Network intrusion detection system for DDoS attacks in ICS using deep autoencoders

Anomaly detection in industrial control and cyber-physical systems has gained much attention over the past years due to the increasing modernisation and exposure of industrial environments. Current dangers to the connected industry include the theft of industrial intellectual property, denial of service, or the compromise of cloud components; all of which might result in a cyber-attack across the operational network. However, most scientific work employs device logs, which necessitate substantial understanding and preprocessing before they can be used in anomaly detection. In this paper, we propose a network intrusion detection system (NIDS) architecture based on a deep autoencoder trained on network flow data, which has the advantage of not requiring prior knowledge of the network topology or its underlying architecture. Experimental results show that the proposed model can detect anomalies, caused by distributed denial of service attacks, providing a high detection rate and low false alarms, outperforming the state-of-the-art and a baseline model in an unsupervised learning environment. Furthermore, the deep autoencoder model can detect abnormal behaviour in legitimate devices after an attack. We also demonstrate the suitability of the proposed NIDS in a real industrial plant from the alimentary sector, analysing the false positive rate and the viability of the data generation, filtering and preprocessing procedure for a near real time scenario. The suggested NIDS architecture is a low-cost solution that uses only fifteen network-based features, requires minimal processing, operates in unsupervised mode, and is straightforward to deploy in real-world scenarios.Axencia Galega de Innovación | Ref. IN854A 2019/15Centro para el Desarrollo Tecnológico Industrial | Ref. CER-20191012Agencia Estatal de Investigación | Ref. MTM2017-89422-PFinanciado para publicación en acceso aberto: Universidade de Vigo/CISU

seq2R: an R package to detect change points in DNA sequences

Identifying the mutational processes that shape the nucleotide composition of the mitochondrial genome (mtDNA) is fundamental to better understand how these genomes evolve. Several methods have been proposed to analyze DNA sequence nucleotide composition and skewness, but most of them lack any measurement of statistical support or were not developed taking into account the specificities of mitochondrial genomes. A new methodology is presented, which is specifically developed for mtDNA to detect compositional changes or asymmetries (AT and CG skews) based on nonparametric regression models and their derivatives. The proposed method also includes the construction of confidence intervals, which are built using bootstrap techniques. This paper introduces an R package, known as seq2R, that implements the proposed methodology. Moreover, an illustration of the use of seq2R is provided using real data, specifically two publicly available complete mtDNAs: the human (Homo sapiens) sequence and a nematode (Radopholus similis) mitogenome sequence.Ministerio de Ciencia e Innovación | Ref. MTM2011-23204Ministerio de Ciencia e Innovación | Ref. PID2020-118101GB-I00Xunta de Galicia | Ref. 10PXIB 300 068 P

Reactivity of polar organometallic compounds in unconventional reaction media : challenges and opportunities

Developing new green solvents in designing chemical products and processes or successfully employing the already existing ones is one of the key subjects in green chemistry and is especially important in organometallic chemistry, which is an interdisciplinary field. Can we advantageously also use unconventional reaction media in place of current harsh organic solvents for polar organometallic compounds? This microreview critically analyses the state of the art with regard to this topic and showcases recent developments and breakthroughs that are becoming new research directions in this field. Because metals cover a vast swath of the Periodic Table the content is organised into three sections discussing the reactivity of organometallic compounds of s-, p- and d-block elements in unconventional solvents