Review of intrusion detection systems based on deep learning techniques: coherent taxonomy, challenges, motivations, recommendations, substantial analysis and future directions

This study reviews and analyses the research landscape for intrusion detection systems (IDSs) based on deep learning (DL) techniques into a coherent taxonomy and identifies the gap in this pivotal research area. The focus is on articles related to the keywords ‘deep learning’, ‘intrusion’ and ‘attack’ and their variations in four major databases, namely Web of Science, ScienceDirect, Scopus and the Institute of Electrical and Electronics Engineers’ Xplore. These databases are sufficiently broad to cover the technical literature. The dataset comprises 68 articles. The largest proportion (72.06%; 49/68) relates to articles that develop an approach for evaluating or identifying intrusion detection techniques using the DL approach. The second largest proportion (22.06%; 15/68) relates to studying/applying articles to the DL area, IDSs or other related issues. The third largest proportion (5.88%; 4/68) discusses frameworks/models for running or adopting IDSs. The basic characteristics of this emerging field are identified from the aspects of motivations, open challenges that impede the technology’s utility, authors’ recommendations and substantial analysis. Then, a result analysis mapping for new directions is discussed. Three phases are designed to meet the demands of detecting distributed denial-of-service attacks with a high accuracy rate. This study provides an extensive resource background for researchers who are interested in IDSs based on DL

Optimal Event-Driven Multi-Agent Persistent Monitoring of a Finite Set of Targets

We consider the problem of controlling the movement of multiple cooperating agents so as to minimize an uncertainty metric associated with a finite number of targets. In a one-dimensional mission space, we adopt an optimal control framework and show that the solution is reduced to a simpler parametric optimization problem: determining a sequence of locations where each agent may dwell for a finite amount of time and then switch direction. This amounts to a hybrid system which we analyze using Infinitesimal Perturbation Analysis (IPA) to obtain a complete on-line solution through an event-driven gradient-based algorithm which is also robust with respect to the uncertainty model used. The resulting controller depends on observing the events required to excite the gradient-based algorithm, which cannot be guaranteed. We solve this problem by proposing a new metric for the objective function which creates a potential field guaranteeing that gradient values are non-zero. This approach is compared to an alternative graph-based task scheduling algorithm for determining an optimal sequence of target visits. Simulation examples are included to demonstrate the proposed methods.Comment: 12 pages full version, IEEE Conference on Decision and Control, 201

Codon usage analysis of prokaryotic mechanosensation genes

[Abstract]: In the present study, we examined GC nucleotide composition, relative synonymous codon usage (RSCU), effective number of codons (ENC), codon adaptation index (CAI) and gene length for 308 prokaryotic mechanosensitive ion channel (MSC) genes from six evolutionary groups: Euryarchaeota, Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Firmicutes, and Gammaproteobacteria. Results showed that 1). a wide variation of overrepresentation of nucleotides exists in the MSC genes; 2). codon usage bias varies considerably among the MSC genes; 3). both nucleotide constraint and gene length play an important role in shaping codon usage of the bacterial MSC genes and 4). synonymous codon usage of prokaryotic MSC genes is phylogenetically conserved. Knowledge of codon usage in prokaryotic MSC genes may benefit for the study of the MSC genes in eukaryotes in which few MSC genes have been identified and functionally analysed

