Location Based Services (LBS) are widely used in VANETs to provide a variety of services for vehicles. The trajectory privacy protection has attracted wide attention. However, there are some shortcomings in the scheme...
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Location Based Services (LBS) are widely used in VANETs to provide a variety of services for vehicles. The trajectory privacy protection has attracted wide attention. However, there are some shortcomings in the schemes proposed at home and abroad. Therefore, this paper proposes a protection scheme based on shadow vehicles. First, the Genetic Algorithm is used to predict the trajectory, and suitable shadow vehicles are selected based on the deviation of the predicted trajectory. Then, a number of fake queries are inserted into the queries of real vehicles and shadow vehicles, finally a query matrix is formed and sent it to the LBS server for query. Fake queries make vehicle’s paths intersect, which can prevent the reverse mapping from vehicle’s identity to query content, so that the attacker can’t distinguish the complete trajectory of the target vehicle and the scheme can prevent continuous query attacks. Experiments have proved that the scheme improves the prediction similarity, the selected shadow vehicles are similar to the predicted trajectory of the real vehicle and the privacy protection of the trajectory is enhanced.
The paper (Compact Routing Messages in Self-Healing Trees, TCS 2017) introduced CompactFTZ, the first self-healing compact routing algorithm that works in a distributed network with each node using only O(log n) words...
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ISBN:
(纸本)9781450377515
The paper (Compact Routing Messages in Self-Healing Trees, TCS 2017) introduced CompactFTZ, the first self-healing compact routing algorithm that works in a distributed network with each node using only O(log n) words (i.e. O(log(2) n) bits) memory and thus O(log n) sized messages. The routing uses only O(1) and O(log n) words routing table and packet labels respectively on a self-healing tree that also works using only O(1) words repairing the network in face of a strong adversary deleting nodes. This deterministic algorithm sets up its data structures in a preprocessing phase and then updates the required data structures in only O(1) parallel time per healing round during execution of the algorithm. However, CompactFTZ has no constraints in its preprocessing phase which could be done in distributed large memory or even centrally. In this paper, we correct that by developing the algorithms for preprocessing of CompactFTZ in a fully distributed manner using only O(log n) words memory in optimal time. In fact, the preprocessing for the self-healing tree (ForgivingTree) component takes only O(1) memory. We develop a local function which each node invokes to instantly compute and then relay its repair instructions (known as its Will) in only O(1) time. We formalise the low memory CONGEST model setting used in previous low memory algorithms (e.g.[24]);nodes' working memory is restricted to be much smaller (in our case, O(log n)) than the numbers of their neighbours to whom they communicate through their I/O ports. We expand the model to allow for non-contiguous ports (e.g. empty ports or neighbours unmarked or lost in dynamic settings) and adversarial order of inputs from neighbours. Besides the Wills, we set up the tree structures and traversals for the routing scheme using only O(log n) memory and O(D) parallel time, where D is the diameter. Thus, we devise the first self-healing compact routing algorithm that can be fully set up and executed in low memory.
This keynote talk will provide an overview of a recent line of work [Rozhoň and Ghaffari at STOC 2020; Ghaffari, Harris, and Kuhn at FOCS 2018; and Ghaffari, Kuhn, and Maus at STOC 2017], which presented the first ef...
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ISBN:
(纸本)9781450389334
This keynote talk will provide an overview of a recent line of work [Rozhoň and Ghaffari at STOC 2020; Ghaffari, Harris, and Kuhn at FOCS 2018; and Ghaffari, Kuhn, and Maus at STOC 2017], which presented the first efficient deterministic network decomposition algorithm as well as a general derandomization result for distributed graph algorithms. Informally, the derandomization result shows that any (locally-checkable) graph problem that admits an efficient randomized distributed algorithm also admits an efficient deterministic distributed algorithm. These results resolve several central and decades-old open problems in distributed graph algorithms.
Practical applications of quantum computers require millions of physical qubits and it will be challenging for individual quantum processors to reach such qubit numbers. It is therefore timely to investigate the resou...
