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Zero-interaction authentication 02

Zero-interaction authentication

引用

Proceedings of the 8th annual international conference on Mobile computing and networking

作者： Mark D. Corner Brian D. Noble University of Michigan

ISBN: (纸本)9781581134865

Laptops are vulnerable to theft, greatly increasing the likelihood of exposing sensitive files. Unfortunately, storing data in a cryptographic file system does not fully address this problem. Such systems ask the user to imbue them with long-term authority for decryption, but that authority can be used by anyone who physically possesses the machine. Forcing the user to frequently reestablish his identity is intrusive, encouraging him to disable *** solution to this problem is Zero-Interaction Authentication, or ZIA. In ZIA, a user wears a small authentication token that communicates with a laptop over a short-range, wireless link. Whenever the laptop needs decryption authority, it acquires it from the token; authority is retained only as long as necessary. With careful key management, ZIA imposes an overhead of only 9.3% for representative workloads. the largest file cache on our hardware can be re-encrypted within five seconds of the user's departure, and restored in just over six seconds after detecting the user's return. this secures the machine before an attacker can gain physical access, but recovers full performance before a returning user resumes work.

关键词： stackable file systems cryptographic file systems transient authentication mobile computing

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An Efficient Vehicle Tyre Pressure Monitoring Algorithm Based on Quasi-distributed computing and Recursive Least Squares

An Efficient Vehicle Tyre Pressure Monitoring Algorithm Base...

引用

conference on Vehicle Control and Intelligence (CVCI)

作者： Daolin Zhou Xiangyu Wang Xiaoming Ye Feng Lai Chunlai Zhao Menghao Wei School of Vehicle and Mobility Tsinghua University Beijing China Research&Development Institute DONGFENG Motor Corportion Wuhan China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

Indirect tyre pressure monitoring system (ITPMS) can effectively reduce tyre blowouts risk and enhance high-speed vehicle operation safety, gradually emerging as a rapidly popular-ized on-board electronic control safety product. ITPMS imposes stringent requirements on the memory space and computational capabilities of embedded systems, particularly for cost-sensitive products such as Electronic Stability Program (ESP) and Anti-lock Braking System (ABS). this paper proposes a method utilizing Recursive Least Squares (RLS) for natural frequency identification, transforming spatial requirements into iterative signal demands along the time dimension to mitigate memory usage. Additionally, a quasi-distributed computing architecture (QDCA) is proposed to distribute the natural frequency identifi-cation process across different time segments, thereby enhancing computational efficiency. During the trial and validation process, the proposed method is deployed within ABS. Experimental validation demonstrates that this method achieves equivalent monitoring accuracy while reducing memory usage by 11.2% and enabling natural frequency updates within 500ms.

关键词： Learning systems Time-frequency analysis Embedded systems Memory management Tires Real-time systems Computational efficiency Safety Iterative methods Monitoring

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A distributed Algorithm for Controller Placement in Software Defined Vehicular Networks 2019

A Distributed Algorithm for Controller Placement in Software...

引用

Proceedings of the 2019 8th international conference on Networks, Communication and computing

作者： Junpeng Wang Zhumu Fu Pengju Si Fazhan Tao Henan University of Science and Technology Henan Key Laboratory of Robot and Intelligent Systems Luoyang Henan China School of Information Engineering Henan University of Science and Technology Luoyang Henan China

ISBN: (纸本)9781450377027

With the rise of autonomous driving technology and the growing demand for real-time traffic information, there is a growing demand for Internet of Vehicle (IoV). Vehicle Ad-hoc Network (VANET) is purposed to avoid long-distance data transmission for situations where only local information is needed. However, it is difficult to update the routing protocol in VANET, so the Software Defined Network (SDN) technology is applied to the VANET network. the SDN structure consists of a data layer and a control layer, and how to arrange the control layer structure will affect system performance. In this paper, we approximate the placement problem of the control layer as a facility location problem, and propose a distributed algorithm to better solve this problem. the simulation in the actual problem verifies that the proposed algorithm can effectively solve the problem of the placement of the control layer.

