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Safety in distributed Sensor networks: A Literature Review 5

Safety in Distributed Sensor Networks: A Literature Review

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5th international conference on Internet of Things, Big Data and security (IoTBDS)

作者： Altenburg, Tobias Bosse, Sascha Turowski, Klaus Otto von Guericke Univ Fac Comp Sci Very Large Business Applicat Lab Magdeburg Germany

ISBN: (纸本)9789897584268

The connectivity megatrend dominates the current social change. The number of networked devices and the resulting amount of data is constantly increasing worldwide. For this reason, the dependability of computer systems is becoming increasingly relevant. Especially in the context of civil infrastructures, the constant availability of computer systems is of great importance. This paper provides a structured overview of the current literary status of safety in distributed sensor networks. Most approaches from the literature focus on the design phase. By the following connection with the existing dependability theory, the potential for the optimization of dependability could be proven.

关键词： Dependability Sensor Network Internet of Things Fault Tolerance Fault Prevention

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Intelligent transportation systems trusted user’s security and privacy

Intelligent transportation systems trusted user’s security ...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE conference on

作者： Priyanka Kaushik Saurabh Pratap Singh Rathore Lakshay Sachdeva Minakshi Poonia Dipti Singh Lovish Bir Dept. of CSE (AIML) CSE-APEX Chandigarh University Chandigarh India Management & Research ICAPSR New Delhi India Dept. of Eng. Math’s & Computing Madhav Institute of Technology & Science Gwalior India Dept. of Management Madhav University Abu Road India

Standard encryption cannot be utilized in practical communications due to time and storage limits. Dedicated lane keeping (DRL) is a technique that helps self-driving cars navigate congested roads by keeping them in a specific lane (CAVs). Researchers have developed separate networks for distinct types of mixed traffic to cut down on the time and effort typically spent on instruction and coordination. A deep reinforcement learning technique boosts the efficiency of each part and the entire fleet. There is a common misconception that the blockchain is a secure database for private information. A distributed database system in which nodes are directly connected to consensus mechanisms. To ensure data integrity, block blocks on a blockchain network use cryptography and other computer safeguards (such as smart contracts and time stamps). Because of its decentralized design, data storage facilitates collaboration. Digitally signed data records can also be checked to ensure they are accurate. Using hashes to connect individual blocks protects data against tampering by hackers. There is no need for a centralized authority or third party to verify the ledger’s accuracy because everyone can access it anytime. The blockchain allows for a transparent, trustworthy, and auditable system sharing information between entities. Like many other industries, transportation may benefit from the broader implementation of blockchain technology. Based on our findings, a state-run blockchain tailored to the transportation industry was developed and made available to the public. Because of blockchain technology, the car-sharing business model may need to be revised. Blockchain technology utilizes a distributed ledger to record transactions in a way that makes it impossible to alter the underlying data while still allowing for fast access for verification and auditing.

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Detection of DDoS Attacks in Software Defined Network using Decision Tree 10

Detection of DDoS Attacks in Software Defined Network using ...

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10th IEEE international conference on Communication systems and Network Technologies, CSNT 2021

作者： Kousar, Heena Mulla, Mohammed Moin Shettar, Pooja Narayan, D.G. School of Computer Science and Engineering KLE Technological University Karnataka Hubli India

ISBN: (纸本)9780738105239

Software Defined networks (SDN) is a programmable network which can be easily managed with a global knowledge of network topology. However, SDN controller is vulnerable to distributed denial of service (DDoS) due to its centralized architecture. DDoS attacks are dangerous and threatening attacks as they flood the controller with large volume of packets. This leads to the failure of SDN controller which is a critical issue of security. In this work, we initially detect the different types of DDoS attacks using classification algorithms for CIC-DDoS 2019 dataset. Next, we capture packets from SDN environment, pre-process the data and apply classification algorithm to detect DDoS attacks using SDN dataset. We create SDN dataset with Mininet emulator and RYU controller using different DDoS tools. The results reveal that decision tree has better performance compared to SVM and Naïve Bayes. © 2021 IEEE.

关键词： Decision trees

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Serverless-DFS: Serverless Federated Learning with Dynamic Forest Strategy 23

Serverless-DFS: Serverless Federated Learning with Dynamic F...