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ISBN:
(数字)9781450384421
ISBN:
(纸本)9781665483902
Practical applications of quantum computers require millions of physical qubits and it will be challenging for individual quantum processors to reach such qubit numbers. It is therefore timely to investigate the resource requirements of quantum algorithms in a distributed setting, where multiple quantum processors are inter-connected by a coherent network. We introduce an extension of the Message Passing Interface (MPI) to enable high-performance implementations of distributed quantum algorithms. In turn, these implementations can be used for testing, debugging, and resource estimation. In addition to a prototype implementation of quantum MPI, we present a performance model for distributed quantum computing, SENDQ. The model is inspired by the classical LogP model, making it useful to inform algorithmic decisions when program-ming distributed quantum computers. Specifically, we consider several optimizations of two quantum algorithms for problems in physics and chemistry, and we detail their effects on performance in the SENDQ model.
COVID-19 pandemic has caused great distress in the lives of many populations. Low-income households are among the most severely impacted groups in the United States and across the globe. Using social media, this paper...
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COVID-19 pandemic has caused great distress in the lives of many populations. Low-income households are among the most severely impacted groups in the United States and across the globe. Using social media, this paper aims to identify and organize the information about the impact of the pandemic on low-income households. We use content analysis to derive an annotation protocol and manually annotate a tweet dataset using this protocol. Furthermore, we use machine learning to learn models from the annotated dataset. We also employ a human-in-the-loop data augmentation procedure to improve the model’s performance for the underrepresented classes. Our results show that using carefully annotated data, automated machine learning models can be trained and employed to identify information relevant to low income households, potentially in real time.
Platforms for distributedcomputing are able to solve complex problems such as radio telescope signal analysis or protein design. However, the distributedcomputing systems are also vulnerable to attacks, especially c...
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ISBN:
(纸本)9781728132341
Platforms for distributedcomputing are able to solve complex problems such as radio telescope signal analysis or protein design. However, the distributedcomputing systems are also vulnerable to attacks, especially considering the fact that some distributed projects reward their participants, so cybercriminals have incentive to sabotage the project for their own gain. The article considers question of distributedcomputing security. We propose to use metastable blockchain protocol to ensure that integrity of data is preserved. We also discuss advantages of metastable blockchain protocol over regular one for the task of mass distributedcomputing. Prototype distributed data processing program was designed for the task of calculating checksums. The program was tested in a controlled virtual machine environment with different checksum algorithms and different number of computing units.
Computer networks and their services have become increasingly dynamic with the introduction of concepts such as Network Functions Virtualization (NFV) and cloud computing. To understand and configure such a complex ne...
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The proceedings contain 53 papers. The topics discussed include: block sizes control for an efficient real time record linkage;run time optimization using a novel implementation of parallel-PSO for real-world applicat...
ISBN:
(纸本)9781728161754
The proceedings contain 53 papers. The topics discussed include: block sizes control for an efficient real time record linkage;run time optimization using a novel implementation of parallel-PSO for real-world applications;deployment of containerized deep learning applications in the cloud;big data storage and analysis for smart farming;a cross-layered interference in multichannel MAC of VANET;an overall statistical analysis of AI tools deployed in cloud computing and networking systems;a distributed large graph coloring algorithm on giraph;a new recurrent neural network fuzzy mean square clustering method;a recommendation approach based on correlation and co-occurrence within social learning network;a re-engineering approach for extension of the tourist guide knowledge base;and bloom filter and its variants for the optimization of MapReduce’s algorithms: a review.
This paper describes new solutions for distributed services management protocols. The new idea will be based on use transformative computing methodology in services securing algorithms. Such solutions will be based on...
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With the application of blockchains in cryptocurrencies, Internet-of-things and smart contracts etc., many attacks on blockchains and related vulnerabilities have been found. In this paper, we propose a conspiracy sch...
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With the application of blockchains in cryptocurrencies, Internet-of-things and smart contracts etc., many attacks on blockchains and related vulnerabilities have been found. In this paper, we propose a conspiracy scheme on permissioned blockchain, Hyperledger Fabric, through the subliminal channel in the digital signature of Gossip message. For the first time, we propose an attack, called denial-of- endorsement (DoE) attack, on the channel where malicious peer nodes deliberately refuse to endorse the transaction proposals from client applications, trying to break down the normal business workflow. Based on our proposed conspiracy scheme, we design a DoE attack conspiracy protocol, which enables malicious peer nodes to secretly conspire to mount a DoE attack on the channel. We also make some mitigation analysis, aiming at helping Hyperledger Fabric users avoid such DoE attacks and eliminate conspiracy.
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