Detection of Lying Electrical Vehicles in Charging Coordination Application Using Deep Learning

The simultaneous charging of many electric vehicles (EVs) stresses the distribution system and may cause grid instability in severe cases. The best way to avoid this problem is by charging coordination. The idea is that the EVs should report data (such as state-of-charge (SoC) of the battery) to run a mechanism to prioritize the charging requests and select the EVs that should charge during this time slot and defer other requests to future time slots. However, EVs may lie and send false data to receive high charging priority illegally. In this paper, we first study this attack to evaluate the gains of the lying EVs and how their behavior impacts the honest EVs and the performance of charging coordination mechanism. Our evaluations indicate that lying EVs have a greater chance to get charged comparing to honest EVs and they degrade the performance of the charging coordination mechanism. Then, an anomaly based detector that is using deep neural networks (DNN) is devised to identify the lying EVs. To do that, we first create an honest dataset for charging coordination application using real driving traces and information revealed by EV manufacturers, and then we also propose a number of attacks to create malicious data. We trained and evaluated two models, which are the multi-layer perceptron (MLP) and the gated recurrent unit (GRU) using this dataset and the GRU detector gives better results. Our evaluations indicate that our detector can detect lying EVs with high accuracy and low false positive rate

Laboratory- to field-scale investigations to evaluate phosphate amendments and Miscanthus for phytostabilization of lead-contaminated military sites

Doctor of PhilosophyDepartment of AgronomyGanga M. HettiarachchiPotentially toxic substances can contaminate extensive areas of productive land due to military activities. The most common and widespread metal contaminant in military lands is lead (Pb). The main objectives of this study were to evaluate the feasibility of using Miscanthus, a second-generation biofuel crop, for photostabilization of Pb in contaminated military site soils; the effect of soil amendments on Miscanthus growth; and the effects of continual plant growth, nutrient removal and the soil chemical changes induced by Miscanthus growth on soil Pb bioaccessibility. In 2016, we established a field site on a US Army reservation in Fort Riley, KS. Miscanthus was planted in an area with soil total Pb concentration ranging from 900 – 1,500 mg kg⁻¹ and near-neutral soil pH. Five treatments were evaluated: (i) control plots without tillage with existing vegetation, (ii) no-tillage, no additional amendments planted with Miscanthus, (iii) tilled soil, no additional amendments planted with Miscanthus, (iv) tilled soil amended with triple superphosphate (at 5:3 Pb:P molar ratio) planted with Miscanthus, and (v) tilled soil amended with organic P source (class B biosolids applied at 45 Mg/ha ) planted with Miscanthus. Results from three years show that one-time addition of soil amendments to Pb-contaminated soil supports establishing and stabilizing Miscanthus, increasing biomass yield as well as reducing phytoavailability and bioaccessibility of Pb. Plots amended with biosolids had significantly less total Pb uptake, plant tissue Pb concentration, and Pb bioaccessibility, and more soil enzyme activities, organic carbon, and microbial biomass. Controlled-environment greenhouse and laboratory incubation studies were conducted to test selected additional P sources. Additional sources included non-traditional, less soluble types such as struvite and apatite. The greenhouse study aimed to evaluate the effect of Miscanthus growth on bioaccessibility of amended and non-amended soils and the effect of soil amendments on soil-plant transfer of soil Pb over three Miscanthus cuttings. Soil amendments increased dry matter yield in the first cutting. Soils in Miscanthus pots that were amended with biosolids, had significantly lower total Pb uptake, Pb concentration in plant tissues, and Pb bioaccessibility when compared to the control across all cuttings. Overall, the results suggested that Miscanthus can be effectively and safely grown on Pb-contaminated soils amended with biosolids. The incubation study evaluated the effectiveness of various in situ P treatments on reducing Pb bioaccessibility and the effects of different P sources on the speciation of soil Pb over time. X-ray absorption spectroscopy was used to understand treatment-induced changes to soil Pb speciation. Results showed that soil pH decreased slightly for all treatments. Percent of bioaccessible Pb in soils amended with biosolid were significantly (α=0.05) less than the other amendments. The high rate of biosolids (225 Mg ha⁻¹) was the most effective in controlling the bioaccessibility of soil Pb, and the reductions in bioaccessibility ranged from 63 to 76% compared to the control. X-ray absorption spectroscopy results indicated pyromorphite (stable Pb phosphates) phases were the most dominant Pb species in both amended and non-amended soils. The results of these studies suggest that Miscanthus can be grown successfully in Pb-contaminated shooting range soils in combination with organic or inorganic phosphate amendments, while minimizing the associated environmental risks