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Proceedings of the 2023 12th international conference on networks, Communication and Computing

作者： Bobin Deng Xinyue Zhang Dan Chia-Tien Lo Department of Computer Science Kennesaw State University USA

ISBN: (纸本)9798400709265

Training large-scale machine learning models typically requires support from High-performance computers (HPCs) or cloud servers. One strategy to reduce the computational burden and alleviate the communication bottleneck of servers or HPCs is to move a subset of training computation to the edge or end-user devices. Federated learning is a distributed training approach that aims to protect the privacy of end-user data. However, most federated learning systems utilize centralized server architecture, which slows down the model training and limits the system's scalability. Many machine learning trainings require high performance while maintaining end-user data security. The state-of-the-art serverless approaches have performance limitations and can be further improved. This paper proposes Serverless-DFS, a serverless federated learning with a dynamic forest strategy, to improve the performance and scalability of federated learning while keeping its privacy protection capability. From the experimental results, our Serverless-DFS approach is observed to have a 63.9X speedup compared to the default server-client method in a large-scale system with 256 clients.

关键词： All-reduce Dynamic Forest Federated Learning Serverless

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A review of cyber securities in smart grid technology 2

A review of cyber securities in smart grid technology

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2nd international conference on Computation, Automation and Knowledge Management, ICCAKM 2021

作者： Kawoosa, Asif Iqbal Prashar, Deepak Lovely Professional University Department of Computer Applications Punjab India

ISBN: (纸本)9781728194912

A Smart Grid (SG) is an electrical infrastructure much like legacy power grid with scalable and pervasive two-way communications, timely control capabilities, large scale integration of distributed resources and efficient use of resources. The SG provides the features of pervasive smart monitoring technologies, automatic equipment fault sensing and self-healing. The features like 'Wireless Automatic Meter Reading' (WAMR), monitoring of power system stability, distributed energy resources optimization and applications of Demand Response system makes it intelligent infrastructure. Given some of these salient features, SGs without any doubt are the future power infrastructure of energy world. A smart grid has ability to connect millions of consumers and devices in a network which demand it to be highly robust, reliable and secure. security is considered as one of the major challenges in the present-day smart grid systems because of its long-range communication on open networks. Cybercriminals, hackers, terrorists are trying to attack this national infrastructure due to their malicious intensions or to get control on the automated energy monitoring and remote controlling for personal gains. This review paper offers a comprehensive survey of understanding of Smart Grids, architecture of SGs, methodologies used, the communication protocols but the focus is mainly on the cyber-attacks carried out and solutions recommended on the smart grids. We finally discuss the various challenges in cyber security, the issues that still exist in the literature and current solution space with future research gap. © 2021 IEEE.

关键词： Network security

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An approach to Improving Columnar Permutation Cipher for Wills in distributed systems of Law Firms 5

An approach to Improving Columnar Permutation Cipher for Wil...

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5th international conference on Future networks and distributed systems: The Premier conference on Smart Next Generation Networking Technologies, ICFNDS 2021

作者： Nwokedi, Emeka Adeniyi Ojerinde, Oluwaseun Ojeniyi, Joseph Adepoju, Solomon Federal University of Technology Minna Department of Computer Science Niger Nigeria

ISBN: (纸本)9781450387347

With the evolution of cryptography in the twentieth century, classical ciphers (transposition ciphers) are gradually being pushed out because it now possesses low security ratings, however we can still salvage them, as they have other desirable and admirable qualities which include: easy of design, medium technical know-how and low computational power and it is to achieve this that this study;"A three layer permutation Cryptosystem using a modification of Transposition cipher and two layers content permutation for Wills"was carried out . The aim of this study is to make columnar transposition more secure and relevant so that companies with low technology budget and know-how be secured from known cryptosystem attack. The method used to achieve the above aim is adding to columnar transposition the technique of rail cipher, this affected the sequence of transposition, and lead to a new encryption equation and function. Cryptanalysis was carried out using various tools (Cryptool 2, Dcode and Countwordsfree) and parameters, using a transposition decoder the cipher text gotten using the traditional transposition cryptosystem decrypted with a hundred percent word and character accuracy whilst using the improved system gave a thirty percent accuracy. © 2021 ACM.

关键词： Cryptography

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Using Synthetic Data to Reduce Model Convergence Time in Federated Learning

Using Synthetic Data to Reduce Model Convergence Time in Fed...

