4,949 research outputs found

    TANDEM: taming failures in next-generation datacenters with emerging memory

    Get PDF
    The explosive growth of online services, leading to unforeseen scales, has made modern datacenters highly prone to failures. Taming these failures hinges on fast and correct recovery, minimizing service interruptions. Applications, owing to recovery, entail additional measures to maintain a recoverable state of data and computation logic during their failure-free execution. However, these precautionary measures have severe implications on performance, correctness, and programmability, making recovery incredibly challenging to realize in practice. Emerging memory, particularly non-volatile memory (NVM) and disaggregated memory (DM), offers a promising opportunity to achieve fast recovery with maximum performance. However, incorporating these technologies into datacenter architecture presents significant challenges; Their distinct architectural attributes, differing significantly from traditional memory devices, introduce new semantic challenges for implementing recovery, complicating correctness and programmability. Can emerging memory enable fast, performant, and correct recovery in the datacenter? This thesis aims to answer this question while addressing the associated challenges. When architecting datacenters with emerging memory, system architects face four key challenges: (1) how to guarantee correct semantics; (2) how to efficiently enforce correctness with optimal performance; (3) how to validate end-to-end correctness including recovery; and (4) how to preserve programmer productivity (Programmability). This thesis aims to address these challenges through the following approaches: (a) defining precise consistency models that formally specify correct end-to-end semantics in the presence of failures (consistency models also play a crucial role in programmability); (b) developing new low-level mechanisms to efficiently enforce the prescribed models given the capabilities of emerging memory; and (c) creating robust testing frameworks to validate end-to-end correctness and recovery. We start our exploration with non-volatile memory (NVM), which offers fast persistence capabilities directly accessible through the processor’s load-store (memory) interface. Notably, these capabilities can be leveraged to enable fast recovery for Log-Free Data Structures (LFDs) while maximizing performance. However, due to the complexity of modern cache hierarchies, data hardly persist in any specific order, jeop- ardizing recovery and correctness. Therefore, recovery needs primitives that explicitly control the order of updates to NVM (known as persistency models). We outline the precise specification of a novel persistency model – Release Persistency (RP) – that provides a consistency guarantee for LFDs on what remains in non-volatile memory upon failure. To efficiently enforce RP, we propose a novel microarchitecture mechanism, lazy release persistence (LRP). Using standard LFDs benchmarks, we show that LRP achieves fast recovery while incurring minimal overhead on performance. We continue our discussion with memory disaggregation which decouples memory from traditional monolithic servers, offering a promising pathway for achieving very high availability in replicated in-memory data stores. Achieving such availability hinges on transaction protocols that can efficiently handle recovery in this setting, where compute and memory are independent. However, there is a challenge: disaggregated memory (DM) fails to work with RPC-style protocols, mandating one-sided transaction protocols. Exacerbating the problem, one-sided transactions expose critical low-level ordering to architects, posing a threat to correctness. We present a highly available transaction protocol, Pandora, that is specifically designed to achieve fast recovery in disaggregated key-value stores (DKVSes). Pandora is the first one-sided transactional protocol that ensures correct, non-blocking, and fast recovery in DKVS. Our experimental implementation artifacts demonstrate that Pandora achieves fast recovery and high availability while causing minimal disruption to services. Finally, we introduce a novel target litmus-testing framework – DART – to validate the end-to-end correctness of transactional protocols with recovery. Using DART’s target testing capabilities, we have found several critical bugs in Pandora, highlighting the need for robust end-to-end testing methods in the design loop to iteratively fix correctness bugs. Crucially, DART is lightweight and black-box, thereby eliminating any intervention from the programmers

