1,346 research outputs found

    A Trust Management Framework for Vehicular Ad Hoc Networks

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    The inception of Vehicular Ad Hoc Networks (VANETs) provides an opportunity for road users and public infrastructure to share information that improves the operation of roads and the driver experience. However, such systems can be vulnerable to malicious external entities and legitimate users. Trust management is used to address attacks from legitimate users in accordance with a user’s trust score. Trust models evaluate messages to assign rewards or punishments. This can be used to influence a driver’s future behaviour or, in extremis, block the driver. With receiver-side schemes, various methods are used to evaluate trust including, reputation computation, neighbour recommendations, and storing historical information. However, they incur overhead and add a delay when deciding whether to accept or reject messages. In this thesis, we propose a novel Tamper-Proof Device (TPD) based trust framework for managing trust of multiple drivers at the sender side vehicle that updates trust, stores, and protects information from malicious tampering. The TPD also regulates, rewards, and punishes each specific driver, as required. Furthermore, the trust score determines the classes of message that a driver can access. Dissemination of feedback is only required when there is an attack (conflicting information). A Road-Side Unit (RSU) rules on a dispute, using either the sum of products of trust and feedback or official vehicle data if available. These “untrue attacks” are resolved by an RSU using collaboration, and then providing a fixed amount of reward and punishment, as appropriate. Repeated attacks are addressed by incremental punishments and potentially driver access-blocking when conditions are met. The lack of sophistication in this fixed RSU assessment scheme is then addressed by a novel fuzzy logic-based RSU approach. This determines a fairer level of reward and punishment based on the severity of incident, driver past behaviour, and RSU confidence. The fuzzy RSU controller assesses judgements in such a way as to encourage drivers to improve their behaviour. Although any driver can lie in any situation, we believe that trustworthy drivers are more likely to remain so, and vice versa. We capture this behaviour in a Markov chain model for the sender and reporter driver behaviours where a driver’s truthfulness is influenced by their trust score and trust state. For each trust state, the driver’s likelihood of lying or honesty is set by a probability distribution which is different for each state. This framework is analysed in Veins using various classes of vehicles under different traffic conditions. Results confirm that the framework operates effectively in the presence of untrue and inconsistent attacks. The correct functioning is confirmed with the system appropriately classifying incidents when clarifier vehicles send truthful feedback. The framework is also evaluated against a centralized reputation scheme and the results demonstrate that it outperforms the reputation approach in terms of reduced communication overhead and shorter response time. Next, we perform a set of experiments to evaluate the performance of the fuzzy assessment in Veins. The fuzzy and fixed RSU assessment schemes are compared, and the results show that the fuzzy scheme provides better overall driver behaviour. The Markov chain driver behaviour model is also examined when changing the initial trust score of all drivers

    Assessing the Role and Regulatory Impact of Digital Assets in Decentralizing Finance

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    This project will explore the development of decentralized financial (DeFi) markets since the first introduction of digital assets created through the application of a form of distributed ledger technology (DLT), known as blockchain, in 2008. More specifically, a qualitative inquiry of the role of digital assets in relation to traditional financial markets infrastructure will be conducted in order to answer the following questions: (i) can the digital asset and decentralized financial markets examined in this thesis co-exist with traditional assets and financial markets, and, if so, (ii) are traditional or novel forms of regulation (whether financial or otherwise) needed or desirable for the digital asset and decentralized financial markets examined herein? The aim of this project will be to challenge a preliminary hypothesis that traditional and decentralized finance can be compatible; provided, that governments and other centralized authorities approach market innovations as an opportunity to improve existing monetary infrastructure and delivery of financial services (both in the public and private sector), rather than as an existential threat. Thus, this thesis seeks to establish that, through collaborating with private markets to identify the public good to which DeFi markets contribute, the public sector can foster an appropriate environment which is both promotive and protective of the public interest without unduly stifling innovation and progress

