Global Data Flow Research Articles

全球数据跨境流动国际法规制现状、问题及解决

全球数据跨境流动国际法规制现状、问题及解决

Long-Arm Jurisdiction in Cross-Border Data Flows: EU-US Gaming and Balancing

In the era of digital economy, the power struggle and legal challenges arising from cross-border data flows have become increasingly prominent, making data governance a focal topic in the international community. Countries are competing and cooperating in formulating rules on cross-border data flows, as this phenomenon becomes more significant with the global popularity and rapid development of big data-based digital products like ChatGPT. As traditional powers in this field, the United States and the European Union have established long-arm jurisdiction systems with unique characteristics and have engaged in multiple rounds of fierce gamesmanship over dominance in global data flow governance standards, while constantly seeking power balance in bilateral cooperation. Through historical research, comparative analysis, and case studies, this paper analyzes and summarizes the governance principles, regulatory models, and competitive and compromising processes of transatlantic data flows, leading to the conclusion that Chinas data governance strategy should balance data security and data freedom, while transforming its approach to regulating data outflows and emphasizing the importance of efficiency values in maintaining data sovereignty. By expanding international cooperation and promoting the signing of regional data flow agreements, China can enhance its voice in the global data governance system.

DetAC: Approach to Detect Access Control Vulnerability in Web Application Based on Sitemap Model with Global Information Representation

Access control vulnerabilities that lead to elevated privileges are among the most dangerous vulnerabilities in Web applications. Most of the existing detection methods use dynamic or static analysis techniques alone, which suffer from high manual involvement, low automation, high leakage rate, low page coverage, and other deficiencies. To this end, this paper proposes a novel access control vulnerability detection method (DetAC) based on a sitemap model with global information representation. This method first constructs a static site-wide sitemap model based on the page link addresses in the Web application source code through static analysis techniques. After that, the application is logged in and executed dynamically with different role users. During this process, execution traces and request parameters are collected and converted into annotations to fill the corresponding edges of the static site-wide sitemap model. Then, the sitemap model with global information representation is obtained. This model can represent both the global control flow and data flow of the application. Then DetAC analyzes the role-based and user-based access control policies of the Web application based on the node reachability and annotated data features of the model. And according to the information such as role, user, and access resources, it generates attack vectors to achieve different roles and the same role of different users to access each other’s resources. Finally, access control vulnerabilities are detected based on the equivalence of the results obtained using attack vector access and normal access to the Web application server. DetAC was validated on five real open-source Web applications, and the results showed that DetAC successfully detected up to 12 access control vulnerabilities, which are more than those of the traditional seven tools. The dynamic analysis page coverage rate was significantly improved during the detection process, reaching an average of 91.37%.

RCEP Basic Security Exceptions for Cross-Border Data Flows and China's Response

With the booming development of digital economy, the cross-border activities of data are becoming more and more frequent. At present, data has become an important national strategic resource in the information age. Rational data flow plays an important role in promoting economic growth, accelerating innovation and facilitating globalization. The current global cross-border data flow regulatory system is in a critical period of formation. In the context of the continuous improvement of the current rules system at the regional level, the Regional Comprehensive Economic Partnership Agreement (RCEP), as an important regional free trade area agreement (FTA), has made new provisions on the cross-border flow of data, and the regional data flow rules represented by RCEP profoundly reflect that the rules of global cross-border data flow should not be completely dominated and formulated by developed economies, and all kinds of sovereign countries All kinds of sovereign countries should have the right to participate and the right to speak in the system. The regulation of global data cross-border flows in the digital economy is not only motivated by economic interests, but more importantly, by the protection of national interests. Therefore, under the current data governance system, China should use RCEP as an external driving force to revise and improve the relevant domestic rules on cross-border data flows, so as to promote the benign development of the data governance system, accelerate the promotion of the free flow of data across borders, strengthen cooperation with the international community, continuously expand the intersection of rules on cross-border data flows, achieve convergence of rules, and promote the Chinese solution for the governance of cross-border data flows.

Cyfrowy nadzór w chińskim modelu autorytarnego kapitalizmu

This paper examines the rise of digital authoritarianism in the 21st century. In this political regime, the state authorities exercise control over society via digital technologies while governing the national economy based chiefly on free-market principles.
 The thesis consists of the statement that the elements of the digital economy, including artificial intelligence, digital platforms, and Internet of Things (IoT) communication, are the critical drivers of surveillance capitalism, characterized by unlimited access to any personal and business data. Subsequently, authoritarian governments benefit from possibilities of digital surveillance, including the control of media and the so-called behavioral surplus. It consequently leads to social manipulation, censorship, Internet shutdowns, and different kinds of punishment of citizens via social rating practices.
 The analysis presents the case study of a model of Chinese digital authoritarianism, taking into account the rising popularity of this kind of regime in other countries, where political power is highly centralized. At the same time, the economic transformation has occurred there due to historical or specific geopolitical conditions.
 The findings show that the development of digital authoritarianism is a consequence of surveillance capitalism, within which there is a global data flow via digital platforms. Although surveillance capitalism takes more sophisticated forms than digital authoritarianism, it still serves the same purposes of pursuing the interests of the political elites and influential market players, and it could be perilous for the democratic freedoms of citizens.

