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检索条件"丛书名=Computer Communications and Networks"

共 4934 条记录，以下是121-130 订阅

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Socially-aware Collaborative Defense System against Bit-Flip Attack in Social Internet of Things and Its Online Assignment Optimization 31

Socially-aware Collaborative Defense System against Bit-Flip...

引用

31st International Conference on computer communications and networks (ICCCN)

作者： Yang, Li-Hsing Huang, Shin-Shan Cheng, Tsai-Ling Kuo, Yi-Ching Kuo, Jian-Jhih Natl Chung Cheng Univ Dept Comp Sci & Informat Engn Chiayi Taiwan

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

A powerful Bit-Flip Attack (BFA), based on Row Hammer Attack (RHA), can precisely flip the most vulnerable bits in the memory system (i.e., DRAM) to crash Convolutional Neural networks (CNNs) run on Internet-of-Things (IoT) devices. However, it is very difficult to detect BFA since most devices are usually with limited computation capability and unaware of the security issue. Therefore, BFA becomes one of the most crucial threats to IoT networks. To this end, we design a novel defense system termed Resilient Dual-mode Defense System (RIDES) to encourage IoT devices with social relationships (i.e., Social IoT (SIoT)) to collaborate on BFA detection in an online manner. Subsequently, a new online problem, Online Computing Unit Assignment Problem (OMAR), is formulated to optimize the total inference rate for detecting BFA. To address OMAR's challenges, we present an online algorithm, Socially-aware Checker Assignment Algorithm (SCAN), to achieve the optimal competitive ratio. Extensive experiment and simulation results manifest that RIDES effectively detects BFA and in average, SCAN increases the total inference rate by 8% 515% and reduces the average overhead per image by 31% 55% compared with other solutions.

关键词： Convolutional neural network bit-flip attack attack detection social internet-of-things network

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VeriBlock: A Blockchain-Based Verifiable Trust Management Architecture with Provable Interactions 31

VeriBlock: A Blockchain-Based Verifiable Trust Management Ar...

引用

31st International Conference on computer communications and networks (ICCCN)

作者： Pal, Shantanu Hill, Ambrose Rabehaj, Tahiry Hitchens, Michael Queensland Univ Technol Sch Comp Sci Brisbane Qld 4000 Australia Meadow Labs Brisbane Qld 4000 Australia Risk Frontiers Sydney NSW 2065 Australia Macquarie Univ Sch Comp Sydney NSW 2109 Australia

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

There has been considerable advancement in the use of blockchain for trust management in large-scale dynamic systems. In such systems, blockchain is mainly used to store the trust score or trust-related information of interactions among the various entities. However, present trust management architectures using blockchain lack verifiable interactions among the entities on which the trust score is calculated. In this paper, we propose a blockchain-based trust management framework that allows independent trust providers to implement different trust metrics on a common set of trust evidence and provide individual trust value. We employ geo-location as proof of interaction. Some of the existing proposals rely upon geo-location data, but they do not support trust calculation by multiple trust providers. Instead, they can only support a centralised system. Our proposed architecture does not depend upon a single centralised third-party entity to ensure trusted interactions. Our architecture is supported by provable interactions that can easily be verified using blockchain. Therefore, it allows a high degree of confidence in trust management by ensuring the actual interactions between the entities. We provide a detailed design and development of the architecture using real-world use case examples. The proof of prototype was implemented on the Ethereum blockchain platform. Experimental results demonstrate that the employment of independent trust providers adequately provides a high degree of trust scores and that the proposed architecture can be used in a real-world environment.

关键词： Blockchain Verifiable interactions Security Trust management Geo-location data

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Security of Machine Learning-Based Anomaly Detection in Cyber Physical Systems 31

Security of Machine Learning-Based Anomaly Detection in Cybe...