    A novel smart contract based blockchain with sidechain for electronic voting

    Get PDF
    Several countries have been researching digital voting methods in order to overcome the challenges of paper balloting and physical voting. The recent coronavirus disease 2019 (COVID-19) epidemic has compelled the remote implementation of existing systems and procedures. Online voting will ultimately become the norm just like unified payments interface (UPI) payments and online banking. With digital voting or electronic voting (e-voting) a small bug can cause massive vote rigging. E-voting must be honest, exact, safe, and simple. E-voting is vulnerable to malware, which can disrupt servers. Blockchain’s end-to-end validation solves these problems. Three smart contracts-voter, candidate, and voting-are employed. The problem of fraudulent actions is addressed using vote coins. Vote coins indicate voter status. Sidechain technology complements blockchain. Sidechains improve blockchain functionality by performing operations outside of blockchains and delivering the results to the mainchain. Thus, storing the encrypted vote on the sidechain and using the decrypted result on the mainchain reduces cost. Building access control policies to grant only authorized users’ access to the votes for counting is made simpler by this authorization paradigm. Results of the approach depict the proposed e-voting system improves system security against replay attacks and reduces the processing cost as well as processing time

    Christian Global Citizenship Education in Korea

    Get PDF
    This practice-based research thesis employs theological action research as a methodology to explore the intersection of Global Citizenship Education (GCED) and public theology, with a specific focus on the contributions of Protestant Christianity. The research objectives are to investigate the relevance of Christianity in public life, its potential influence on GCED within the context of South Korea, and to develop practical tools for promoting the application of Christian values in global citizenship education.GCED is widely promoted by international and national governments, but its implementation faces challenges due to diverse perspectives, historicity, and varying economic and political statuses worldwide. Bridging these differences requires dialogue among different groups to determine the knowledge, skills, attitudes, and values necessary for effective engagement. Within this context, Protestant Christianity offers unique insights and contributions.Through key informant interviews with experienced practitioners in educational settings in South Korea, this practice-based research thesis gathers perspectives on integrating Protestant Christian values in GCED and the role of public theology. Employing theological action research practices, the study develops a refined study guide for Christian Global Citizenship Education, incorporating feedback from key informants to ensure its relevance and alignment with the needs of engaged faith communities. The study guide serves as a practical tool for promoting the application of Christian values in global citizenship education.Overall, this practice-based research underscores the importance of integrating biblical values drawn from reflection on scripture and perspectives from Christianity into global education efforts and encourages active participation in discussions on global citizenship. The research aims to make an original contribution to scholarship in this area by contribute by creating a nuanced approach to GCED rooted in the teachings of Protestant Christianity to bridge gaps between different regions and communities, fostering a more inclusive and nuanced approach to GCED rooted in the teachings of Protestant Christianity. The findings of this research have practical implications for educators, policymakers, and faith communities seeking to incorporate spiritual values into the global citizenship education discourse.<br/

    Protecting Privacy in Indian Schools: Regulating AI-based Technologies' Design, Development and Deployment

    Get PDF
    Education is one of the priority areas for the Indian government, where Artificial Intelligence (AI) technologies are touted to bring digital transformation. Several Indian states have also started deploying facial recognition-enabled CCTV cameras, emotion recognition technologies, fingerprint scanners, and Radio frequency identification tags in their schools to provide personalised recommendations, ensure student security, and predict the drop-out rate of students but also provide 360-degree information of a student. Further, Integrating Aadhaar (digital identity card that works on biometric data) across AI technologies and learning and management systems (LMS) renders schools a ‘panopticon’. Certain technologies or systems like Aadhaar, CCTV cameras, GPS Systems, RFID tags, and learning management systems are used primarily for continuous data collection, storage, and retention purposes. Though they cannot be termed AI technologies per se, they are fundamental for designing and developing AI systems like facial, fingerprint, and emotion recognition technologies. The large amount of student data collected speedily through the former technologies is used to create an algorithm for the latter-stated AI systems. Once algorithms are processed using machine learning (ML) techniques, they learn correlations between multiple datasets predicting each student’s identity, decisions, grades, learning growth, tendency to drop out, and other behavioural characteristics. Such autonomous and repetitive collection, processing, storage, and retention of student data without effective data protection legislation endangers student privacy. The algorithmic predictions by AI technologies are an avatar of the data fed into the system. An AI technology is as good as the person collecting the data, processing it for a relevant and valuable output, and regularly evaluating the inputs going inside an AI model. An AI model can produce inaccurate predictions if the person overlooks any relevant data. However, the state, school administrations and parents’ belief in AI technologies as a panacea to student security and educational development overlooks the context in which ‘data practices’ are conducted. A right to privacy in an AI age is inextricably connected to data practices where data gets ‘cooked’. Thus, data protection legislation operating without understanding and regulating such data practices will remain ineffective in safeguarding privacy. The thesis undergoes interdisciplinary research that enables a better understanding of the interplay of data practices of AI technologies with social practices of an Indian school, which the present Indian data protection legislation overlooks, endangering students’ privacy from designing and developing to deploying stages of an AI model. The thesis recommends the Indian legislature frame better legislation equipped for the AI/ML age and the Indian judiciary on evaluating the legality and reasonability of designing, developing, and deploying such technologies in schools

