BArcherFuzzer:An Android System Services Fuzzier via Transaction Dependencies of BpBinder

By the analysis of vulnerabilities of Android native system services,we find that some vulnerabilities are caused by inconsistent data transmission and inconsistent data processing logic between client and server.The existing research cannot find the above two types of vulnerabilities and the test cases of them face the problem of low coverage.In this paper,we propose an extraction method of test cases based on the native system services of the client and design a case construction method that supports multi-parameter mutation based on genetic algorithm and priority strategy.Based on the above method,we implement a detection tool-BArcherFuzzer to detect vulnerabilities of Android native system services.The experiment results show that BArcherFuzzer found four vulnerabilities of hundreds of exception messages,all of them were confirmed by Google and one was assigned a Common Vulnerabilities and Exposures(CVE)number(CVE-2020-0363).

Software defined intelligent satellite-terrestrial integrated networks:Insights and challenges

Satellite-Terrestrial integrated Networks(STNs)have been advocated by both academia and industry as a promising network paradigm to achieve service continuity and ubiquity.However,STNs suffer from problems including poor flexibility of network architecture,low adaptability to dynamic environments,the lack of network intelligence,and low resource utilization.To handle these challenges,a Software defined Intelligent STN(SISTN)architecture is introduced.Specifically,the hierarchical architecture of the proposal is described and a distributed deployment scheme for SISTNs controllers is proposed to realize agile and effective network management and control.Moreover,three use cases in SISTNs are discussed.Meanwhile,key techniques and their corresponding solutions are presented,followed by the identification of several open issues in SISTNs including compatibility with existing networks,the tradeoff between network flexibility and performance,and so on.

Performance analysis and comparison of PoW,PoS and DAG based blockchains

In the blockchain,the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks.Various blockchain consensus mechanisms have been proposed.However,there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application.To this end,this work investigates three mainstream consensus mechanisms in the blockchain,namely,Proof of Work(PoW),Proof of Stake(PoS),and Direct Acyclic Graph(DAG),and identifies their performances in terms of the average time to generate a new block,the confirmation delay,the Transaction Per Second(TPS)and the confirmation failure probability.The results show that the consensus process is affected by both network resource(computation power/coin age,buffer size)and network load conditions.In addition,it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.

A Golden Decade of Polar Codes:From Basic Principle to 5G Applications

After the pursuit of seventy years,the invention of polar codes indicates that we have found the first capacity-achieving coding with low complexity construction and decoding,which is the great breakthrough of the coding theory in the past two decades.In this survey,we retrospect the history of polar codes and summarize the advancement in the past ten years.First,the primary principle of channel polarization is investigated such that the basic construction,coding method and the classic successive cancellation(SC)decoding are reviewed.Second,in order to improve the performance of the finite code length,we introduce the guiding principle and conclude five design criteria for the construction,design and implementation of the polar code in the practical communication system based on the exemplar schemes in the literature.Especially,we explain the design principle behind the concatenated coding and rate matching of polar codes in 5G wireless system.Furthermore,the improved SC decoding algorithms,such as SC list(SCL)decoding and SC stack(SCS)decoding etc.,are investigated and compared.Finally,the research prospects of polar codes for the future 6G communication system are explored,including the optimization of short polar codes,coding construction in fading channels,polar coded modulation and HARQ,and the polar coded transmission,namely polar processing.Predictably,as a new coding methodology,polar codes will shine a light on communication theory and unveil a revolution in transmission technology.

Semantic information processing for interoperability in the Industrial Internet of Things

With the advent of the Internet of Everything(IoE),the concept of fully interconnected systems has become a reality,and the need for seamless communication and interoperability among different industrial systems has become more pressing than ever before.To address the challenges posed by massive data traffic,we demonstrate the potentials of semantic information processing in industrial manufacturing processes and then propose a brief framework of semantic processing and communication system for industrial network.In particular,the scheme is featured with task-orientation and collaborative processing.To illustrate its applicability,we provide examples of time series and images,as typical industrial data sources,for practical tasks,such as lifecycle estimation and surface defect detection.Simulation results show that semantic information processing achieves a more efficient way of information processing and exchanging,compared to conventional methods,which is crucial for handling the demands of future interconnected industrial networks.