关键词： Internet of Vehicle Software Defined Network Facility Location Problem Vehicle Ad-hoc Network

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SDN-DDoSNet: A Deep Learning Framework for DDoS Attack Detection in Software-Defined Networks

SDN-DDoSNet: A Deep Learning Framework for DDoS Attack Detec...

引用

conference on Information and Communication Technology (CICT)

作者： Abhilash Ojha Ashok Yadav Vrijendra Singh Department of Computer Science Tezpur University Tezpur Assam India Department of Information Technology Indian Institute of Information Technology Allahabad Prayagraj India

ISBN: (数字)9798331531539

ISBN: (纸本)9798331531546

distributed Denial of Service (DDoS) attack is a malicious attempt to disrupt normal web traffic, posing an increasing threat to network infrastructures due to the growing frequency and sophistication of such attacks. this necessitates the development of robust and adaptive defense mechanisms. In this research, we propose a deep learning-based approach for DDoS attack detection, leveraging a Software-Defined Net-working dataset. Our study explores three models: Long-short-term memory,convolutional neural network, and hybrid CNN-LSTM architecture, each designed to capture the temporal and spatial features inherent in network traffic data. the data set includes diverse attack scenarios, including UDP, ICMP, and SYN protocol. the LSTM model achieved an accuracy of 99. 61% in the SDN- DDOS data set, followed by the hybrid model at 99.24%, and the CNN model at 98.86%.

关键词： Deep learning Protocols Neural networks Telecommunication traffic Denial-of-service attack Data models Information and communication technology Computer crime Software defined networking Long short term memory

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A Proactive Data-Parallel Framework for Machine Learning 21

A Proactive Data-Parallel Framework for Machine Learning

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2021 IEEE/ACM 8th international conference on Big Data computing, Applications and Technologies (BDCAT '21)

作者： Guoyi Zhao Tian Zhou Lixin Gao University of Massachusetts Amherst USA University of Massachusetts Amherst USA

ISBN: (纸本)9781450391641

Data parallel frameworks become essential for training machine learning models. the classic Bulk Synchronous Parallel (BSP) model updates the model parameters through pre-defined synchronization barriers. However, when a worker computes significantly slower than other workers, waiting for the slow worker will lead to excessive waste of computing resources. In this paper, we propose a novel proactive data-parallel (PDP) framework. PDP enables the parameter server to initiate the update of the model parameter. that is, we can perform the update at any time without pre-defined update points. PDP not only initiates the update but also determines when to update. the global decision on the frequency of updates will accelerate the training. We further propose asynchronous PDP to reduce the idle time caused by synchronizing parameter updates. We theoretically prove the convergence property of asynchronous PDP. We implement a distributed PDP framework and evaluate PDP with several popular machine learning algorithms including Multilayer Perceptron, Convolutional Neural Network, K-means, and Gaussian Mixture Model. Our evaluation shows that PDP can achieve up to 20X speedup over the BSP model and scale to large clusters.

关键词： stragglers machine learning gradient descent expectation-maximization asynchronous distributed computation

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the Vision of 5G and Cell-Free Communication Networks in Malaysia

The Vision of 5G and Cell-Free Communication Networks in Mal...

引用

international conference on Information Technology and Multimedia (ICIM)

作者： Mohammed Najah Mahdi Khalid Sheikhidris Mohamed Abdul Rahim Ahmad Mohammed Ahmed Subhi Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Malaysia Faculty of Engineering Multimedia University Cyberjaya Malaysia College of Computing & Informatics Universiti Tenaga Nasional Kajang Malaysia Universiti Kebangsaan Malaysia Bangi Malaysia

ISBN: (数字)9781728173108

ISBN: (纸本)9781728173115

5 G cellular networks are supposed to accommodate the ever-increasing data explosion and hyper-dense installation of base stations thanks to their capacity to leverage connectivity and cost-effectiveness. 5G networks can accommodate far more applications concurrently than the existing infrastructure easily and efficiently. this is particularly relevant in view of the fact that the Internet is going to be used by around 41.6 billion linked users by 2025. Many will require guaranteed access to cloud services to function safely, like autonomous vehicle systems and industrial sensors. Whilst 4G networks (which use the Internet Protocol and Wifi, wireless and reaction-based networking) dominated the environment of telecommunications, Artificial intelligence Technology has advanced, along with its numerous sub-categories, including machine learning and deep learning, which was ready for delivering 5G networks for individuals to tackle the decreased bandwidth capacity of 4G. this project encourages us to create location optimization technologies that chooses ideal places for services antennas, ensuring the best potential coverage and use computer training algorithms to distribute resources dynamically to minimise user interference and to save energy.