The Influence of RCEP on the Regulation of Cross-Border Data Flow and China's Response

The Regional Comprehensive Economic Partnership Agreement (RCEP), as an important regional Free Trade Area agreement (FTA), provides for new provisions for cross-border data flow. RCEP focuses on the security, which allows cross-border data flow basis on respecting national data sovereignty while setting up basic security exceptions. This respect-based cooperation and co-governance model is different from the "zero-sum game" in Europe and the United States.In addition, the RCEP cross-border data flow clause plays a great significant role in promoting regional digital governance and improving the global data flow rules when the WTO related rules lag behind.As the RCEP contracting party, China should be as the external driving force, on the fundamental of the national security concept to expand the level of open cross-border data flow, form data governance "Chinese template", contribute to digital development and data governance wisdom and Chinese solutions, promote a more inclusive, more open digital pattern of international law.

Scheduling Data Flow between Data Centers Based on Software Defined Network

For intelligent control of network traffic, to solve the problem of low utilization of public network bandwidth, we put forward scheduling data flow between data center based on SDN technology. First, we connect the data center distributed in different locations by wide area network and exchange or share the research data of high performance. Then, the system can sense the utilization and performance of the network bandwidth resources between the data center. Based on the results of perception, we can dynamically adjust and optimize the path of data and maximize the utilization of network link. SDN is a new software based network structure. This paper uses SDN network architecture to schedule the traffic of data center, and constructs a two-layer network suitable for cloud computing and virtualization environment. It realizes the global, dynamic and intelligent data flow.

The central role of laboratory medicine as the integrating element in healthcare services

The central role of laboratory medicine as the integrating element in healthcare services

Data Protection and Transborder Data Flow in the European and Global Context

Very similar to trade barriers, data protection has been an obstacle to free global data flow. The European legal system on cross-border data flow set up by Directive 95/46/EC prohibits transfer of personal data to third countries which do not have an adequate data protection level. With enormous international implications, such a regionally oriented system is heavily dependent on effective monitoring of cross-border data transfer. Due to a lack of proper supervision on data transfer, it encounters many challenges, which forces the European Commission to adopt the contractual model and the corporate law model. Meanwhile, compared with issues like free trade and environmental protection, not much international consensus has been reached on cross-border data protection. As a result, bilateral, regional, and multilateral collaborations between national sovereignties are to be strengthened, to facilitate transborder data flow and to safeguard individuals� right to data protection.

An Efficient Algorithm for Finding Maximum Cycle Packings in Reducible Flow Graphs

Reducible flow graphs occur naturally in connection with flowcharts of computer programs and are used extensively for code optimization and global data flow analysis. In this paper we present an O(n2 log(n2/m)) algorithm for finding a maximum cycle packing in any weighted reducible flow graph with n vertices and m arcs; our algorithm heavily relies on Ramachandran's earlier work concerning reducible flow graphs.

Demand-Driven Data Flow Analysis for Communication Optimization

Exhaustive global array data flow analysis for communication optimization is expensive and considered to be impractical for large programs. This paper proposes a demand-driven analysis approach that reduces the analysis cost by computing only the data flow information related to optimizations. In addition, the analysis cost of our scheme can be effectively managed by trading space for time or compromising precision for time.

Precise concrete type inference for object-oriented languages

Concrete type information is invaluable for program optimization. The determination of concrete types in object-oriented languages is a flow sensitive global data flow problem. It is made difficult by dynamic dispatch (virtual function invocation) and first class functions (and selectors)—the very program structures for whose optimization its results are most critical. Previous work has shown that constraint-based type inference systems can be used to safely approximate concrete types [15], but their use can be expensive and their results imprecise. We present an incremental constraint-based type inference which produces precise concrete type information for a much larger class of programs at lower cost. Our algorithm extends the analysis in response to discovered imprecisions, guiding the analysis' effort to where it is most productive. This produces precise information at a cost proportional to the type complexity of the program. Many programs untypable by previous approaches or practically untypable due to computational expense, can be precisely analyzed by our new algorithm. Performance results, precision, and running time, are reported for a number of concurrent object-oriented programs. These results confirm the algorithm's precision and efficiency.

Compiling dataflow analysis of logic programs

Abstract interpretation is a technique extensively used for global dataflow analyses of logic programs. Existing implementations of abstract interpretation are slow due to interpretive or transforming overhead and the inefficiency in manipulation of global information. Since abstract interpretation mimics standard interpretation, it is a promising alternative to compile abstract interpretation into the framework of the WAM (Warren Abstract Machine) for better performance. In this paper, we show how this approach can be effectively implemented in a low-cost manner. To evaluate the possible benefits of this approach, a prototype dataflow analyzer has been implemented for inference of mode, type and variable aliasing information of logic programs. For a subset of benchmark programs in [15], it significantly improves the performance by a factor of over 150 on the average.

