This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. This paper proposed an improved anomaly threshold solution for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability. In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV. | How to cite this paper: Mohamad Farhan Mohamad Mohsin, Azuraliza Abu Bakar, Abdul Razak Hamdan & Mohd Helmy Abdul Wahab (2018). An improved artificial dendrite cell algorithm for abnormal signal detection. Journal of Information and Communication Technology (JICT), 17 (1), 33-54. AN IMPROVED ARTIFICIAL DENDRITE CELL ALGORITHM FOR ABNORMAL SIGNAL DETECTION 1 Mohamad Farhan Mohamad Mohsin, 2Azuraliza Abu Bakar, 3Abdul Razak Hamdan & 4 Mohd Helmy Abdul Wahab 1 School of Computing, Universiti Utara Malaysia, Malaysia Faculty of Science & Information Technology Universiti Kebangsaan Malaysia, Malaysia, 4 Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia, Malaysia 2,3 farhan@; aab@; arh@; helmy@ ABSTRACT In dendrite cell algorithm (DCA), the abnormality of a data point is determined by comparing the multi-context antigen value (MCAV) with anomaly threshold. The limitation of the existing threshold is that the value needs to be determined before mining based on previous information and the existing MCAV is inefficient when exposed to extreme values. This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. This paper proposed an improved anomaly threshold solution for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability. In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV. From the experiments towards 12 benchmark and two outbreak datasets, the improved DCA is proven to have a better detection result than its previous version in terms of sensitivity, specificity, false detection rate and accuracy. Keywords: Anomaly threshold, dendrite cell algorithm, multi-context antigen value. Received: 20 February 2017 Accepted: 30 July 2017 Journal .