引用

31st International Conference on computer communications and networks (ICCCN)

作者： Jadidi, Zahra Pal, Shantanu Nayak, Nithesh K. Selvakkumar, Arawinkumaar Chang, Chih-Chia Beheshti, Maedeh Jolfaei, Alireza Queensland Univ Technol Sch Comp Sci Brisbane Qld 4000 Australia Crit Path Inst Tucson AZ 85718 USA Macquarie Univ Sch Comp Sci Sydney NSW 2109 Australia

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

With the emergence of the Internet of Things (IoT) and Artificial Intelligence (AI) services and applications in the Cyber Physical Systems (CPS), the methods of protecting CPS against cyber threats is becoming more and more challenging. Various security solutions are implemented to protect CPS networks from cyber attacks. For instance, Machine Learning (ML) methods have been deployed to automate the process of anomaly detection in CPS environments. The core of ML is deep learning. However, it has been found that deep learning is vulnerable to adversarial attacks. Attackers can launch the attack by applying perturbations to input samples to mislead the model, which results in incorrect predictions and low accuracy. For example, the Fast Gradient Sign Method (FGSM) is a white-box attack that calculates gradient descent oppositely to maximize the loss and generates perturbations by adding the gradient to unpolluted data. In this study, we focus on the impact of adversarial attacks on deep learning-based anomaly detection in CPS networks and implement a mitigation approach against the attack by retraining models using adversarial samples. We use the Bot-IoT and Modbus IoT datasets to represent the two CPS networks. We train deep learning models and generate adversarial samples using these datasets. These datasets are captured from IoT and Industrial IoT (IIoT) networks. They both provide samples of normal and attack activities. The deep learning model trained with these datasets showed high accuracy in detecting attacks. An Artificial Neural Network (ANN) is adopted with one input layer, four intermediate layers, and one output layer. The output layer has two nodes representing the binary classification results. To generate adversarial samples for the experiment, we used a function called the 'fast gradient method' from the Cleverhans library. The experimental result demonstrates the influence of FGSM adversarial samples on the accuracy of the predictions and proves th

关键词： Cyber physical systems Machine learning Security Attacks Defence Internet of Things

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Graph Representation of computer Network Resources for Precise Allocations 31

Graph Representation of Computer Network Resources for Preci...

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31st International Conference on computer communications and networks (ICCCN)

作者： Baxley, Stuart Gurkan, Deniz Validi, Hamidreza Hicks, Illya Univ Houston Dept Comp Sci Houston TX 77004 USA Univ Houston Dept Engn Technol Houston TX 77004 USA Rice Univ Dept Computat & Appl Math Houston TX USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Distributed networked systems form an essential resource for computation and applications ranging from commercial, military, scientific, and research communities. Allocation of resources on a given infrastructure is realized through various mapping systems that are tailored towards specific use cases of the requesting applications. While HPC system requests demand compute resources heavy on processor and memory, cloud applications may demand distributed web services that are composed of networked processing and some memory. All resource requests allocate on the infrastructure with some form of network connectivity. However, during mapping of resources, the features and topology constraints of network components are typically handled indirectly through abstractions of user requests. This paper is on a novel graph representation that enables precise mapping methods for distributed networked systems. The proposed graph representations are demonstrated to allocate specific network components and adjacency requirements of a requested graph on a given infrastructure. Furthermore, we report on application of business policy requirements that resulted in increased utilization and a gradual decrease in idle node count as requests are mapped using our proposed methods.

关键词： Industries Costs Web services Network topology Military computing Energy efficiency Distance measurement

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Mobility-aware Software-Defined Service-Centric Networking 31

Mobility-aware Software-Defined Service-Centric Networking

引用

31st International Conference on computer communications and networks (ICCCN)

作者： Rodrigues, Diego O. Braun, Torsten Maia, Guilherme Villas, Leandro Univ Estadual Campinas Inst Comp Campinas SP Brazil Univ Bern Inst Comp Sci Bern Switzerland Univ Fed Minas Gerais Dept Comp Sci Belo Horizonte MG Brazil