Structured dataflow analysis for arrays and its use in an optimizing compiler

AbstractWe extend the well‐known interval analysis method so that it can be used to gather global flow information for individual array elements. Data dependences between all array accesses in different basic blocks, different iterations of the same loop, and across different loops are computed and represented as labelled arcs in a program flow graph. This approach results in a uniform treatment of scalars and arrays in the compiler and builds a systematic basis from which the compiler can perform numerous global optimizations.This global dataflow analysis is performed as a separate phase in the compiler. This phase only gathers the global relationships between different accesses to a variable, yet the use of this information is left to the code generator. This organization substantially simplifies the engineering of an optimizing compiler and separates the back end of the compiler (e.g. code generator and register allocator) from the flow analysis part.The global dataflow analysis algorithm described in this paper has been implemented and used in an optimizing compiler for a processor with deep pipelines. This paper describes the algorithm and its compact implementation and evaluates it, both with respect to the accuracy of the information and to the compile‐time cost of obtaining and using it.

Anomaly Detection of Functional Programs Based on Global Dataflow Analysis

AbstractThis paper proposes a new anomaly detection algorithm based on the global dataflow analysis, considering the first‐order functional program. The anomaly detection is made concerning two points: the irrelevant object which does not affect the result by evaluation; and the diverged object which will fall in an infinite loop without being terminated if an evaluation is made. The detection algorithm is based on the global functional analysis technique which determines the computation path arriving at the result of computation. Because of this property, the algorithm has a higher detection ability than the cross‐reference analysis, which simply traces the syntactic definition and reference relation. Using the proposed algorithm, the bug which may diverge the computation is detected effectively automatically, and is often produced in the program using a stream which is conceptually an infinite list.

Maximum Pipelining Of Array Computation: A Pipelined Code Mapping Scheme For Dataflow Computers

AbstractDespite the attractive features of data flow computers, skepticism exists concerning their efficiency in handling arrays (vectors) in high performance scientific computation. This paper argues that massive parallelism in vector computation can be exploited effectively utilizing data flow principles. The key is to organize the data flow machine program graph such that array operations can be fully pipelined. Unlike in conventional pipelined vector processors, there is no requirement that the activities belonging to the same vector operation be continuously processed by one or a group of physically tightly-coupled function units in the processor. The applicative nature of the data flow graph model allows flexible scheduling of the execution of enabled instructions in the pipeline data flow programs. Accordingly, program transformation can be performed on the basis of both the global and local data flow analysis to generate efficient pipelined data flow machine code. As a result of such fine-grain pa...

An efficient general iterative algorithm for dataflow analysis

Existing iterative algorithms for global dataflow analysis have demonstrable shortcomings; either they can be used only for a limited class of problems or they are needlessly inefficient in some cases. We review several algorithms, pointing out weaknesses and develop a new algorithm that can be used for a wide class of problems and has a runtime that compares favorably ro runtimes of existing algorithms.

An APL/370 compiler and some performance comparisons with APL interpreter and FORTRAN

The experimental APL/370 E-compiler compiles a subset of APL which is large enough for most scientific and engineering uses, directly into 370 assembly code. The compiler does not require variable declarations. The front-end employs extensive type-shape analysis based on global dataflow analysis. The back-end takes the parse trees, graphs and tables produced by the front-end and generates 370-code which runs independently of the interpreter. The compiled-code executes at 2-10 times the speed of the interpreter on several one-line functions, and this ratio increases significantly with iterative programs. The code quality is comparable to that produced by an optimizing FORTRAN compiler on FORTRAN programs corresponding to our test cases. This removes the performance penalty of APL in computation intensive applications.

Incremental data flow analysis in a structured program editor

For many years, the generally accepted methods for solving global data flow analysis problems (GDFAPs) have relied on the bit vector paradigm [Alle 70] [Kenn 81]. In these algorithms, the information for each variable is represented as a position in a bit vector. These vectors are propagated from node to node during the analysis of the program.This paper investigates a different paradigm for solving GDFAPs. In this strategy, the data flow solution for each variable is computed independently. A new algorithm for solving some GDFAPs is presented here. While it is expected that this algorithm will run slower in the batch compiling environment, there are conditions under which this algorithm can be expected to be superior to those in the bit vector class.

Global Data Flow Analysis Problems Arising in Locally Least-Cost Error Recovery

Localement, la recuperation d'erreur a moindre cout est une technique pour revenir aux erreurs de syntaxe en editant la chaine d'entree au point de detection d'erreur. On suggere un schema pour son implementation dans des analyseurs syntaxiques de transmission recursive, qui en principe renferme un processus de passage de parametre a chaque procedure dans l'analyseur, pour chaque symbole terminal dans la grammaire