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

    Get PDF
    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Secure storage systems for untrusted cloud environments

    Get PDF
    The cloud has become established for applications that need to be scalable and highly available. However, moving data to data centers owned and operated by a third party, i.e., the cloud provider, raises security concerns because a cloud provider could easily access and manipulate the data or program flow, preventing the cloud from being used for certain applications, like medical or financial. Hardware vendors are addressing these concerns by developing Trusted Execution Environments (TEEs) that make the CPU state and parts of memory inaccessible from the host software. While TEEs protect the current execution state, they do not provide security guarantees for data which does not fit nor reside in the protected memory area, like network and persistent storage. In this work, we aim to address TEEs’ limitations in three different ways, first we provide the trust of TEEs to persistent storage, second we extend the trust to multiple nodes in a network, and third we propose a compiler-based solution for accessing heterogeneous memory regions. More specifically, ‱ SPEICHER extends the trust provided by TEEs to persistent storage. SPEICHER implements a key-value interface. Its design is based on LSM data structures, but extends them to provide confidentiality, integrity, and freshness for the stored data. Thus, SPEICHER can prove to the client that the data has not been tampered with by an attacker. ‱ AVOCADO is a distributed in-memory key-value store (KVS) that extends the trust that TEEs provide across the network to multiple nodes, allowing KVSs to scale beyond the boundaries of a single node. On each node, AVOCADO carefully divides data between trusted memory and untrusted host memory, to maximize the amount of data that can be stored on each node. AVOCADO leverages the fact that we can model network attacks as crash-faults to trust other nodes with a hardened ABD replication protocol. ‱ TOAST is based on the observation that modern high-performance systems often use several different heterogeneous memory regions that are not easily distinguishable by the programmer. The number of regions is increased by the fact that TEEs divide memory into trusted and untrusted regions. TOAST is a compiler-based approach to unify access to different heterogeneous memory regions and provides programmability and portability. TOAST uses a load/store interface to abstract most library interfaces for different memory regions

