Defending financial infrastructures through early warning systems

Abstract

Recent evidence of successful Internet-based attacks and frauds involving financial institutions highlights the inadequacy of the existing protection mechanisms, in which each instutition implements its own isolated monitoring and reaction strategy. Analyzing on-line activity and detecting attacks on a large scale is an open issue due to the huge amounts of events that should be collected and processed. In this paper, we propose a large-scale distributed event processing system, called intelligence cloud, allowing the financial entities to participate in a widely distributed monitoring and detection effort through the exchange and processing of information locally available at each participating site. We expect this approach to be able to handle large amounts of events arriving at high rates from multiple domains of the financial scenario. We describe a framework based on the intelligence cloud where each participant can receive early alerts enabling them to deploy proactive countermeasures and mitigation strategies.

A Conceptual Model for Cloud Computing Adoption by SMEs in Australia

“…There are many business areas where Cloud Computing has been adopted, including in higher education (Sultan, 2010;Wheeler and Waggener, 2009;Suess and Morooney, 2009), to provide solutions for human resources (Farah, 2010), software testing (Babcock, 2009), data back-up or archive services (Treese, 2008), Web 2.0 based collaborative applications (Orr, 2008), for storage capacity on demand (Kraska et al, 2009), and for content distribution services (Fortino et al, 2009). New IT approaches and services have taken advantage of Cloud Computing, for example, market-oriented allocation of resources , hard discrete optimization problems (Li et al, 2009), corporate fraud detection using intelligence (Lodi et al, 2009), collaborative business intelligence (Chow et al, 2009), data mining algorithms and predictive analytics (Zeller et al, 2009;Guazzelli et al, 2009), software testing as a service (Ciortea et al, 2009), e-government solutions (Cellary and Strykowski, 2009), and architecture and implementation courses at graduate level in Cloud Computing (Holden et al, 2009).…”

Security of Separated Data in Cloud Systems with Competing Attack Detection and Data Theft Processes

“…In this article, we advance the state of the art by considering early warning mechanisms for possibly detecting and preventing co‐residence attacks at a nascent stage in cloud systems with data partitions. The early warning mechanisms (e.g., in the form of a monitor, honeypot, or proxy firewall) have been implemented to improve security or reliability of different types of systems (Fu & Yan, ; Kalutarage, Shaikh, Lee, Lee, & Kiat, ; Lodi et al., ; Mohammad, Kalam, & Akella, ). Considerable research efforts have been dedicated to reliability modeling and analysis of early warning systems for power systems, natural hazards, and public crises (Nasonov & Butakov, ; Qin, Shang, Zhang, & Zhao, ; Sättele, Bründl, & Straub, ; Visheratin, Melnik, Nasonov, Butakov, & Boukhanovsky, ; Wang & Hu, ; Xu, Wang, Wu, & Kuo‐Chen, ).…”

Secure Collaborative Processing Architecture for MITB Attack Detection

“…Because of the increased sophistication of computer attack tools, a higher number of actors are capable of launching effective attacks against IT critical infrastructures; that is, the range of possible attackers is not limited to skilled crackers anymore; criminal organizations, terrorist groups using the Internet for making money or causing any types of damages are augmenting, with serious and measurable consequences for any critical infrastructure: lost revenue, own time, damage to the reputation, damage to IT assets, theft of proprietary data or customer sensitive information [4].…”