关键词： Wireless communication Training Wireless sensor networks 5G mobile communication Sensor systems Telecommunications Wireless fidelity

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distributed Misbehavior Detection System for Cooperative Driving Networks

Distributed Misbehavior Detection System for Cooperative Dri...

引用

IEEE international conference on Fog and Edge computing (ICFEC)

作者： Abdullahi Modibbo Abdullahi Wassila Lalouani Department of Computer and Information Science Towson University Towson Maryland USA

ISBN: (数字)9798350361353

ISBN: (纸本)9798350361360

Cooperative Intelligent Transportation Systems (C-ITS) are foundational evolution of vehicular networks, emphasizing the seamless coordination of Vehicle-to-Vehicle communication for exchanging vital information. In C-ITS, vehicles collaborate by distributing V2V messages throughout the network. However, the potential transmission of deceptive or inaccurate information by a malicious vehicle poses a significant risk to road safety. Detecting such malicious data promptly is crucial for taking appropriate actions. Current Misbehavior Detection Systems (MBS) operate with the assumption of a centralized MBS existence, but the challenge lies in empowering vehicles to make local MBS decisions as early as possible. this approach avoids the exchange of all messages with the infrastructure, reducing excessive communication overhead. In response to this challenge, we introduce an innovative distributed misbehavior detection system designed to protect vehicular networks from potential attacks. Our proposed system harnesses the scalability benefits of Federated Learning, allowing vehicles to collaboratively learn a shared model for detecting faulty and malicious messages. Recognizing the impracticality of assuming that all vehicles possess fully labeled data in real-world settings, we propose Fisher-Discriminant Analysis and model regularization to generate an effective pseudo-labeling mechanism. the model regularization proves effective when multiple models from different vehicles produce less-confidence predictions for a given sequence of Basic Safety Messages. Our approach demonstrates efficacy in identifying a broad spectrum of faults and attacks, including rare types, by learning the inherent data distribution and essential network traffic characteristics.

关键词： Training Adaptation models Analytical models Vehicular ad hoc networks Transportation Predictive models Data models Safety Vehicle dynamics Vehicle-to-everything

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Key Safe Algorithms for Blockchain Technologies

Key Safe Algorithms for Blockchain Technologies

引用

international conference on computing Communication Control and Automation (ICCUBEA)

作者： Bhavesh Ingale Amar Buchade Varsha Jadhav Ratna Patil Swapnil Shinde Information Technology Vishwakarma Institute of Information Technology Pune India Artificial Intelligence and Data Science Vishwakarma Institute of Information Technology Pune India

ISBN: (数字)9798350391770

ISBN: (纸本)9798350391787

In the fast-changing world of blockchain tech, keeping cryptographic algorithms secure and efficient is crucial, especially for managing keys in groups. this paper compares three cryptographic algorithms—Shamir's Secret Sharing Scheme, Blakley's Scheme, and the Asmuth-Bloom Scheme—to see how well they work in managing group keys in blockchain systems. We look at how fast they are and how well they resist attacks to understand their strengths and weaknesses in blockchain. Key management is really important for keeping things secure with cryptography, especially in systems like distributed ledgers. We study how long it takes to use Shamir's Secret Sharing, Blakley's Scheme, and the Asmuth-Bloom Scheme in blockchain, showing how efficient and scalable they are, which matters a lot in big distributed systems. We also look at how secure these cryptographic schemes are against different types of attacks, like trying lots of passwords, intercepting messages, working together to attack, and finding vulnerabilities in the system. By focusing on both efficiency and security, we try to get a clear picture of which cryptographic scheme is best for blockchain, especially when managing group keys securely and dynamically. In our research, we found that in terms of speed, Shamir's Secret Sharing Scheme outperforms the Asmuth-Bloom Scheme and Blakley's Scheme, with Shamir being the fastest, followed by Asmuth and then Blakley. However, regarding security, all three schemes demonstrate robustness against various attack vectors. We also discovered that Shamir Secret Sharing Scheme’s efficiency could be further enhanced by implementing Newton's interpolation technique for value interpolation.

