GNN4IFA: Interest Flooding Attack Detection With Graph Neural Networks

In the context of Information-Centric Networking, Interest Flooding Attacks (IFAs) represent a new and dangerous sort of distributed denial of service. Since existing proposals targeting IFAs mainly focus on local information, in this paper we propose GNN4IFA as the first mechanism exploiting complex non-local knowledge for IFA detection by leveraging Graph Neural Networks (GNNs) handling the overall network topology. In order to test GNN4IFA, we collect SPOTIFAI, a novel dataset filling the current lack of available IFA datasets by covering a variety of IFA setups, including ?40 heterogeneous scenarios over three network topologies. We show that GNN4IFA performs well on all tested topologies and setups, reaching over 99% detection rate along with a negligible false positive rate and small computational costs. Overall, GNN4IFA overcomes state-of-the-art detection mechanisms both in terms of raw detection and flexibility, and – unlike all previous solutions in the literature – also enables the transfer of its detection on network topologies different from the one used in its design phase

A multifold approach to address the security issues of stateful forwarding mechanisms in Information-Centric Networks.

Today's Internet dominant usage trends motivate research on more content-oriented future network architectures. Among the emerging future Internet proposals, the promising Information-Centric Networking (ICN) research paradigm aims to redesign the Internet's core protocols to promote a shift in focus from hosts to contents. Among the ICN architectures, the Named-Data Networking (NDN) envisions users' named content requests to be forwarded and recorded by their names in routers along the path from one consumer to 1-or-many sources. The Pending Interest Table (PIT) is the NDN's data-plane component which temporarily records forwarded content requests in routers. On one hand, the PIT stateful mechanism enables properties like requests aggregation, multicast responses delivery and native hop-by-hop control flow. On the other hand, the PIT stateful forwarding behavior can be easily abused by malicious users to mount disruptive distributed denial of service attacks (DDoS), named Interest Flooding Attacks (IFAs). In IFAs, loosely coordinated botnets flood the network with a large amount of hard to satisfy requests with the aim to overload both the network infrastructure and the content producers. Countermeasures against IFA have been proposed since the early attack discovery. However, a fair understanding of the defense mechanisms' real efficacy is missing since those have been tested under simplistic assumptions about the evaluation scenarios. Thus, overall, the IFA security threat still appears easy to launch but hard to mitigate. This dissertation work shapes a better understanding of both the implications of IFAs and the possibilities of improving the state-of-the-art defense mechanisms against these attacks. The contributions of this work include the definition of a more complete and realistic attacker model for IFAs, the design of novel stealthy IFAs built upon the proposed attacker model, a re-assessment of the most-efficient state-of-the-art IFA countermeasures against the novel proposed attacks, the theorization and one concrete design of a novel class of IFA countermeasures to efficiently address the novel stealthy IFAs. Finally, this work also seminally proposes to leverage the latest programmable data-plane technologies to design and test alternative forwarding mechanisms for the NDN which could be less vulnerable to the IFA threat

Improved Content Finding in Named Data Networking

In today’s Internet, the current architecture may not be able to support various challenges (e.g., security, mobility, scalability, and quality of service) in a sufficient level. Information-centric communication model is expected to address the bottleneck of the traditional host-centric model. A number of Information Centric Network (ICN) approaches have been proposed by aiming to replace or augment the current host-to-host routing architecture. ICN focuses on finding and transmitting content to end-users and content routing is location-independent, thereby being able to support multi-sourcing for content consumers. Named Data Networking (NDN) is one of the promising ICN proposals that allows users (i.e., consumers) to find content objects by their names. In the default forwarding strategy of NDN, an interest packet is forwarded to locate content. A corresponding data packet will be returned back in the reverse path to its requester and will be replicated along this path (called on-path caching). When a consumer requests a content object, it may be found at an intermediate on-path cache. However, several replicas that are often cached off-path especially in nearby nodes of the consumer’s vicinity could be the better potential source but they are not effectively utilised, causing a worse than necessary delivery efficiency. Therefore, this thesis investigates the potential of off-path content finding in NDN. We examine how we can design a flexible and efficient solution to supplement the existing NDN architecture. We then propose a new design called a Vicinity-based Content Finding scheme (VCoF) to utilise nearby replicas in each vicinity for improving content finding. This includes analysing the efficiency of the proposed scheme in comparison to default NDN. We consider content popularity, which can impact content finding results due to the different number of content replicas (i.e., content availability). We also explore our scheme in supporting mobility, particularly for the issues of missing content because of handover. Through a prototype implementation, we evaluate the delivery efficiency against overhead costs in different scenarios, made possible through effective deployment on real NDN environments

Structural and economic analysis of capesize bulk carriers

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 935-1001).Structural failures of bulk carriers continue to account for the loss of many lives every year. Capes are particularly vulnerable to cracking because of their large length, their trade in high density cargos, and the high rates of cargo operations. Rapid loss often occurs allowing little reaction time which has alarmed the industry. The Cape market is extremely volatile with ship values appreciating in some cases by over 500% and then returning to original levels, all within a few years. Recent market changes have rendered conventional pricing methods inaccurate and often inapplicable, resulting in a pressing need for alternate valuation models. Very little research combines the closely interlinked technical and financial elements which are crucial for valuation and decision making by various parties in the shipping industry. The present research involves the collection and analysis of one of the largest ship cracking surveys. It is focused specifically on capes which lie at the core of the problem and is based on the records of ship owners, classification societies and shipyards. A location coding system was specifically designed to analyze the data and present the frequency, size and estimated crack growth rates with respect to location and ship age. The results were compared with existing knowledge based on surveys conducted over the past 50 years, the stress distribution based on an investigation of loading patterns, and theoretical fracture mechanics predictions. They were then combined with the frequency of crack failures, derived from an investigation of an extensive fleet sample, to develop a reliability model which yields the hazard function throughout the ship's life. Repair procedures and design modifications were also examined and a model was designed to assess their cost effectiveness based on the present value of projected crack costs. The crack repair costs were calculated as a function of ship age to be used in conjunction with the safety assessment for decision making by ship owners, insurance companies, classification societies and others. A new state of the art valuation model was developed combining both technical and financial aspects in a fundamental valuation based on risk-adjusted discounting of expected cash flows. A forward view of the main parameters was obtained from derivatives and financial securities that include shipping futures, FFAs, options, interest rate swaps and inflation protected bonds. The inherent risk of cracks is treated as a fictitious credit risk, derived from the reliability model, and is incorporated into the discount rate along with other risk premiums. Other inputs include repair costs and off-hire time, which were calculated with respect to ship age using a database of repairs, while the records of public and private companies were used along with surveys to estimate operating expenses. The resulting valuations were found to be in very close alignment with recent transaction prices across all ship ages. The model also estimates the volatility of the ship value and uses it to price optionalities that are often included in ship transactions. The combination of technical and financial analysis of this thesis is valuable to many involved in the shipping industry including brokers, accountants, analysts, shipping banks and investors interested in valuation; ship owners when making managerial or investment decisions; shipyards when designing ships, setting prices and deciding payment structures and options; insurance companies when covering total loss or emergency repairs; the IMO when setting regulations; and classification societies when scheduling inspections and deciding which areas to focus on.by Nicholas Andrew Hadjiyiannis.Ph.D