CRJul 5, 2019
A Pvalue-guided Anomaly Detection Approach Combining Multiple Heterogeneous Log Parser Algorithms on IIoT SystemsXueshuo Xie, Zhi Wang, Xuhang Xiao et al.
Industrial Internet of Things (IIoT) is becoming an attack target of advanced persistent threat (APT). Currently, IIoT logs have not been effectively used for anomaly detection. In this paper, we use blockchain to prevent logs from being tampered with and propose a pvalue-guided anomaly detection approach. This approach uses statistical pvalues to combine multiple heterogeneous log parser algorithms. The weighted edit distance is selected as a score function to calculate the nonconformity score between a log and a predefined event. The pvalue is calculated based on the non-conformity scores which indicate how well a log matches an event. This approach is tested on a large number of real-world HDFS logs and IIoT logs. The experiment results show that abnormal events could be effectively recognized by our pvalue-guided approach.
GTDec 20, 2016
Computational Complexity of Testing Proportional Justified RepresentationHaris Aziz, Shenwei Huang
We consider a committee voting setting in which each voter approves of a subset of candidates and based on the approvals, a target number of candidates are selected. Aziz et al. (2015) proposed two representation axioms called justified representation and extended justified representation. Whereas the former can be tested as well as achieved in polynomial time, the latter property is coNP-complete to test and no polynomial-time algorithm is known to achieve it. Interestingly, S{á}nchez-Fern{á}ndez et~al. (2016) proposed an intermediate property called proportional justified representation that admits a polynomial-time algorithm to achieve. The complexity of testing proportional justified representation has remained an open problem. In this paper, we settle the complexity by proving that testing proportional justified representation is coNP-complete. We complement the complexity result by showing that the problem admits efficient algorithms if any of the following parameters are bounded: (1) number of voters (2) number of candidates (3) maximum number of candidates approved by a voter (4) maximum number of voters approving a given candidate.