.

Today cyber security is one of the most active fields of re- search due to its wide range of impact in business, govern- ment and everyday life. In recent years machine learning methods and algorithms have been quite successful in a num- ber of security areas. In this paper, we explore an approach to classify intrusion called multi-perspective machine learn- ing (MPML). For any given cyber-attack there are multiple methods of detection. Every method of detection is built on one or more network characteristic. These characteristics are then represented by a number of network features. The main idea behind MPML is that, by grouping features that support the same characteristics into feature subsets called perspectives, this will encourage diversity among perspectives (classifiers in the ensemble) and improve the accuracy of prediction. Initial results on the NSL- KDD dataset show at least a 4% improvement over other ensemble methods such as bagging boosting rotation forest and random for- est.

Organizations develop technical and procedural measures to protect information systems. Relying only on technical based security solutions is not enough. Organizations must consider technical security solutions along with social, human, and organizational factors. The human element represents the employees (insiders) who use the information systems and other technology resources in their day-to-day operations. ISP awareness is essential to protect organizational information systems. This study adapts the Innovation Diffusion Theory to examine the antecedents of ISP awareness and its impact on the satisfaction with ISP and security practices. A sample of 236 employees in universities in the United States is collected to evaluate the research model. Results indicated that ISP quality, self-efficacy, and technology security awareness significantly impact ISP awareness. The current study presents significant contributions toward understanding the antecedents of ISP awareness and provides a starting point toward including satisfaction aspect in information security behavioral domain.

This paper suggests a conceptual mechanism for increasing the security level of the global information community, national information technology infrastructures (e-governments) and private cloud structures, which uses the logical characteristic of IPv6-protocol. The mechanism is based on the properties of the IPv6-header and, in particular, rules of coding IPv6-addresses.

This study seeks to investigate how the development of e-government services impacts on cybersecurity. The study uses the methods of correlation and multiple regression to analyse two sets of global data, the e-government development index of the 2015 United Nations e-government survey and the 2015 International Telecommunication Union global cybersecurity development index (GCI 2015). After analysing the various contextual factors affecting e-government development, the study found that, various composite measures of e-government development are significantly correlated with cybersecurity development. The therefore study contributes to the understanding of the relationship between e-government and cybersecurity development. The authors developed a model to highlight this relationship and have validated the model using empirical data. This is expected to provide guidance on specific dimensions of e-government services that will stimulate the development of cybersecurity. The study provided the basis for understanding the patterns in cybersecurity development and has implication for policy makers in developing trust and confidence for the adoption e-government services.

By connecting devices, people, vehicles and infrastructures everywhere in a city, governments and their partners can improve community wellbeing and other economic and financial aspects (e.g., cost and energy savings). Nonetheless, smart cities are complex ecosystems that comprise many different stakeholders (network operators, managed service providers, logistic centers...) who must work together to provide the best services and unlock the commercial potential of the IoT. This is one of the major challenges that faces today's smart city movement, and more generally the IoT as a whole. Indeed, while new smart connected objects hit the market every day, they mostly feed "vertical silos" (e.g., vertical apps, siloed apps...) that are closed to the rest of the IoT, thus hampering developers to produce new added value across multiple platforms. Within this context, the contribution of this paper is twofold: (i) present the EU vision and ongoing activities to overcome the problem of vertical silos; (ii) introduce recent IoT standards used as part of a recent Horizon 2020 IoT project to address this problem. The implementation of those standards for enhanced sporting event management in a smart city/government context (FIFA World Cup 2022) is developed, presented, and evaluated as a proof-of-concept.

We propose a new voting scheme, BeleniosRF, that offers both receipt-freeness and end-to-end verifiability. It is receipt-free in a strong sense, meaning that even dishonest voters cannot prove how they voted. We provide a game-based definition of receipt-freeness for voting protocols with non-interactive ballot casting, which we name strong receipt-freeness (sRF). To our knowledge, sRF is the first game-based definition of receipt-freeness in the literature, and it has the merit of being particularly concise and simple. Built upon the Helios protocol, BeleniosRF inherits its simplicity and does not require any anti-coercion strategy from the voters. We implement BeleniosRF and show its feasibility on a number of platforms, including desktop computers and smartphones.

This paper presents the holistic approach to cyber resilience as a means of preparing for the "unknown unknowns". Principles of augmented cyber risks management and resilience management model at national level are presented, with elaboration on multi-stakeholder engagement and partnership for the implementation of national cyber resilience collaborative framework. The complementarity of governance, law, and business/industry initiatives is outlined, with examples of the collaborative resilience model for the Bulgarian national strategy and its multi-national engagements.

Cloud computing is one of the happening technologies in these years and gives scope to lot of research ideas. Banks are likely to enter the cloud computing field because of abundant advantages offered by cloud like reduced IT costs, pay-per-use modeling, and business agility and green IT. Main challenges to be addressed while moving bank to cloud are security breach, governance, and Service Level Agreements (SLA). Banks should not give prospect for security breaches at any cost. Access control and authorization are vivacious solutions to security risks. Thus we are proposing a knowledge based security model addressing the present issue. Separate ontologies for subject, object, and action elements are created and an authorization rule is framed by considering the inter linkage between those elements to ensure data security with restricted access. Moreover banks are now using Software as a Service (SaaS), which is managed by Cloud Service Providers (CSPs). Banks rely upon the security measures provided by CSPs. If CSPs follow traditional security model, then the data security will be a big question. Our work facilitates the bank to pose some security measures on their side along with the security provided by the CSPs. Banks can add and delete rules according to their needs and can have control over the data in addition to CSPs. We also showed the performance analysis of our model and proved that our model provides secure access to bank data.