    SCENARIO DEVELOPMENT FOR URBAN WATER MANAGEMENT PLANNING FOR UNCERTAINTY

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    The urban water sector is confronted with a multitude of challenges. Rapid population growth, changing political landscapes, aging water infrastructures, and the worsening climate crisis are creating a range of uncertainties in the sector around managing water. Scenarios have been used extensively in the environmental domain to plan for and capture uncertainties to develop plausible futures, including the field of urban water management. Scenarios are key in enabling plans and creating roadmaps to attain desired futures. Despite the advantages and opportunities that scenarios offer for planning, they also have limitations; generally, and within the urban water space. Firstly, the growing uncertainty surrounding urban water management systems necessitates a focused review specifically aimed at the use of scenarios in urban water management. This thesis presents a systematic review to empirically investigate the crucial dimensions of urban water scenarios. Through this review, key knowledge gaps are highlighted, and recommendations are proposed to address these gaps. Secondly, scenarios often depict distressing, almost dystopian futures. Though negative future visions help understand the consequences of present trends and aid in anticipating imminent threats, the limited exploration of positive future visions can make it challenging to find the direction to transform. Optimistic scenarios delve into what people want for the future and capture how their aspirations shape them. Imagining positive visions encourage innovative thinking, creates agency, and creates pathways to desired futures. There is therefore a recognition to move towards more positive, desirable futures. This thesis uses a narrative, participatory scenario process, the SEEDS method, to develop positive visions of urban water futures. The Greater Sydney region in New South Wales, Australia is used as a case study to evaluate the applicability of this approach for urban water management. The urban water sector in the Greater Sydney region faces a multitude of challenges including impacts from climate change, managing diverse water supply sources, and meeting future water demand. These challenges create an increasingly uncertain future for the water sector, where the scale and nature of water services needed in the Greater Sydney region can be unclear. Hence, the Greater Sydney region is selected as the case study region to apply the SEEDS method and develop scenarios for urban water management to plan for future uncertainties. Thirdly, only a few scenario studies include surprises, the unexpected events, which make scenarios useful for planning. Challenges around capturing surprises in scenarios include a lack of structured approaches as well as a lack of evaluation of those methods that have been developed. This thesis discusses the effectiveness and suitability of various surprise methods for scenario development. These methods have been applied in the context of the SEEDS method for urban water management. Finally, there is a lack of evaluation of the tools used to cope with surprises as well as a lack of evaluation efforts of urban water management scenario studies. The assessment of the SEEDS approach for urban water management as well as the different surprise methods for scenario development requires evaluation criteria. This thesis develops and presents an evaluation criteria list based on existing literature that captures key criteria required for adequate assessment of the surprise methods and the scenario process. This thesis contributes to the fields of scenario development and urban water management, and the use of surprises within scenarios. Critical gaps in existing urban water management scenario practices are highlighted and key recommendations are proposed to fill the gaps. Through the pilot study and full-scale implementation of a positive-visioning, narrative-based scenario approach - the SEEDS method, the thesis demonstrates that the SEEDS method is applicable for urban water planning and shows potential for use at different stages of water planning. The positive visions generated through the SEEDS method highlight fundamental aspirations for the urban water sector, possible challenges, and conflicts, and discuss pathways to achieve positive future visions. By using in-situ experimentation and engaging participants with expertise in the relevant field, this thesis provides a realistic evaluation of the scenario process and surprise methods. This thesis thus fills the critical gap about the lack of evaluation in urban water management scenario processes by assessing the scenario method using selected evaluation criteria. Further, the thesis contributes towards the development of quality surprise methods through application and evaluation, thus addressing the gap about the lack of evaluation of the methods used to explore surprise events. Finally, the lack of surprises in scenarios is addressed by presenting different methods that can be used to explore surprise events. Guidance is provided to researchers working with scenario development to understand the different surprise methods available and for choosing the appropriate method(s) to plan for uncertain futures

    The Mogadishu Effect: America\u27s Failure-Driven Foreign Policy

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    The October 1993 Battle of Mogadishu, commonly referred to as “Black Hawk Down,” transformed American foreign policy in its wake. One of the largest special operations missions in recent history, the failures in Somalia left not only the United States government and military in shock, but also the American people. After the nation’s most elite fighting forces suffered a nearly 50 percent casualty rate at the hands of Somali warlords during what many Americans thought was a humanitarian operation, Congress and the American people erupted in anger. Although the United States has continued to be seen as an overbearing global peacekeeping force in the thirty years since Somalia, the Battle of Mogadishu served as the turning point for a generational foreign policy shift that significantly limited future global intervention because of the overt publicization of battle’s aftermath in the media, domestic and international reactions, and a fear of repeating the same mistakes elsewhere. The first major American loss of life after the Cold War, the battle and the reaction that followed, known as the “Mogadishu effect,” forced President Clinton to rethink the United States’ role internationally. Clinton and his administration struggled to convince the American people that involvement overseas, especially global peacekeeping, was vital to international order after becoming the world’s sole superpower. Congressional hearings, presidential correspondence, government documents, poll results, and numerous media releases across Clinton’s presidency mark the distinct shift in American foreign policy that took place after Mogadishu. Although he inherited involvement in the United Nations mission in Somalia from George H.W. Bush, the failures in Somalia transformed Clinton’s humanitarian involvement in Haiti, Bosnia, and Rwanda, tarnishing the remainder of his presidency and shifting expectations of significant American involvement in international peacekeeping after the Cold War

