ForChaos: Real Time Application DDoS detection using Forecasting and Chaos Theory in Smart Home IoT Network

Recently, D/DoS attacks have been launched by zombie IoT devices in smart home networks. They pose a great threat to to network systems with Application Layer DDoS attacks being especially hard to detect due to their stealth and seemingly legitimacy. In this paper, we propose we propose ForChaos, a lightweight detection algorithm for IoT devices, that is based on forecasting and chaos theory to identify flooding and DDoS attacks. For every time-series behaviour collected, a forecasting-technique prediction is generated, based on a number of features, and the error between the two values is calcualted. In order to assess the error of the forecasting from the actual value, the lyapunov exponent is used to detect potential malicious behaviour. In NS-3 we evaluate our detection algorithm through a series of experiments in Flooding and Slow-Rate DDoS attacks. The results are presented and discussed in detail and compared with related studies, demonstrating its effectiveness and robustness

Lead identification and structure-activity relationships of heteroarylpyrazole arylsulfonamides as allosteric CC-chemokine receptor 4 (CCR4) antagonists

A knowledge-based library of aryl 2,3-dichlorophenylsulfonamides was synthesised and screened as human CCR4 antagonists, in order to identify a suitable hit for the start of a lead-optimisation programme. X-ray diffraction studies were used to identify the pyrazole ring as a moiety that could bring about intramolecular hydrogen bonding with the sulfonamide NH and provide a clip or orthogonal conformation that was believed to be the preferred active conformation. Replacement of the core phenyl ring with a pyridine, and replacement of the 2,3-dichlorobenzenesulfonamide with 5- chlorothiophenesulfonamide provided compound 33 which has excellent physicochemical properties and represents a good starting point for a lead optimisation programme. Electronic structure calculations indicated that the preference for the clip or orthogonal conformation found in the small molecule crystal structures of 7 and 14 was in agreement with the order of potency in the biological assay

Oxazoline Promoted Rh-Catalyzed C-H Amidation of Benzene Derivatives with Sulfonamides and Trifluoroacetamide. A Comparative Study.

A Rh-catalyzed ortho-amidation of 2-aryloxazolines offers an efficient and direct route to a range of sulfonamides. The scope of the reaction is very broad with respect to sulfonamide substrate, but the position and electronic nature of the substituents on the aryl moiety of the oxazoline lead to a surprising modulation of reactivity. The reactivity of sulfonamides in comparison to trifluoroacetamide is compared, the latter undergoing Rh-catalyzed amidation more rapidly

Biophysical modeling of a cochlear implant system: progress on closed-loop design using a novel patient-specific evaluation platform

The modern cochlear implant is one of the most successful neural stimulation devices, which partially mimics the workings of the auditory periphery. In the last few decades it has created a paradigm shift in hearing restoration of the deaf population, which has led to more than 324,000 cochlear implant users today. Despite its great success there is great disparity in patient outcomes without clear understanding of the aetiology of this variance in implant performance. Furthermore speech recognition in adverse conditions or music appreciation is still not attainable with today's commercial technology. This motivates the research for the next generation of cochlear implants that takes advantage of recent developments in electronics, neuroscience, nanotechnology, micro-mechanics, polymer chemistry and molecular biology to deliver high fidelity sound. The main difficulties in determining the root of the problem in the cases where the cochlear implant does not perform well are two fold: first there is not a clear paradigm on how the electrical stimulation is perceived as sound by the brain, and second there is limited understanding on the plasticity effects, or learning, of the brain in response to electrical stimulation. These significant knowledge limitations impede the design of novel cochlear implant technologies, as the technical specifications that can lead to better performing implants remain undefined. The motivation of the work presented in this thesis is to compare and contrast the cochlear implant neural stimulation with the operation of the physiological healthy auditory periphery up to the level of the auditory nerve. As such design of novel cochlear implant systems can become feasible by gaining insight on the question `how well does a specific cochlear implant system approximate the healthy auditory periphery?' circumventing the necessity of complete understanding of the brain's comprehension of patterned electrical stimulation delivered from a generic cochlear implant device. A computational model, termed Digital Cochlea Stimulation and Evaluation Tool (‘DiCoStET’) has been developed to provide an objective estimate of cochlear implant performance based on neuronal activation measures, such as vector strength and average activation. A patient-specific cochlea 3D geometry is generated using a model derived by a single anatomical measurement from a patient, using non-invasive high resolution computed tomography (HRCT), and anatomically invariant human metrics and relations. Human measurements of the neuron route within the inner ear enable an innervation pattern to be modelled which joins the space from the organ of Corti to the spiral ganglion subsequently descending into the auditory nerve bundle. An electrode is inserted in the cochlea at a depth that is determined by the user of the tool. The geometric relation between the stimulation sites on the electrode and the spiral ganglion are used to estimate an activating function that will be unique for the specific patient's cochlear shape and electrode placement. This `transfer function', so to speak, between electrode and spiral ganglion serves as a `digital patient' for validating novel cochlear implant systems. The novel computational tool is intended for use by bioengineers, surgeons, audiologists and neuroscientists alike. In addition to ‘DiCoStET’ a second computational model is presented in this thesis aiming at enhancing the understanding of the physiological mechanisms of hearing, specifically the workings of the auditory synapse. The purpose of this model is to provide insight on the sound encoding mechanisms of the synapse. A hypothetical mechanism is suggested in the release of neurotransmitter vesicles that permits the auditory synapse to encode temporal patterns of sound separately from sound intensity. DiCoStET was used to examine the performance of two different types of filters used for spectral analysis in the cochlear implant system, the Gammatone type filter and the Butterworth type filter. The model outputs suggest that the Gammatone type filter performs better than the Butterworth type filter. Furthermore two stimulation strategies, the Continuous Interleaved Stimulation (CIS) and Asynchronous Interleaved Stimulation (AIS) have been compared. The estimated neuronal stimulation spatiotemporal patterns for each strategy suggest that the overall stimulation pattern is not greatly affected by the temporal sequence change. However the finer detail of neuronal activation is different between the two strategies, and when compared to healthy neuronal activation patterns the conjecture is made that the sequential stimulation of CIS hinders the transmission of sound fine structure information to the brain. The effect of the two models developed is the feasibility of collaborative work emanating from various disciplines; especially electrical engineering, auditory physiology and neuroscience for the development of novel cochlear implant systems. This is achieved by using the concept of a `digital patient' whose artificial neuronal activation is compared to a healthy scenario in a computationally efficient manner to allow practical simulation times.Open Acces

