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Recent trends towards privacy-preservation in Internet of Things, its challenges and future directions

IET CIRCUITS DEVICES & SYSTEMS 2023年第2期17卷 53-61页

作者： Yaraziz, Mahdi Safaei Jalili, Ahmad Gheisari, Mehdi Liu, Yang Islamic Azad Univ Zanjan Branch Dept Comp Engn Zanjan Zanjan Iran Gonbad Kavous Univ Dept Comp Engn Gonbad E Kavus Iran Guangdong Univ Technol Fac Automat Guangzhou Peoples R China Harbin Inst Technol Dept Comp Sci & Technol Shenzhen Peoples R China

The Internet of Things (IoT) is a self-configuring, intelligent system in which autonomous things connect to the Internet and communicate with each other. As 'things' are autonomous, it may raise privacy concerns. In this study, the authors describe the background of IoT systems and privacy and security measures, including (a) approaches to preserving privacy in IoT-based systems, (b) existing privacy solutions, and (c) recommending privacy models for different layers of IoT applications. Based on the results of our study, it is clear that new methods such as Blockchain, Machine Learning, data Minimisation, and data Encryption can greatly impact privacy issues to ensure security and privacy. Moreover, it makes sense that users can protect their personal information easier if there is fewer data to collect, store, and share by smart devices. Thus, this study proposes a machine learning-based data minimisation method that, in these networks, can be very beneficial for privacy-preserving.

关键词： data flow analysis data handling data privacy Internet of Things security of data

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BottleMod: Modeling data flows and Tasks for Fast Bottleneck analysis

BottleMod: Modeling Data Flows and Tasks for Fast Bottleneck...

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2022 IEEE International Conference on Big data, Big data 2022

作者： Loser, Ansgar Witzke, Joel Schintke, Florian Scheuermann, Bjorn Tu Darmstadt Germany Zuse Institute Berlin Germany

ISBN: (纸本)9781665480451

In the recent years, scientific workflows gained more and more popularity. In scientific workflows, tasks are typically treated as black boxes. Dealing with their complex interrelations to identify optimization potentials and bottlenecks is therefore inherently hard. The progress of a scientific workflow depends on several factors, including the available input data, the available computational power, and the I/O and network bandwidth. Here, we tackle the problem of predicting the workflow progress with very low overhead. To this end, we look at suitable formalizations for the key parameters and their interactions which are sufficiently flexible to de scribe the input da ta consumption, the computational effort and the output production of the workflow's tasks. At the same time they allow for computationally simple and fast performance predictions, including a bottleneck analysis over the workflow runtime. A piecewise-defined bottleneck function is derived from the discrete intersections of the task models' limiting functions. This allows to estimate potential performance gains from overcoming the bottlenecks and can be used as a basis for optimized resource allocation and workflow execution. © 2022 IEEE.

关键词： data flow analysis

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Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection-based distributed Blockchain systems

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IET SOFTWARE 2023年第4期17卷 742-754页

作者： Cao, Yuanlong Gu, Keyang Wu, Junyi Zou, Xiang Tao, Lei Huang, Xin Jiang, Changgen Jiangxi Normal Univ Sch Software Nanchang 330022 Peoples R China Educ Univ Hong Kong Dept Math & Informat Technol Hong Kong Peoples R China

With the vigorous development of mobile Internet and Blockchain, the rapid and secure interaction of high-frequency data in the era of data explosion has gradually become an urgent need for people. Quick User datagram Protocol Internet Connection Protocol (QUIC) can be perfectly integrated into the Blockchain due to its low latency and high security, providing a safe and reliable transmission service for the Blockchain system. However, QUIC-based distributed Blockchain systems are vulnerable to cyberattacks due to asymmetric encryption and timestamp, which seriously impacts security and fairness. Therefore, based on the self-similarity of QUIC network traffic, this study proposes an anomaly detection model for QUIC network traffic based on Ensemble Empirical Mode Decomposition and Approximate Entropy. The model obtains several intrinsic mode functions and a residual term by decomposing the network traffic, introducing Approximate Entropy to judge the complexity of each component, and using the Hurst parameter to determine the generation of abnormal traffic. Compared with traditional detection methods, the model can effectively overcome the problems of poor adaptive ability and low efficiency and has high accuracy, which can be used for attack detection and prevention of network nodes.

