Existing Detection Approaches Research Articles

Detecting mutations in mixed sample sequencing data using empirical Bayes

We develop statistically based methods to detect single nucleotide DNA mutations in next generation sequencing data. Sequencing generates counts of the number of times each base was observed at hundreds of thousands to billions of genome positions in each sample. Using these counts to detect mutations is challenging because mutations may have very low prevalence and sequencing error rates vary dramatically by genome position. The discreteness of sequencing data also creates a difficult multiple testing problem: current false discovery rate methods are designed for continuous data, and work poorly, if at all, on discrete data. We show that a simple randomization technique lets us use continuous false discovery rate methods on discrete data. Our approach is a useful way to estimate false discovery rates for any collection of discrete test statistics, and is hence not limited to sequencing data. We then use an empirical Bayes model to capture different sources of variation in sequencing error rates. The resulting method outperforms existing detection approaches on example data sets.

Enabling automated threat response through the use of a dynamic security policy

Information systems security issues are currently being addressed using different techniques, such as authentication, encryption and access control, through the definition of security policies, but also using monitoring techniques, in particular intrusion detection systems. We can observe that security monitoring is currently totally decorrelated from security policies, that is security requirements are not linked with the means used to control their fulfillment. Most of the time, security operators have to analyze monitoring results and manually react to provide countermeasures to threats compromising the security policy. The response process is far from trivial, since it both relies on the relevance of the threat analysis and on the adequacy of the selected countermeasures. In this paper, we present an approach aiming at connecting monitoring techniques with security policy management in order to provide response to threat. We propose an architecture allowing to dynamically and automatically deploy a generic security policy into concrete policy instances taking into account the threat level characterized thanks to intrusion detection systems. Such an approach provides means to bridge the gap between existing detection approaches and new requirements, which clearly deal with the development of intrusion prevention systems, enabling a better protection of the resources and services.