    AFSC Resilience Framework in Developing Country

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    Retinoic Acid and proteotoxic stress induce myeloid leukemia progenitors cell death overcoming the protective effects of the bone marrow niche mesenchymal cells

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    The biological issue - Acute myeloid leukemia (AML) is a group of diseases due to chromosomal and genetic mutations that impair myeloid progenitor differentiation. Some leukemic blasts express mutant proteins sensitizing them to pharmacologically induced proteotoxic stresses. Indeed, our lab demonstrated that in the presence of the differentiating agent Retinoic acid, the ER stress inducer Tunicamycin and the oxidative stress inducer Arsenic Trioxide trigger cell death of AML cell lines and primary blasts bearing the FLT3-ITD mutation. Whereas Retinoic acid and Arsenic trioxide are the current therapy for acute promyelocytic leukemia (APL), Tunicamycin has never been used in clinical practice. Therefore, in order to develop a new therapeutic strategy, my Ph.D. project investigated the proteasome inhibitor Bortezomib, which induces ER stress and is already clinically approved for multiple myeloma and mantle cell lymphoma. Results - AML cell lines were treated with low doses of Retinoic Acid (R), Bortezomib (B), and Arsenic Trioxide (A). FLT3-ITD+ cell lines and primary blasts are highly sensitive to the triple combination RBA but not to the single agents. The cytotoxic effect is mostly due to the generation of oxidative stress and the suppression of the pro-survival branches of the Unfolded Protein Response (UPR). Additionally, the role of the bone marrow niche was examined. In an in vitro co-culture system, bone marrow stromal cells (BMSCs) protect AML from RBA toxicity by attenuating oxidative stress. However, pharmacological doses of ascorbic acid (Vit C) used as an adjuvant pro-oxidant agent, tamper with this protection. Importantly, combined treatment efficacy was confirmed in vivo. Furthermore, the combination of RBA with some promising targeted therapies also provided encouraging results. Conclusion - FLT3-ITD+ AML cells are sensitive to RBA combination. Notably, the bone marrow niche can protect leukemic blasts from oxidative stress, but additional Vit C hampers this protective effect. These results stress the importance of studying AML in the context of the bone marrow niche and open to possible applications in AML treatment

    SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient

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    Many deep learning applications benefit from using large models with billions of parameters. Training these models is notoriously expensive due to the need for specialized HPC clusters. In this work, we consider alternative setups for training large models: using cheap "preemptible" instances or pooling existing resources from multiple regions. We analyze the performance of existing model-parallel algorithms in these conditions and find configurations where training larger models becomes less communication-intensive. Based on these findings, we propose SWARM parallelism, a model-parallel training algorithm designed for poorly connected, heterogeneous and unreliable devices. SWARM creates temporary randomized pipelines between nodes that are rebalanced in case of failure. We empirically validate our findings and compare SWARM parallelism with existing large-scale training approaches. Finally, we combine our insights with compression strategies to train a large Transformer language model with 1B shared parameters (approximately 13B before sharing) on preemptible T4 GPUs with less than 200Mb/s network.Comment: Accepted to International Conference on Machine Learning (ICML) 2023. 25 pages, 8 figure

    Engineering Systems of Anti-Repressors for Next-Generation Transcriptional Programming