Analyzing and Detecting Internet of Things Malware Using Residual Static Graph- and String-Based Artifacts

Recently, the Internet of Things (IoT) has become wider and adopted many features from social networks and mainly uses sensing devices technologies, causing a rapid increase in production and adoption. However, security and privacy are serious threats that users usually take precautions to protect their devices and information. Thus, understanding the security shortcomings at first stage will educate IoT users to protect their connected things. Understanding IoT software through analysis, comparison (with other types of malware), and detection (from benign IoT) is an essential problem to mitigate security threats. We focus on two central perspectives, the graph and string representations of the software, typically extracted from the software binaries. First, we look into a comparative study of Android and IoT malware through the lenses of graph measurements. We construct the abstract structures of the malware, using Control Flow Graph (CFG) to represent malware binaries, and use them to conduct an in-depth analysis of malicious graphs. Machine Learning (ML) algorithms are actively used in the process of detecting and classifying malicious software. Toward detection, we use different CFG-based features as mentioned above, and augment them with CFGs of the benign dataset and build a detection system. Furthermore, we classify the IoT malware to their corresponding families. However, adversarial ML attacks on malware detectors are proposed in the literature. For example, Adversarial Examples (AEs) on the CFG can be generated by applying small perturbation to the graph features that force the model to misclassification. Thus, we propose Soteria, a CFG-based AEs detector utilizing deep learning with random walks to construct in-depth features. Moreover, we detect the malicious shell commands by extracting and analyzing the malicious commands of IoT malware. We utilize Natural Language Processing (NLP) for feature generation, followed by a deep learning model to detect malicious commands, hence detecting malware samples

The Mobility Impact in IEEE 802.11p Infrastructureless Vehicular Networks

Vehicular ad hoc networks (VANETs) are an extreme case of mobile ad hoc networks (MANETs). High speed and frequent network topology changes are the main characteristics of vehicular networks. These characteristics lead to special issues and challenges in the network design, especially at the medium access control (MAC) layer. Due to high speed of nodes and their frequent disconnections, it is difficult to design a MAC scheme in VANETs that satisfies the quality-of-service requirements in all networking scenarios. In this thesis, we provide a comprehensive evaluation of the mobility impact on the IEEE 802.11p MAC performance. The study evaluates basic performance metrics such as packet delivery ratio, throughput, and delay, as well as the impact of mobility factors. The study also presents a relation between the mobility factors and the respective medium access behavior. Moreover, a new unfairness problem according to node relative speed is identified for both broadcast and unicast scenarios. To achieve better performance, we propose two dynamic contention window mechanisms to alleviate network performance degradation due to high mobility. Extensive simulation results show the significant impact of mobility on the IEEE 802.11p MAC performance, an identification of a new unfairness problem in the vehicle-to-vehicle (V2V) communications, and the effectiveness of the proposed MAC schemes

Synthesis and evaluation of selected benzimidazole derivatives as potential antimicrobial agents. An investigation into the synthesis of substituted benzimidazoles and their evaluation in vitro for antimicrobial activity.

Microbe resistence is a serious issue, especially as they have become resistant to most well known drugs. Therefore this is considered as a global problem and is now dealt with at a poitical level. Since no new classes of antimicrobial agents have been discovered in the past three deacdes, the development of new drugs is extremely urgent. Therefore the aim of this project was to synthesise derivatives of benzimidazole, and then assesses their antimicrobial activities in vitro by using disc (well) diffusion and MICs tests. A total of 69 benzimidazole derivatives, with substituents at positions 1, 2, and 5, were synthesised, characterised and tested against selected bacteria and fungi. In addition, six bezimidazole silver complexes were prepared and evaluated for their antimicrobial behavior. The SAR showed that the antimicrobial activity of the compounds depended on the substituents attached to the bicyclic heterocycle. Some promising results were obtained. In particular, 5 compounds displayed antibacterial activity against two MRSA strains with MIC values corresponding to ciprofloxacin, which can be considered significant. The compounds have some common features; four possess 5-chloro or 5-bromo substituents; two are derivatives of (S)-2- ethanaminebenzimidazole and the others are derivative of one 2-(chloromethyl)-1Hbenzo[d]imidazole, (1H-benzo[d]imidazol-2-yl)methanethiol and 2-(methoxymethyl)-1-methyl-1H-benzo[d]imidazole. The results from the antifungal screening were very interesting as there were 26 compounds, including two silver complexes, which were potent fungicides against the selected fungal species. They showed equivalent or greater potentency in their MIC values than amphotericin B. In particular, the 5-fluoro, 5-chloro and 5-bromo benzimidazole showed broad spectrum activity.Saudi Culture Bureau and King Saud Universit