Regarding Information and Communication Technologies (ICTs) in the public sector, electronic governance is the first emerged concept which has been recognized as an important issue in government's outreach to citizens since the early 1990s. The most important development of e-governance recently is Open Government Data, which provides citizens with the opportunity to freely access government data, conduct value-added applications, provide creative public services, and participate in different kinds of democratic processes. Open Government Data is expected to enhance the quality and efficiency of government services, strengthen democratic participation, and create interests for the public and enterprises. The success of Open Government Data hinges on its accessibility, quality of data, security policy, and platform functions in general. This article presents a robust assessment framework that not only provides a valuable understanding of the development of Open Government Data but also provides an effective feedback mechanism for mid-course corrections. We further apply the framework to evaluate the Open Government Data platform of the central government, on which open data of nine major government agencies are analyzed. Our research results indicate that Financial Supervisory Commission performs better than other agencies; especially in terms of the accessibility. Financial Supervisory Commission mostly provides 3-star or above dataset formats, and the quality of its metadata is well established. However, most of the data released by government agencies are regulations, reports, operations and other administrative data, which are not immediately applicable. Overall, government agencies should enhance the amount and quality of Open Government Data positively and continuously, also strengthen the functions of discussion and linkage of platforms and the quality of datasets. Aside from consolidating collaborations and interactions to open data communities, government agencies should improve the awareness and ability of personnel to manage and apply open data. With the improvement of the level of acceptance of open data among personnel, the quantity and quality of Open Government Data would enhance as well.

This paper proposes the Digital Public Service Innovation Framework that extends the "standard" provision of digital public services according to the emerging, enhanced, transactional and connected stages underpinning the United Nations Global e-Government Survey, with seven example "innovations" in digital public service delivery – transparent, participatory, anticipatory, personalized, co-created, context-aware and context-smart. Unlike the "standard" provisions, innovations in digital public service delivery are open-ended – new forms may continuously emerge in response to new policy demands and technological progress, and are non-linear – one innovation may or may not depend on others. The framework builds on the foundations of public sector innovation and Digital Government Evolution model. In line with the latter, the paper equips each innovation with sharp logical characterization, body of research literature and real-life cases from around the world to simultaneously serve the illustration and validation goals. The paper also identifies some policy implications of the framework, covering a broad range of issues from infrastructure, capacity, eco-system and partnerships, to inclusion, value, channels, security, privacy and authentication.

Recent years have seen an exponential growth of the collection and processing of data from heterogeneous sources for a variety of purposes. Several methods and techniques have been proposed to transform and fuse data into "useful" information. However, the security aspects concerning the fusion of sensitive data are often overlooked. This paper investigates the problem of data fusion and derived data control. In particular, we identify the requirements for regulating the fusion process and eliciting restrictions on the access and usage of derived data. Based on these requirements, we propose an attribute-based policy framework to control the fusion of data from different information sources and under the control of different authorities. The framework comprises two types of policies: access control policies, which define the authorizations governing the resources used in the fusion process, and fusion policies, which define constraints on allowed fusion processes. We also discuss how such policies can be obtained for derived data.

While in business and private settings the disruptive impact of advanced information communication technology (ICT) have already been felt, the legal sector is now starting to face great disruptions due to such ICTs. Bits and pieces of innovations in the legal sector have been emerging for some time, affecting the performance of core functions and the legitimacy of public institutions. In this paper, we present our framework for enabling the smart government vision, particularly for the case of criminal justice systems, by unifying different isolated ICT-based solutions. Our framework, coined as Legal Logistics, supports the well-functioning of a legal system in order to streamline the innovations in these legal systems. The framework targets the exploitation of all relevant data generated by the ICT-based solutions. As will be illustrated for the Dutch criminal justice system, the framework may be used to integrate different ICT-based innovations and to gain insights about the well-functioning of the system. Furthermore, Legal Logistics can be regarded as a roadmap towards a smart and open justice.

In this workshop, participants coming from a variety of disciplinary backgrounds and countries–-China, South Korea, EU, and US–-will present their country's cyber security initiatives and challenges. Following the presentations, participants will discuss current trends, lessons learned in implementing the initiatives, and international collaboration. The workshop will culminate in the setting an agenda for future collaborative studies in cyber security.

While the rapid progress in smart city technologies are changing cities and the lifestyle of the people, there are increasingly enormous challenges in terms of the safety and security of smart cities. The potential vulnerabilities of e-government products and imminent attacks on smart city infrastructure and services will have catastrophic consequences on the governments and can cause substantial economic and noneconomic losses, even chaos, to the cities and their residents. This paper aims to explore alternative economic solutions ranging from incentive mechanisms to market-based solutions to motivate smart city product vendors, governments, and vulnerability researchers and finders to improve the cybersecurity of smart cities.

Texting while driving has emerged as a significant threat to citizen safety. In this study, we utilize general deterrence theory (GDT), protection motivation theory and personality traits to evaluate texting while driving (TWD) compliance intentions among teenage drivers. This paper presents the results of our pilot study. We administered an online survey to 105 teenage and young adult drivers. The potential implications for research and practice and policy are discussed.

This paper designs a secure transmission and authorization management system which based on the principles of Public Key Infrastructure and Rose-Based Access Control. It can solve the problems of identity authentication, secure transmission and access control on internet. In the first place, according to PKI principles, certificate authority system is implemented. It can issue and revoke the server-side and client-side digital certificate. Data secure transmission is achieved through the combination of digital certificate and SSL protocol. In addition, this paper analyses access control mechanism and RBAC model. The structure of RBAC model has been improved. The principle of group authority is added into the model and the combination of centralized authority and distributed authority management is adopted, so the model becomes more flexible.