    Nonlocal games and their device-independent quantum applications

    Get PDF
    Device-independence is a property of certain protocols that allows one to ensure their proper execution given only classical interaction with devices and assuming the correctness of the laws of physics. This scenario describes the most general form of cryptographic security, in which no trust is placed in the hardware involved; indeed, one may even take it to have been prepared by an adversary. Many quantum tasks have been shown to admit device-independent protocols by augmentation with "nonlocal games". These are games in which noncommunicating parties jointly attempt to fulfil some conditions imposed by a referee. We introduce examples of such games and examine the optimal strategies of players who are allowed access to different possible shared resources, such as entangled quantum states. We then study their role in self-testing, private random number generation, and secure delegated quantum computation. Hardware imperfections are naturally incorporated in the device-independent scenario as adversarial, and we thus also perform noise robustness analysis where feasible. We first study a generalization of the Mermin–Peres magic square game to arbitrary rectangular dimensions. After exhibiting some general properties, these "magic rectangle" games are fully characterized in terms of their optimal win probabilities for quantum strategies. We find that for m×n magic rectangle games with dimensions m,n≄3, there are quantum strategies that win with certainty, while for dimensions 1×n quantum strategies do not outperform classical strategies. The final case of dimensions 2×n is richer, and we give upper and lower bounds that both outperform the classical strategies. As an initial usage scenario, we apply our findings to quantum certified randomness expansion to find noise tolerances and rates for all magic rectangle games. To do this, we use our previous results to obtain the winning probabilities of games with a distinguished input for which the devices give a deterministic outcome and follow the analysis of C. A. Miller and Y. Shi [SIAM J. Comput. 46, 1304 (2017)]. Self-testing is a method to verify that one has a particular quantum state from purely classical statistics. For practical applications, such as device-independent delegated verifiable quantum computation, it is crucial that one self-tests multiple Bell states in parallel while keeping the quantum capabilities required of one side to a minimum. We use our 3×n magic rectangle games to obtain a self-test for n Bell states where one side needs only to measure single-qubit Pauli observables. The protocol requires small input sizes [constant for Alice and O(log n) bits for Bob] and is robust with robustness O(n⁔/ÂČ√Δ), where Δ is the closeness of the ideal (perfect) correlations to those observed. To achieve the desired self-test, we introduce a one-side-local quantum strategy for the magic square game that wins with certainty, we generalize this strategy to the family of 3×n magic rectangle games, and we supplement these nonlocal games with extra check rounds (of single and pairs of observables). Finally, we introduce a device-independent two-prover scheme in which a classical verifier can use a simple untrusted quantum measurement device (the client device) to securely delegate a quantum computation to an untrusted quantum server. To do this, we construct a parallel self-testing protocol to perform device-independent remote state preparation of n qubits and compose this with the unconditionally secure universal verifiable blind quantum computation (VBQC) scheme of J. F. Fitzsimons and E. Kashefi [Phys. Rev. A 96, 012303 (2017)]. Our self-test achieves a multitude of desirable properties for the application we consider, giving rise to practical and fully device-independent VBQC. It certifies parallel measurements of all cardinal and intercardinal directions in the XY-plane as well as the computational basis, uses few input questions (of size logarithmic in n for the client and a constant number communicated to the server), and requires only single-qubit measurements to be performed by the client device

    Cognitive Machine Individualism in a Symbiotic Cybersecurity Policy Framework for the Preservation of Internet of Things Integrity: A Quantitative Study

    Get PDF
    This quantitative study examined the complex nature of modern cyber threats to propose the establishment of cyber as an interdisciplinary field of public policy initiated through the creation of a symbiotic cybersecurity policy framework. For the public good (and maintaining ideological balance), there must be recognition that public policies are at a transition point where the digital public square is a tangible reality that is more than a collection of technological widgets. The academic contribution of this research project is the fusion of humanistic principles with Internet of Things (IoT) technologies that alters our perception of the machine from an instrument of human engineering into a thinking peer to elevate cyber from technical esoterism into an interdisciplinary field of public policy. The contribution to the US national cybersecurity policy body of knowledge is a unified policy framework (manifested in the symbiotic cybersecurity policy triad) that could transform cybersecurity policies from network-based to entity-based. A correlation archival data design was used with the frequency of malicious software attacks as the dependent variable and diversity of intrusion techniques as the independent variable for RQ1. For RQ2, the frequency of detection events was the dependent variable and diversity of intrusion techniques was the independent variable. Self-determination Theory is the theoretical framework as the cognitive machine can recognize, self-endorse, and maintain its own identity based on a sense of self-motivation that is progressively shaped by the machine’s ability to learn. The transformation of cyber policies from technical esoterism into an interdisciplinary field of public policy starts with the recognition that the cognitive machine is an independent consumer of, advisor into, and influenced by public policy theories, philosophical constructs, and societal initiatives
    • 

    corecore