1314530
GridSec: Trusted Grid Computing with Security Binding and Self-defense Against Network Worms and DDoS Attacks
The USC GridSec project develops distributed security infrastructure and self-defense capabilities to secure wide-area networked resource sites participating in a Grid application. We report new developments in trust modeling, security-binding methodology, and defense architecture against intrusions, worms, and flooding attacks. We propose a novel architectural design of Grid security infrastructure, security binding for enhanced Grid efficiency, distributed collaborative IDS and alert correlation, DHT-based overlay networks for worm containment, and pushback of DDoS attacks. Specifically, we present a new pushback scheme for tracking attack-transit routers and for cutting malicious flows carrying DDoS attacks. We discuss challenging research issues to achieve secure Grid computing effectively in an open Internet environment.
16325811
Collaborative detection and filtering of shrew DDoS attacks using spectral analysis
This paper presents a new spectral template-matching approach to countering shrew distributed denial-of-service (DDoS) attacks. These attacks are stealthy, periodic, pulsing, and low-rate in attack volume, very different from the flooding type of attacks. They are launched with high narrow spikes in very low frequency, periodically. Thus, shrew attacks may endanger the victim systems for a long time without being detected. In other words, such attacks may reduce the quality of services unnoticeably. Our defense method calls for collaborative detection and filtering (CDF) of shrew DDoS attacks. We detect shrew attack flows hidden in legitimate TCP/UDP streams by spectral analysis against pre-stored template of average attack spectral characteristics. This novel scheme is suitable for either software or hardware implementation. 
 
The CDF scheme is implemented with the NS-2 network simulator using real-life Internet background traffic mixed with attack datasets used by established research groups. Our simulated results show high detection accuracy by merging alerts from cooperative routers. Both theoretical modeling and simulation experimental results are reported here. The experiments achieved up to 95% successful detection of network anomalies along with a low 10% false positive alarms. The scheme cuts off malicious flows containing shrew attacks using a newly developed packet-filtering scheme. Our filtering scheme retained 99% of legitimate TCP flows, compared with only 20% TCP flows retained by using the Drop Tail algorithm. The paper also considers DSE FPGA, and network processor implementation issues and discusses limitations and further research challenges.
206594758
Detecting Collusion Attacks in Security Protocols
Security protocols have been widely used to safeguard secure electronic transactions. We usually assume that principals are credible and shall not maliciously disclose their individual secrets to someone else. Nevertheless, it is impractical to completely ignore the possibility that some principals may collude in private to achieve a fraudulent or illegal purpose. Therefore, it is critical to address the possibility of collusion attacks in order to correctly analyse security protocols. This paper proposes a framework by which to detect collusion attacks in security protocols. The possibility of security threats from insiders is especially taken into account. The case study demonstrates that our methods are useful and promising in discovering and preventing collusion attacks.
11734040
Analyzing Security Protocols Using Association Rule Mining
Current studies to analyzing security protocols using formal methods require users to predefine authentication goals. Besides, they are unable to discover potential correlations between secure messages. This research attempts to analyze security protocols using data mining. This is done by extending the idea of association rule mining and converting the verification of protocols into computing the frequency and confidence of inconsistent secure messages. It provides a novel and efficient way to analyze security protocols and find out potential correlations between secure messages. The conducted experiments demonstrate our approaches.
206473788
Booth's law of word frequency
Booth’s (1967) law is widely used to model the incidence of low frequency words in English text. Fedorowicz (198 1, 1982a, 1982b) used equation (3) below to study automated bibliographic systems. Pao (1978) used equation (4) to derive a transition point in automatic text analysis. The present communication confirms this usage, corrects a deficiency in the original derivation, and makes the results more general. Booth’s results are based on Zipf’s (1949) well-known relationship between the probability of occurrence, p(r), and the corresponding rank, r, of a word where
45083530
Improving backpropagation learning under limited precision
Abstract Most of the work to date on learning in neural networks assumes the availability of unlimited precision for implementing weights and the neural transfer functions. Recently some studies have investigated the effects of limited precision on the learning and generalisation performance. In this paper, we identify the causes of performance degradation due to limited precision and propose a novel algorithm to improve the performance of Backpropagation.
41090805
Distributed policy specification and enforcement in service-oriented business systems
Service-oriented computing (SOC) and Web services (WS) provide a flexible computing platform for electronic business and commerce. Introducing policy-based computing to service-oriented business systems adds another dimension of flexibility and security. While service composition and re-composition in service-oriented business systems allow major system reconstruction, policy-based computing can better deal with the small and routine changes of business processing. This paper reports our latest research on integrating policy-based computing into service-oriented business system and discusses its feasibility, benefits and cost. Under this research, we designed a policy specification and enforcement language PSEL for specifying system constraints and business rules. We implemented a runtime environment in which a service-oriented business system can be modeled, analyzed, deployed, and executed with policy enforcement. Automated tools have been developed to facilitate the entire development process. The cost of policy-based computing is experimentally evaluated