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international conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Fida K. Dankar Nisha Madathil Computer Science program NYUAD Abu Dhabi UAE Information Systems and Security UAEU Al Ain UAE

Federated Learning (FL) is a hot new topic in collaborative training of machine learning problems. It is a privacy-preserving distributed machine learning approach, allowing multiple clients to jointly train a global model under the coordination of a central server, while keeping their sensitive data private. The problem with FL systems is that they require intense communication between the server and clients to achieve the final machine learning model. Such complexity increases with the number of clients participating and the complexity of the model sought. In this paper, we introduce synthetic data generation into FL systems with the intention of reducing the number of iterations required for model convergence. In this novel method, clients generate synthetic datasets modeling their private data. The synthetic datasets are then sent to the central server and are used to generate a cognizant initial model. Our experiments show that such conscious method for generating the initial model lowers the number of iterations by a factor of more than 4 without affecting the model accuracy. As such it enhances the overall efficiency of FL systems.

关键词： Training Federated learning Social networking (online) distributed databases Data models Complexity theory Servers

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DDoS Attack Detection Approaches in on Software Defined Network

DDoS Attack Detection Approaches in on Software Defined Netw...

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international conference on Mathematics, Actuarial Science, computer Science and Statistics (MACS)

作者： Saira Muzafar NZ Jhanjhi Navid Ali Khan Farzeen Ashfaq School of Computer Science SCE Taylor's University Subang Jaya Malaysia

ISBN: (纸本)9781665460729

Software Defined Networking (SDN) is a new network paradigm to address the limitations of vertically integrated conventional networks in context of scalability, Quality of Service, flexibility, and security. SDN isolates the data plane from the control plane and the controller dynamically manages the network activities solely while the switches in the data plane just forward data packets as per the rules set by the controller. With the development of SDN, network security can be done in a more efficient and adaptable way. But the centralized controller, the control-data interface, and the control-application interface are all problems with the way SDN was built from the start. Intruders can use these weaknesses to launch many kinds of attacks to retard the network performance, specifically all layers of SDN architecture are endangered to distributed Denial of Service (DDoS) attacks. In this paper, we discuss the popular DDoS attack detection approaches in SDN such as statistical, blockchain, machine learning and deep learning.

关键词： Deep learning Scalability computer architecture Quality of service Network security Denial-of-service attack Control systems

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Secure Consensus Generation with distributed DoH 50

Secure Consensus Generation with Distributed DoH

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50th IEEE/IFIP Annual international conference on Dependable systems and networks (DSN)

作者： Jeitner, Philipp Shulman, Haya Waidner, Michael Tech Univ Darmstadt Darmstadt Germany Fraunhofer Inst Secure Informat Technol SIT Darmstadt Germany

ISBN: (纸本)9781728172606

Many applications and protocols depend on the ability to generate a pool of servers to conduct majority-based consensus mechanisms and often this is done by doing plain DNS queries. A recent off-path attack [1] against NTP and security enhanced NTP with Chronos [2] showed that relying on DNS for generating the pool of NTP servers introduces a weak link. In this work, we propose a secure, backward-compatible address pool generation method using distributed DNS-over-HTTPS (DoH) resolvers which is aimed to prevent such attacks against server pool generation.

关键词： Servers Proposals Protocols Internet Cryptography computer security

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Department of Computing and Mathematics, Manchester Metropolitan University Manchester, UK 5

Department of Computing and Mathematics, Manchester Metropol...

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5th international conference on Future networks and distributed systems: The Premier conference on Smart Next Generation Networking Technologies, ICFNDS 2021

作者： Alrehaili, Meaad Alshamrani, Adel Eshmawi, Ala Department of Computer Science and Artificial Intelligence University of Jeddah Jeddah Saudi Arabia Department of Cybersecurity University of Jeddah Jeddah Saudi Arabia

ISBN: (纸本)9781450387347

Advanced Persistent Threat (APT) attack is one of the most common and costly destructive attacks on the target system. This attack has become a challenge for companies, governments, and organizations' information security systems. In recent years, methods for detecting and preventing APT attacks that use machine learning or deep learning algorithms to analyze indications and anomalous behaviors in network traffic have become popular. However, due to a lack of typical data from attack campaigns, the APT attack detection approach that uses behavior analysis and evaluation approaches encounter many issues. Network traffic analysis to detect a common APT attack is one of the solutions for dealing with this situation. This paper develops efficient and flexible deep learning models. To analyze huge network traffic, a hybrid deep learning approach that builds two models is used: Stacked Autoencoder with Long Short-Term Memory (SAE-LSTM) and Convolutional Neural networks with Long Short-Term Memory Network (CNN-LSTM) to detect indications of APT attacks. A reliable dataset 'DAPT2020' that covers all APT stages is used to evaluate the proposed approach. The experimental results demonstrate that the hybrid deep learning approach proved to give higher performance than the individual deep learning model in detecting malicious behavior in each APT stage. © 2021 ACM.

关键词： Long short-term memory

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