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    The ability to control gene expression in more precise, complex, and robust ways is becoming increasingly relevant in biotechnology and medicine. Synthetic biology has sought to accomplish such higher-order gene regulation through the engineering of synthetic gene circuits, whereby a gene’s expression can be controlled via environmental, temporal, or cellular cues. A typical approach to gene regulation is through transcriptional control, using allosteric transcription factors (TFs). TFs are regulatory proteins that interact with operator DNA elements located in proximity to gene promoters to either compromise or activate transcription. For many TFs, including the ones discussed here, this interaction is modulated by binding to a small molecule ligand for which the TF evolved natural specificity and a related metabolism. This modulation can occur with two main phenotypes: a TF shows the repressor (X+) phenotype if its binding to the ligand causes it to dissociate from the DNA, allowing transcription, while a TF shows the anti-repressor (XA) phenotype if its binding to the ligand causes it to associate to the DNA, preventing transcription. While both functional phenotypes are vital components of regulatory gene networks, anti-repressors are quite rare in nature compared to repressors and thus must be engineered. We first developed a generalized workflow for engineering systems of anti-repressors from bacterial TFs in a family of transcription factors related to the ubiquitous lactose repressor (LacI), the LacI/GalR family. Using this workflow, which is based on a re-routing of the TF’s allosteric network, we engineered anti-repressors in the fructose repressor (anti-FruR – responsive to fructose-1,6-phosphate) and ribose repressor (anti-RbsR – responsive to D-ribose) scaffolds, to complement XA TFs engineered previously in the LacI scaffold (anti-LacI – responsive to IPTG). Engineered TFs were then conferred with alternate DNA binding. To demonstrate their utility in synthetic gene circuits, systems of engineered TFs were then deployed to construct transcriptional programs, achieving all of the NOT-oriented Boolean logical operations – NOT, NOR, NAND, and XNOR – in addition to BUFFER and AND. Notably, our gene circuits built using anti-repressors are far simpler in design and, therefore, exert decreased burden on the chassis cells compared to the state-of-the-art as anti-repressors represent compressed logical operations (gates). Further, we extended this workflow to engineer ligand specificity in addition to regulatory phenotype. Performing the engineering workflow with a fourth member of the LacI/GalR family, the galactose isorepressor (GalS – naturally responsive to D-fucose), we engineered IPTG-responsive repressor and anti-repressor GalS mutants in addition to a D-fucose responsive anti-GalS TF. These engineered TFs were then used to create BANDPASS and BANDSTOP biological signal processing filters, themselves compressed compared to the state-of-the-art, and open-loop control systems. These provided facile methods for dynamic turning ‘ON’ and ‘OFF’ of genes in continuous growth in real time. This presents a general advance in gene regulation, moving beyond simple inducible promoters. We then demonstrated the capabilities of our engineered TFs to function in combinatorial logic using a layered logic approach, which currently stands as the state-of-the art. Using our anti-repressors in layered logic had the advantage of reducing cellular metabolic burden, as we were able to create the fundamental NOT/NOR operations with fewer genetic parts. Additionally, we created more TFs to use in layered logic approaches to prevent cellular cross-talk and minimize the number of TFs necessary to create these gene circuits. Here we demonstrated the successful deployment of our XA-built NOR gate system to create the BUFFER, NOT, NOR, OR, AND, and NAND gates. The work presented here describes a workflow for engineering (i) allosteric phenotype, (ii) ligand selectivity, and (iii) DNA specificity in allosteric transcription factors. The products of the workflow themselves serve as vital tools for the construction of next-generation synthetic gene circuits and genetic regulatory devices. Further, from the products of the workflow presented here, certain design heuristics can be gleaned, which should better facilitate the design of allosteric TFs in the future, moving toward a semi-rational engineering approach. Additionally, the work presented here outlines a transcriptional programming structure and metrology which can be broadly adapted and scaled for future applications and expansion. Consequently, this thesis presents a means for advanced control of gene expression, with promise to have long-reaching implications in the future.Ph.D

    NPTSN:RL-Based Network Planning with Guaranteed Reliability for In-Vehicle TSSDN

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    To achieve strict reliability goals with lower redundancy cost, Time-Sensitive Software-Defined Networking (TSSDN) enables run-time recovery for future in-vehicle networks. While the recovery mechanisms rely on network planning to establish reliability guarantees, existing network planning solutions are not suitable for TSSDN due to its domain-specific scheduling and reliability concerns. The sparse solution space and expensive reliability verification further complicate the problem. We propose NPTSN, a TSSDN planning solution based on deep Reinforcement Learning (RL). It represents the domain-specific concerns with the RL environment and constructs solutions with an intelligent network generator. The network generator iteratively proposes TSSDN solutions based on a failure analysis and trains a decision-making neural network using a modified actor-critic algorithm. Extensive performance evaluations show that NPTSN guarantees reliability for more test cases and shortens the decision trajectory compared to state-of-the-art solutions. It reduces the network cost by up to 6.8x in the performed experiments

    A new algorithm to enhance security against cyber threats for internet of things application

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    One major problem is detecting the unsuitability of traffic caused by a distributed  denial of services (DDoS) attack produced by third party nodes, such as smart phones and other handheld Wi-Fi devices. During the transmission between the devices, there are rising in the number of cyber attacks on systems by using negligible packets, which lead to suspension of the services between source and destination, and can find the vulnerabilities on the network. These vulnerable issues have led to a reduction in the reliability of networks and a reduction in consumer confidence. In this paper, we will introduce a new algorithm called rout attack with detection algorithm (RAWD) to reduce the affect of any attack by checking the packet injection, and to avoid number of cyber attacks being received by the destination and transferred through a determined path or alternative path based on the problem. The proposed algorithm will forward the real time traffic to the required destination from a new alternative backup path which is computed by it before the attacked occurred. The results have showed an improvement when the attack occurred and the alternative path has used to make sure the continuity of receiving the data to the main destination without any affection
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