关键词： computer network security data flow analysis software reliability transport protocols

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Optimization of E-commerce platform marketing method and comment recognition model based on deep learning and intelligent blockchain

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IET SOFTWARE 2023年第4期17卷 797-808页

作者： Cheng, Tao Li, Lianjiang Harbin Univ Commerce Sch Comp & Informat Engn Harbin Peoples R China Harbin Univ Commerce Sch Comp & Informat Engn Harbin 150001 Peoples R China

The emergence of the big data era has brought e-commerce live broadcast progressively into people's life. Customers' intentions to make a purchase can be significantly influenced by online comments made during live broadcasts and marketing strategies used by businesses. Therefore, this paper first introduces the Stimulus Organisation Response (SOR) model, explains the application of the SOR model in the experiment, and also introduces the basic situation of the questionnaire used in this study. Second, the deep learning network is described, and an optimised Bi-directional Long Short-Term Memory (Bi-LSTM) model is put forward, through which the emotional tendency of online reviews is analysed. Finally, the validity and rationality of this hypothesis and model are verified by hypothesis experiments and comparative experiments. The premise in this research has been confirmed by the experimental findings, which demonstrate that precision marketing has a beneficial guiding effect on the majority of consumers. Additionally, the F1 values for classifying and identifying good and negative reviews are 92.92% and 93.02%, respectively. This evidences the efficacy and logic of the optimization model used in this research. The study presented in this paper has some reference value for the improvement and development of the comment recognition model.

关键词： big data commerce consumer behaviour data flow analysis Internet of Things

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A case study of environmental considerations and opportunities in cyber physical systems

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IET SOFTWARE 2023年第4期17卷 424-434页

作者： Cortes-Cornax, Mario Lago, Paula Roncancio, Claudia Univ Grenoble Alpes CNRS Inria Grenoble INP Grenoble France Concordia Univ Dept Elect & Comp Engn Montreal PQ Canada SIGMA Team Lab Informat Grenoble IMAG Bldg700 Ave Cent F-38401 St Martin Dheres France

Cyber Physical Systems (CPS) are becoming more ubiquitous, complex and powerful as well as more and more present in our daily life. The inherent benefit and comfort come with an environmental impact at every step of their life-cycle. This impact is significant and unfortunately often ignored today. As cyber-physical systems tend to be 'invisible', there is a need for awareness of the underlying infrastructure and required resources, early in the design phases. In this article, the environmental impact considerations in the early stages of the implementation and opportunities to improve design choices with a people-planet-system perspective are discussed. The authors discuss the aspects related to system configuration, data management and the overall goal and functionalities supported by the CPS. Through a specific smart home case, the potential of considering life-cycle assessment of both the devices and data management is illustrated. By explicitly considering different configurations, it will be possible to analyse the environmental impacts of the design decisions. Our research in progress targets a design approach to converge into an equilibrium between utility, performance, and minor environmental impact of smart systems.

关键词： cyber-physical systems data flow analysis design engineering environmental monitoring (geophysics) Internet of Things ISO standards

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Inference of Error Specifications and Bug Detection Using Structural Similarities 33

Inference of Error Specifications and Bug Detection Using St...

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33rd USENIX Security Symposium

作者： Dossche, Niels Coppens, Bart Univ Ghent Ghent Belgium

ISBN: (纸本)9781939133441

Error-handling code is a crucial part of software to ensure stability and security. Failing to handle errors correctly can lead to security vulnerabilities such as DoS, privilege escalation, and data corruption. We propose a novel approach to automatically infer error specifications for system software without a priori domain knowledge, while still achieving a high recall and precision. The key insight behind our approach is that we can identify error-handling paths automatically based on structural similarities between error-handling code. We use the inferred error specification to detect three kinds of bugs: missing error checks, incorrect error checks, and error propagation bugs. Our technique uses a combination of path-sensitive, flow-sensitive and both intra-procedural and inter-procedural data-flow analysis to achieve high accuracy and great scalability. We implemented our technique in a tool called ESSS to demonstrate the effectiveness and efficiency of our approach on 7 well-tested, widely-used open-source software projects: OpenSSL, OpenSSH, PHP, zlib, libpng, freetype2, and libwebp. Our tool reported 827 potential bugs in total for all 7 projects combined. We manually categorised these 827 issues into 279 false positives and 541 true positives. Out of these 541 true positives, we sent bug reports and corresponding patches for 46 of them. All the patches were accepted and applied.

关键词： data flow analysis

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Concurrent RSSA for CRIL: flow analysis for a Concurrent Reversible Programming Language 16th

Concurrent RSSA for CRIL: Flow Analysis for a Concurrent Rev...

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16th International Conference on Reversible Computation (RC)

作者： Oguchi, Shunya Yuen, Shoji Nagoya Univ Grad Sch Informat Nagoya Aichi Japan

ISBN: (纸本)9783031620751;9783031620768

We present the CRSSA (Concurrent Reversible Static Single Assignment) form for a concurrent reversible intermediate language called CRIL, which the authors proposed. A CRIL program is a collection of basic blocks where each basic block consists of a single 3-address code with labels for forward and backward control flow. CRIL extends RIL by Mogensen, allowing the multiple calls of basic blocks to execute concurrently in forward and backward directions. The operational semantics of CRIL enjoy causal safety and causal liveness as the fundamental correctness for reversibility. RSSA proposed by Mogensen assigns a value to a pair of unique variables for both directions. In addition to phi functions to present bidirectional splits and joins of sequential flow, we incorporate pi functions for possible joins of concurrent flow via shared variables, where the p functions are proposed by Lee et al. to present the joins of the concurrent flow of parallel programs. We extend p functions for the backward execution to present bidirectional splits and joins of CRIL behavior. We give a translation from a CRIL program into a CRSSA form given a bidirectional data flow analysis. We apply the optimization technique using the CRSSA form, such as conditional constant propagation, dead code elimination, and copy propagation to CRIL programs. A CRSSA form is translated back to a CRIL program.