关键词： Interpolation distributed ledger Scalability Resists Vectors Robustness Blockchains Velocity measurement Usability Testing

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Traffic-Aware Dynamic Functional Split for 5G Cloud Radio Access Networks

Traffic-Aware Dynamic Functional Split for 5G Cloud Radio Ac...

引用

IEEE conference on Network Softwarization (NetSoft)

作者： Himank Gupta A Antony Franklin Mayank Kumar Bheemarjuna Reddy Tamma Indian Institute of Technology Hyderabad India Indian Institute of Technology Bhilai India

ISBN: (数字)9781665406949

ISBN: (纸本)9781665406956

the recent adaption of virtualization technologies in the next generation mobile network enables 5G base station to be segregated into a Radio Unit (RU), a distributed Unit (DU), and a Central Unit (CU) to support Cloud based Radio Access Networks (C-RAN). RU and DU are connected through a fronthaul link. In contrast, CU and DU are connected through a midhaul link. Although virtualization of CU gives benefits of centralization to the operators, there are other issues to be solved such as optimization of midhaul bandwidth and computing resources at edge cloud and central cloud where the DUs and CUs are deployed, respectively. In this paper, we propose a dynamic functional split selection for the DUs in 5G C-RAN by adopting to traffic heterogeneity where the midhaul bandwidth is limited. We propose an optimization problem that maximizes the centralization of the C-RAN system by operating more number of DUs on split Option-7 by changing the channel bandwidth of the DUs. the dynamic selection of split options among each CU-DU pair gives 90% centralization over the static functional split for a given midhaul bandwidth.

关键词： Cloud computing 5G mobile communication Bandwidth Telecommunication traffic Switches Real-time systems Virtualization

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VATE: Edge-Cloud System for Object Detection in Real-Time Video Streams

VATE: Edge-Cloud System for Object Detection in Real-Time Vi...

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IEEE international conference on Fog and Edge computing (ICFEC)

作者： Maximilian Maresch Stefan Nastic Distributed Systems Group TU Wien

ISBN: (数字)9798350361353

ISBN: (纸本)9798350361360

In the realm of edge intelligence, emerging video analytics applications are often based on resource constrained edge devices. these applications need systems which are able to provide both low-latency and high-accuracy video stream processing, such as for object detection in real-time video streams. State-of-the-art systems tackle this challenge by leveraging edge computing and cloud computing. Such edge-cloud approaches typically combine low-latency results from the edge and high accuracy results from the cloud when processing a frame of the video stream. However, the accuracy achieved so far leaves much room for improvement. Furthermore, using more accurate object detection often requires having more capable hardware. this limits the edge devices which can be used. Applications related to autonomous drones, with the drone being the edge device, give one example. A wide variety of objects needs to be detected reliably for drones to operate safely. Drones with more computing capabilities are often more expensive and suffer from short battery life, as they consume more energy. In this paper, we introduce VATE, a novel edge-cloud system for object detection in real-time video streams. An enhanced approach for edge-cloud fusion is presented, leading to improved object detection accuracy. A novel multi-object tracker is introduced, allowing VATE to run on less capable edge devices. the architecture of VATE enables it to be used when edge devices are capable of running on-device object detection frequently and when edge devices need to minimise on-device object detection to preserve battery life. Its performance is evaluated on a challenging, drone-based video dataset. the experimental results show that VATE improves accuracy by up to 27.5% compared to the state-of-the-art system, while running on less capable and cheaper hardware.

关键词： Cloud computing Accuracy Image edge detection Object detection Streaming media Real-time systems Hardware Low latency communication Drones Edge computing

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