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Future Internet applications, such as the vehicular use cases, impose requirements that challenge current networking paradigms. Hence, other networking paradigms have been proposed, such as Software-Defined Networking (SDN) and Information-Centric Networking (ICN), aiming to change network management and operation fundamentals to meet those requirements. Leveraging these networking paradigms, in this paper we present the Mobility-aware Service-Centric Networking (MSCN), an ICN-inspired solution to mitigate mobility-related networking issues by focusing on service provisioning rather than content. Due to the requirement of installing specialized hardware, ICN-based solutions face adoption issues. Still, SDN features can be used to emulate ICN behaviour without the requirement for deployment of new infrastructure. Therefore, we present an SDN-based implementation of MSCN (SD-MSCN), which relies on already installed SDN-enabled switches and the OpenFlow protocol. We evaluate the performance of our proposal by comparing SD-MSCN with other SDN-enabled ICN and IP protocols. Simulations show that our proposal outperforms IP-based solutions in the presence of user mobility events. Nevertheless, it is possible to produce proactive IP-based solutions that achieve similar performance as our proposal. However, our proposal has a significantly better performance than IP-based solutions in environments with frequent service mobility events.

关键词： Software-Defined Networking Information-Centric Networking User Mobility Service Mobility Handover Service Migration

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Evolved IoT Malware Detection using Opcode Category Sequence through Machine Learning 31

Evolved IoT Malware Detection using Opcode Category Sequence...

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31st International Conference on computer communications and networks (ICCCN)

作者： Moon, Sunghyun Kim, Youngho Lee, Hyunjong Kim, Donghoon Hwang, Doosung Dankook Univ Yongin South Korea GI VITA Seoul South Korea KSign Seoul South Korea Arkansas State Univ Jonesboro AR USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

IoT devices are being exploited as entry points for cyberattacks due to security weaknesses. IoT malware variants have evolved as a result of vulnerabilities in IoT devices. This study investigates whether IoT malware can be detected with various types of malware family. An opcode sequence of malware can represent its family characteristics by utilizing opcode categories. Opcode categories are divided into 6 or 11 depending on opcode functions. Thus, a sequence of opcode categories can identify intrinsic characteristics of the family to which it belongs. By applying the entropy histogram, a 2D representation of a category sequence visually reveals innate patterns within homogeneous families. We find that benign and malware can be differentiated visually, as well as correlated and uncorrelated malware. For the designed feature representation, machine learning algorithms (5-NN, SVM, Decision Tree, and Random Forest) are used, with the best case having a mean MCC or F1-score of over 98.0%. Overall, the 11 opcode category outperforms the 6 opcode category. The experiments have shown that evolved malware can be detected with a model learned from its precedent malware.

关键词： Training Support vector machines Histograms Visualization Feature extraction Tsunami Malware

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ADIperf: A Framework for Application-driven IoT Network Performance Evaluation 31

ADIperf: A Framework for Application-driven IoT Network Perf...

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31st International Conference on computer communications and networks (ICCCN)

作者： Si-Mohammed, Samir Begin, Thomas Lassous, Isabelle Guerin Vicat-Blanc, Pascale Univ Lyon CNRS ENSL UCBLInriaLIP F-69342 Lyon 07 France Stackeo Lyon France

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

The Internet of Things (IoT) is the convergence of the physical and the digital worlds. It enables a large spectrum of applications such as smart building, smart tracking, smart metering, predictive maintenance, remote control, augmented reality or video surveillance. The diversity of these applications has caused a profusion of the IoT communication technologies offerings for exchanging data between IoT devices and applications. The latter technologies come with different features in terms of range, throughput, latency, scalability, energy, etc. Each technology can fit several use cases and a use case can leverage several technologies. It is complex, yet critical, for an IoT architect to evaluate the adequacy and the limits of a network technology for a targeted application and to continuously optimize its configuration as the deployment evolves. This paper introduces ADIperf, a framework to simplify and systematize the evaluation of the performance of an IoT communication technology for a given IoT use case and context. The ADIperf approach pays special attention to the energy efficiency as well as to the ability of an IoT communication technology to properly scale up with the number of end-devices, with the ultimate goal of giving guidelines and tools for IoT architects to select the technology and configure the network that fulfill their application's needs over time.

