Cooperative technological solutions for Distributed Denial-of-Service (DDoS) attacks are already available, yet organizations in the best position to implement them lack incentive to do so, and the victims of DDoS attacks cannot find effective methods to motivate them. In this article we discuss two components of the technological solutions to DDoS attacks: cooperative filtering and cooperative traffic smoothing by caching. We then analyze the broken incentive chain in each of these technological solutions. As a remedy, we propose usage-based pricing and Capacity Provision Networks, which enable victims to disseminate enough incentive along attack paths to stimulate cooperation against DDoS attacks. Categories and Subject Descriptors: K.4.1 [Computers and Society]: Public Policy Issues— Abuse and crime involving computers; Use/abuse of power; K.4.4 [Computers and Society]:

The issue of organizational capability is central to virtually all efforts to improve government performance, particularly in the area of information technology innovation. Capability assessment can play an important role in the digital government domain in at least two ways: one is to provide a basis for judging whether agencies are ready to initiate some digital government innovation, and the other is to judge the impact of a digital government initiative in terms of improved capabilities. Data on capabilities targeted by digital government initiatives can provide both baseline measurements and evidence of subsequent improvements. As part of its research and development on several digital government projects, the Center for Technology in Government (CTG) has developed an approach to capability assessment, resulting in specific assessment toolkits for use in different types of digital government initiatives. This paper describes the approach used in developing these toolkits generally, with an example from one version intended for use in justice information integration projects. The paper includes the theoretical rationale for the design of the toolkits, methods for their use, and implications for use in practice.

Because organizations are making large investments in Information systems (IS), efficient IS project management has been found critical to success. This study examines how the use of incentives can improve the project success. Agency theory is used to: identify motivational factors of project success, help the IS owners to understand to what extent management incentives can improve IS development and implementation (ISD/I). The outcomes will help practitioners and researchers to build on theoretical model of project management elements which lead to project success. Given the principal-agent nature of most significant scale of IS development, insights that will allow for greater alignment of the agent’s goals with those of the principal through incentive contracts, will serve to make ISD/I both more efficient and more effective, leading to more successful IS projects.

Through the aegis of the National Natural Science Foundation of China (NSFC), China has embarked on an ambitious effort to regain prominence in innovation and academic contribution to knowledge after decades of relative neglect precipitated by the “cultural revolution. ” Unfortunately, initial efforts made during the last decade of the 20th century resulted in quick growth in knowledge quantity (e.g., publications) that failed to generate sound growth in knowledge quality (e.g., citations). Incentives in place were not producing desired results. An innovative collaborative Internet-based Science Information System (ISIS) was applied nation-wide in 2003 in China’s Research Community (CRC) with a variety of embedded incentives to rectify the situation. The system has been well received. In the year 2005 alone, ISIS helped the NSFC to process more than 53,000 on-line funding applications and 250,000 electronic reviews from 1,400 universities and research institutes in China. This paper is aimed at exploring Information Systems (IS) innovation impact from the perspective of incentive alignment based on CRC empirical results. Since the nation-wide application of ISIS in 2003, CRC outcomes have markedly improved. Discussion and directions for future research examine generalizability in the context of information systems for innovation and collaborative business. Conclusions are drawn.

Institutional theories have been adopted to explain and predict the process of Information Systems (IS) innovation in organisations. However, most institutional-centred frameworks overlook the significance of external economic efficiency and internal organisational capability when organisations consider strategic responses to institutional conformity pressure. Focusing on the diffusion of IS security management as an administrative innovation, this paper develops an integrative framework that illustrates how economic and organisational factors contribute to the organisational decision-making process in the light of institutional influences on the adoption and assimilation of IS security management. The proposed model and hypotheses then plan to be tested using the data collected from two-stage longitudinal study.

Information Systems (IS) continued use theories have typically excluded a role for effort expectancy and similar constructs arguing that they do not impact the intentions of experienced users. This may not hold true for an emerging class of information systems that we refer to as High Maintenance Information Systems (HMIS). HMIS are a class of information systems that require users to expend an ongoing maintenance effort in order to keep the system up-to-date so they can continue to reap future benefits out of using the system. This ongoing maintenance effort is unlikely to significantly diminish as users gain further experience. The proposed study seeks to develop a theoretical model that explains the factors influencing individuals ’ continued use of such systems taking into account the potential role of perceived maintenance effort. The proposed model will be validated using a survey design involving experienced Facebook users. Collected data will be analyzed using structural equation modeling and qualitative data analysis techniques.