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Abstract-Positive expiratory pressure (PEP) therapy is an effective method for removing mucus build-up in the lungs of sufferers of chronic lung diseases such as cystic fibrosis (CF). However, the compliance by young children and adolescents to undertake such physiotherapy can lead to confrontation and stressful situations within families, and can impact on the health of the individual. We have developed game software which is controlled through breathing into a PEP mask or mouthpiece using an air pressure sensor to interface with the PC. By combining games with mucus clearing devices, it could provide a powerful means of encouraging children, teenagers and adults to engage more frequently, and effectively, with vital mucus clearance physiotherapy. This paper presents promising initial results and describes further usability testing plans.

Writable XOR executable (W⊕X) and address space layout randomisation (ASLR) have elevated the understanding necessary to perpetrate buffer overflow exploits [1] . However, they have not proved to be a panacea [1−3] , and so other mechanisms, such as stack guards and prelinking, have been introduced. In this paper, we show that host-based protection still does not offer a complete solution. To demonstrate the protection inadequacies, we perform an over the network brute force return-to-libc attack against a preforking concurrent server to gain remote access to a shell. The attack defeats host protection including W⊕X and ASLR. We then demonstrate that deploying a network intrusion detection systems (NIDS) with appropriate signatures can detect this attack efficiently.

Abstract-Intrusion Detection Systems are an accepted and very useful option to monitor, and detect malicious activities. However, Intrusion Detection Systems have inherent limitations which lead to false positives and false negatives; we propose that combining signature and anomaly based IDSs should be examined. This paper contrasts signature and anomaly-based IDSs, and critiques some proposals about hybrid IDSs with signature and heuristic capabilities, before considering some of their contributions in order to include them as main features of a new hybrid IDS named CONDOR (COmbined Network intrusion Detection ORientate), which is designed to offer superior pattern analysis and anomaly detection by reducing false positive rates and administrator intervention.

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With increasingly more businesses engaging in offshore outsourcing, organisations need to be made aware of the global differences in network security, before entrusting a nation with sensitive information. In July 2011, Syn and Nackrst1 explored this topic by analysing seven countries from a wide spectrum across the globe for network security vulnerabilities. The countries selected were China,

Abstract-This paper presents an approach to shellcode recognition directly from network traffic data using a multi-layer perceptron with back-propagation learning algorithm. Using raw network data composed of a mixture of shellcode, image files, and DLL-Dynamic Link Library files, our proposed design was able to classify the three types of data with high accuracy and high precision with neither false positives nor false negatives. The proposed method comprises simple and fast pre-processing of raw data of a fixed length for each network data package and yields perfect results with 100% accuracy for the three data types considered. The research is significant in the context of network security and intrusion detection systems. Work is under way for real time recognition and fine-tuning the differentiation between various shellcodes.

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