Discovery of AZD3199, an inhaled ultralong acting β2 receptor agonist with rapid onset of action

A series of dibasic des-hydroxy β2 receptor agonists has been prepared and evaluated for potential as inhaled ultra-long acting bronchodilators. Determination of activities at the human β-adrenoreceptors demonstrated a series of highly potent and selective β2 receptor agonists that were progressed to further study in a guinea pig histamine-induced bronchoconstriction model. Following further assessment by; onset studies in guinea pig tracheal rings and human bronchial rings contracted with methacholine (guinea pigs) or carbachol (humans), duration of action studies in guinea pigs after intratracheal (i. t.) administration and further selectivity and safety profiling AZD3199 was shown to have an excellent over all profile and was progressed into clinical evaluation as a new ultra-long acting inhaled β2 receptor agonist with rapid onset of action

Voltage control in LV networks: An initial investigation

The installation of small-scale photovoltaic (PV) systems in European low voltage (LV) networks is continuously increasing given the attractive incentives adopted by countries such as the UK and Germany. In many cases, these installations are clustered in the same feeder or LV network, potentially resulting in voltage rise issues. To address this in a flexible way, here it is proposed the real-time intelligent control of LV on-load tap changer (OLTC)-fitted transformers to regulate voltages at the LV feeders. The performance of the proposed control logic is investigated adopting remote voltage monitoring of the end points as well as estimated values. The proposed control logic is applied to a real UK LV network considering one-minute simulations for a day. The results of both the monitoring and estimation-based approaches are compared for different PV penetrations. The control logic with remote monitoring successfully kept voltages of customers within the EN50160 standard. A strong performance was also shown when using estimated values. This highlights the potential applicability of such an approach

On the effects of monitoring and control settings on voltage control in PV-rich LV networks

(accepted) Adopting on-load tap changer (OLTC)-fitted transformers in low voltage (LV) networks can be a potential solution to counteract voltage rise caused by high penetrations of residential photovoltaic (PV) systems. To efficiently control the OLTC network monitoring might be considered. This work assesses the performance of a proposed OLTC control logic considering different remote monitoring schemes and control cycles. A Monte Carlo-based time-series analysis is applied to a real UK residential LV network considering different uneven PV penetrations per feeder. Results show that the adoption of monitoring only at the end of each feeder can provide a satisfactory performance of customer voltages (BS EN50160 compliant). Additionally, the proposed control logic with a 30-minute control cycle can reduce the number of tap changes whilst producing a good voltage performance. The results can help distribution network operators determining the most adequate control approaches for OLTC-fitted transformers in future LV networks

Women’s Political Capabilities as Mediators of Leadership and People Satisfaction

Despite a much lower proportion than men, in both business and politics, a 2018 Pew Research Center survey shows that majorities in the U.S.A. say women leaders in comparison to men are more compassionate and empathetic in working out compromises and in standing up for their beliefs. Via the resource-based view tool, the researchers examine these specific capabilities (i.e., political proposals that benefit society, humanitarian causes, and political ideas) of U.S. women politicians and men politicians, while separately attempting to validate public perceptions of leadership. Using correlation analysis, the study tests the effect of each capability on leadership and people satisfaction. Data were collected from 80 U.S. politicians (40 women and 40 men) from State and Local Governments. The survey took place between 2 October and 5 December 2017. The results show that “women politicians’ ability to build humanitarian political proposals” has a statistically significant strong positive impact on “leadership”, while “women politicians’ ability to build political proposals to benefit society” has a statistically significant strong positive impact on “people satisfaction”. Putting the gender equality argument aside, the study suggests that women, in any case, deserve much more than a “one in four” political participation, even if only in the name of collective decision-making for the common good. Thus, it is important for more women voters to be actively involved and participate in politics and political decision-making in the context of democratic governments and elected politicians. Managerial implications and academic guidance are provided for future research