Remote Sensing Application to Grassland Monitoring

Application of remote sensing to the management of grassland resources, the role this plays in developing sustainable grassland farming systems and opportunities for further development are outlined. Use of remote sensing technologies in grassland monitoring has a history of more than 30 years. Both fine- and coarse-grained remote sensing techniques are used to monitor and study grasslands. Fine-grained techniques are used to study landscape scale processes through the use of sensors providing spatial resolution of a few meters, whereas coarse-grained techniques are used to study catchment scale areas, and even entire biomes, using satellite-based sensors with a spatial resolution of kilometers. Remote sensing information is obtained from aerial photography, radar systems, video systems, and satellite-based sensors including the Landsat satellites’ Multispectral Scanner (MSS) and Thematic mapper (TM) and the National Oceanic and Atmospheric Administration (NOAA) polar orbiters’ Advanced Very High Resolution Radiometer (AVHRR). Various normalized difference vegetation indices (NDVI) have been developed and used extensively with data from the Landsat sensors (MSS and TM) and NOAA’s AVHRR. The NDVI has been used for grassland classification and inventory, monitoring grassland-use change, determination of site productivity and herbivore carrying capacity, water and soil conservation, integrated management of grassland pests, and suitability for recreational use and wild life protection. Special techniques have also been developed for monitoring where fires occur on grasslands. To date the remote sensing techniques have become a powerful tool for scientists, farmers and policy makers to study and manage grassland resources. World demand for sustainable development of grasslands will increase the reliance on remote sensing as a tool in grassland management. However, the adaptation of existing remote sensing technology in grassland management will require more scientists and technicians to be trained in both remote sensing and grassland science. Additional training programs targeting scientists in developing countries will be needed. System approaches will be required that lead to better understanding of the interfacing of ground and remote sensing data sets. There is also a need for research on low cost, high resolution systems to be flown from aircraft and helicopters using narrow filters for assessing the condition of grassland health

Synthesis Imaging of Dense Molecular Gas in the N113 HII Region of the Large Magellanic Cloud

We present aperture synthesis imaging of dense molecular gas in the Large Magellanic Cloud, taken with the prototype millimeter receivers of the Australia Telescope Compact Array (ATCA). Our observations of the N113 HII region reveal a condensation with a size of ~6" (1.5 pc) FWHM, detected strongly in the 1-0 lines of HCO+, HCN and HNC, and weakly in C_2H. Comparison of the ATCA observations with single-dish maps from the Mopra Telescope and sensitive spectra from the Swedish-ESO Submillimetre Telescope indicates that the condensation is a massive clump of ~10^4 solar masses within a larger ~10^5 solar mass molecular cloud. The clump is centered adjacent to a compact, obscured HII region which is part of a linear structure of radio continuum sources extending across the molecular cloud. We suggest that the clump represents a possible site for triggered star formation. Examining the integrated line intensities as a function of interferometer baseline length, we find evidence for decreasing HCO+/HCN and HCN/HNC ratios on longer baselines. These trends are consistent with a significant component of the HCO+ emission arising in an extended clump envelope and a lower HCN/HNC abundance ratio in dense cores.Comment: 10 pages, 6 figures, to appear in Ap

Positive surface charge of GluN1 N-terminus mediates the direct interaction with EphB2 and NMDAR mobility.

Localization of the N-methyl-D-aspartate type glutamate receptor (NMDAR) to dendritic spines is essential for excitatory synaptic transmission and plasticity. Rather than remaining trapped at synaptic sites, NMDA receptors undergo constant cycling into and out of the postsynaptic density. Receptor movement is constrained by protein-protein interactions with both the intracellular and extracellular domains of the NMDAR. The role of extracellular interactions on the mobility of the NMDAR is poorly understood. Here we demonstrate that the positive surface charge of the hinge region of the N-terminal domain in the GluN1 subunit of the NMDAR is required to maintain NMDARs at dendritic spine synapses and mediates the direct extracellular interaction with a negatively charged phospho-tyrosine on the receptor tyrosine kinase EphB2. Loss of the EphB-NMDAR interaction by either mutating GluN1 or knocking down endogenous EphB2 increases NMDAR mobility. These findings begin to define a mechanism for extracellular interactions mediated by charged domains

The Two-Boson-Exchange Correction to Parity-Violating Elastic Electron-Proton Scattering

We calculate the two-boson-exchange (TBE) corrections to the parity-violating asymmetry of the elastic electron-proton scattering in a simple hadronic model including the nucleon and the $\Delta(1232)$ intermediate states. We find that $\Delta$ contribution $\delta_\Delta$ is, in general, comparable with the nucleon contribution $\delta_N$ and the current experimental measurements of strange-quark effects in the proton neutral weak current. The total TBE corrections to the current extracted values of $G^{s}_{E}+\beta G^{s}_{M}$ in recent experiments are found to lie in the range of $-7\sim +7$.Comment: 3 pages, 2 figs, 1 table, talk given at International Conference of Particle and Nuclei (PANIC08) Eilat, Israel, 9-14 Nov,200