Intent-based networks for 6G:Insights and challenges

Intent-Based Networks(IBNs),which are originally proposed to introduce Artificial Intelligence(AI)into the sixth-generation(6G)wireless networks,can effectively solve the challenges of traditional networks in terms of efficiency,flexibility,and security.IBNs are mainly used to transform users’business intent into network configuration,operation,and maintenance strategies,which are prominent for designing the AI-enabled 6G networks.In particular,in order to meet the massive,intelligent service demands and overcome the time-varying radio propagation,IBNs can continuously learn and adapt to the time-varying network environment based on the massive collected network data in real-time.From the aspects of both the core network and radio access network,this article comprehensively surveys the architectures and key techniques of IBNs for 6G.In particular,the demonstration platforms of IBNs,such as the Apstra Operating System,Forward Networks Verification Platform,and One Convergence Service Interaction Platform,are presented.Moreover,the industrial development of IBNs is elaborated,including the emerging new products and startups to solve the problems of open data platforms,automated network operations,and preemptive network fault diagnosis.Finally,several open issues and challenges are identified as well to spur future researches.

SERVICES AND COMMUNICATIONS IN FOG COMPUTING

In the current cloud-based Internet-of-Things （IoT） model, smart devices （such as sensors, smartphones） exchange information through the Internet to cooperate and provide services to users, which could be citizens, smart home systems, and industrial applications.

CYBERSPACE SECURITY:FOR A BETTER LIFE AND WORK

With the development and widespread application of information technology and industry,the human society has entered into the information age and people live and work in cyberspace.Cyberspace is the information environment in which mankind lives in the information age and is a collection of all

Proactive Platooning Based on C-V2X to Relieve Congestion at a Signalized Intersection

Nowadays urban traffic congestion becomes a major issue due to the increase in vehicles that lead to more commuting time,accidents,traffic violations,and high fuel consumption.Platooning is a good way to solve traffic congestion because it drives with a smaller inter-vehicle distance than human-driving.This paper proposes proactive platooning based on C-V2X(cellular vehicle-to-everything)to relieve congestion.Proactive platooning reduces the inter-vehicle distance and increases the throughput of signalized intersections through integrating the networked control platooning and computation-centralized platooning.Model and simulation experiments of proactive platooning were conducted to verify the impact of inter-vehicle distance on platooning latency,platooning safety,and traffic throughput.Simulation results show that the optimal inter-vehicle distance under proactive platooning is less than half of human-driving at a signalized intersection.

Fundamental Limitation of Semantic Communications:Neural Estimation for Rate-Distortion

This paper studies the fundamental limit of semantic communications over the discrete memoryless channel.We consider the scenario to send a semantic source consisting of an observation state and its corresponding semantic state,both of which are recovered at the receiver.To derive the performance limitation,we adopt the semantic rate-distortion function(SRDF)to study the relationship among the minimum compression rate,observation distortion,semantic distortion,and channel capacity.For the case with unknown semantic source distribution,while only a set of the source samples is available,we propose a neural-network-based method by leveraging the generative networks to learn the semantic source distribution.Furthermore,for a special case where the semantic state is a deterministic function of the observation,we design a cascade neural network to estimate the SRDF.For the case with perfectly known semantic source distribution,we propose a general Blahut-Arimoto(BA)algorithm to effectively compute the SRDE.Finally,experimental results validate our proposed algorithms for the scenarios with ideal Gaussian semantic source and some practical datasets.

Semantic information processing in industrial networks

The industrial Internet of things(industrial IoT, IIoT) aims at connecting everything, which poses severe challenges to existing wireless communication. To handle the demand for massive access in future industrial networks, semantic information processing is integrated into communication systems so as to improve the effectiveness and efficiency of data transmission. The semantic paradigm is particularly suitable for the purpose-oriented information exchanging scheme in industrial networks. To illustrate its applicability, typical industrial data are investigated, i.e., time series and images. Simulation results demonstrate the superiority of semantic information processing, which achieves a better rate-utility tradeoff than conventional signal processing.

Knowledge Graph Embedding for Hyper-Relational Data

Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper,we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs. Previous models such as Trans（E, H, R） and CTrans R are either insufficient for embedding hyper-relational data or focus on projecting an entity into multiple embeddings, which might not be effective for generalization nor accurately reflect real knowledge. To overcome these issues, we propose the novel model Trans HR, which transforms the hyper-relations in a pair of entities into an individual vector, serving as a translation between them. We experimentally evaluate our model on two typical tasks—link prediction and triple classification.The results demonstrate that Trans HR significantly outperforms Trans（E, H, R） and CTrans R, especially for hyperrelational data.