关键词： data flow analysis

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Parrot: Efficient Serving of LLM-based Applications with Semantic Variable 18

Parrot: Efficient Serving of LLM-based Applications with Sem...

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18th USENIX Symposium on Operating Systems Design and Implementation (OSDI)

作者： Lin, Chaofan Han, Zhenhua Zhang, Chengruidong Yang, Yuqing Yang, Fan Chen, Chen Qiu, Lili Shanghai Jiao Tong Univ Shanghai Peoples R China Microsoft Res Redmond WA USA

ISBN: (纸本)9781939133403

The rise of large language models (LLMs) has enabled LLM-based applications (a.k.a. AI agents or co-pilots), a new software paradigm that combines the strength of LLM and conventional software. Diverse LLM applications from different tenants could design complex workflows using multiple LLM requests to accomplish one task. However, they have to use the over-simplified request-level API provided by today's public LLM services, losing essential application-level information. Public LLM services have to blindly optimize individual LLM requests, leading to sub-optimal end-to-end performance of LLM applications. This paper introduces Parrot, an LLM service system that focuses on the end-to-end experience of LLM-based applications. Parrot proposes Semantic Variable, a unified abstraction to expose application-level knowledge to public LLM services. A Semantic Variable annotates an input/output variable in the prompt of a request, and creates the data pipeline when connecting multiple LLM requests, providing a natural way to program LLM applications. Exposing Semantic Variables to the public LLM service allows it to perform conventional data flow analysis to uncover the correlation across multiple LLM requests. This correlation opens a brand-new optimization space for the end-to-end performance of LLM-based applications. Extensive evaluations demonstrate that Parrot can achieve up to an order-of-magnitude improvement for popular and practical use cases of LLM applications.

关键词： data flow analysis

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Lazy Sparse Conditional Constant Propagation in the Sea of Nodes 21

Lazy Sparse Conditional Constant Propagation in the Sea of N...

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21st ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes (MPLR)

作者： Aigner, Christoph Barany, Gergoe Moessenboeck, Hanspeter Johannes Kepler Univ Linz Linz Austria Oracle Labs Vienna Austria

ISBN: (纸本)9798400711183

Conditional constant propagation is a compiler optimization that detects and propagates constant values for expressions in the input program taking unreachable branches into account. It uses a data flow analysis that traverses the program's control flow graph to discover instructions that produce constant values. In this paper we document our work to adapt conditional constant propagation to the Sea of Nodes program representation of GraalVM. In the Sea of Nodes, the program is represented as a graph in which most nodes 'float' and are only restricted by data flow edges. Classical data flow analysis is not possible in this setting because most operations are not ordered and not assigned to basic blocks. We present a novel approach to data flow analysis optimized for the Sea of Nodes. The analysis starts from known constant nodes in the graph and propagates information directly along data flow edges. Most nodes in the graph can never contribute new constants and are therefore never visited, a property we call lazy iteration. Dependences on control flow are taken into account by evaluating SSA.. nodes in a particular order according to a carefully defined priority metric. Our analysis is implemented in the GraalVM compiler. Experiments on the Renaissance benchmark suite show that lazy iteration only visits 20.5 % of all nodes in the graph. With the constants and unreachable branches found by our analysis, and previously undetected by the GraalVM compiler, we achieve an average speedup of 1.4 % over GraalVM's optimized baseline.

关键词： data flow analysis constant propagation compilers optimization Sea of Nodes

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Static analysis of Quantum Programs 31st

Static Analysis of Quantum Programs

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31st International Static analysis Symposium

作者： Assolini, Nicola Di Pierro, Alessandra Mastroeni, Isabella Univ Verona Dipartimento Informat Verona Italy

ISBN: (纸本)9783031747755;9783031747762

In principle, the design and implementation of quantum programming languages are the same essential tasks as for conventional (classical) programming languages. High-level programming constructs and compilation tools are structurally similar in both cases. The difference is mainly in the hardware machine executing the final code, which in the case of quantum programming languages is a quantum processor, i.e. a physical object obeying the laws of quantum mechanics. Therefore, special technical solutions are required to comply with such laws. In this paper, we show how static analysis can guarantee the correct implementation of quantum programs by introducing two data-flow analyses for detecting some 'wrong' uses of quantum variables. A compiler including such analyses would allow for a higher level of abstraction in the quantum language, relieving the programmer of low-level tasks such as the safe removal of temporary variables.

关键词： data flow analysis

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