关键词： Internet of Things Applications Framework Performance Evaluation Simulation

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Inferring User Activities from IoT Device Events in Smart Homes: Challenges and Opportunities 31

Inferring User Activities from IoT Device Events in Smart Ho...

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31st International Conference on computer communications and networks (ICCCN)

作者： Lin, Xuanli Wan, Yinxin Xu, Kuai Wang, Feng Xue, Guoliang Arizona State University

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

The ubiquitous deployment of IoT devices in smart homes has led to growing research interests in studying the home network traffic for various applications such as network measurements, device profiling, and IoT device event inference. Recent studies have shown that user activities can be inferred from a home network using extracted device event logs. However, existing solutions for user activity inference such as IoTMosaic and E2AP have limitations when handling ambiguities caused by device malfunctions. In this paper, we first identify the challenges faced by the existing user activity inference algorithms and the root causes of their poor performances on certain types of inputs. We then show that useful information can still be obtained even in situations where device malfunctions introduce ambiguities in user activity patterns. We achieve so by designing an extension to the existing algorithms. We also apply our extension in a digital forensics application. Our extensive experimental evaluations demonstrate that our solutions can effectively provide insights to user activity inference despite the presence of indistinguishable user activity patterns.

关键词： Internet-of-things device events user activity inference challenges and opportunities

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Achieving High End-to-End Availability in VNF networks 31

Achieving High End-to-End Availability in VNF Networks

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31st International Conference on computer communications and networks (ICCCN)

作者： Rodicio, Enrique Pan, Deng Liu, Jason Tang, Bin Florida Int Univ Sch Comp & Informat Sci Miami FL 33199 USA Calif State Univ Dominguez Hills Dept Comp Sci Carson CA 90747 USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

As software programs, Virtual Network Functions (VNFs) introduce new challenges to network availability due to their potential software failures. Existing models on the availability of VNF networks did not consider all the possible hardware and software failures, making them incapable of analyzing the end-to-end availability of a path. Furthermore, they did not capture the correlation between repeating nodes and links in the path, resulting in inaccurate analytical results. In this paper, we propose a new analytical model, which considers all hardware and software failures as well as the effect of repeating components, to effectively analyze the end-to-end availability of a flow path in VNF networks. On top of the analytical model, we formulate the Highest Availability Path (HAP) problem that finds the flow path with the highest end-to-end availability, and prove its NP-hardness by reduction from the Node-Weighted Steiner Tree problem. Next, we propose two algorithms for HAP: the first one based on a Steiner Tree approximation algorithm, having high time complexity and serving as a performance benchmark;the second one using a dynamic programming approach to search a multi-layer graph in polynomial time. Finally, we present extensive evaluation data to demonstrate the effectiveness of the Layered Search algorithm, which achieves comparable performance as that of the Steiner Tree based algorithm and runs faster by four orders of magnitude.

关键词： VNF availability failure

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Predictive Cyber Defense Remediation against Advanced Persistent Threat in Cyber-Physical Systems 31

Predictive Cyber Defense Remediation against Advanced Persis...

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31st International Conference on computer communications and networks (ICCCN)

作者： Hasanl, Kamrul Shetty, Sachin Islam, Tariqul Ahmed, Imtiaz Tennessee State Univ Nashville TN 37203 USA Old Dominion Univ Norfolk VA USA Syracuse Univ Syracuse NY USA Howard Univ Washington DC USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Advanced Persistent Threat (APT) has dramatically changed the landscape of cybersecurity. APT is carried out by stealthy, continuous, sophisticated, and well-funded attack processes for long-term malicious gain thwarting most current defense mechanisms. There is a need for a defense strategy that continuously combats APT over a long time-span in imperfect/incomplete information on attacker's actions. We propose the stochastic evolutionary game model to simulate the dynamic adversary to address this need in this work. We add the player's rationality parameter & to the Logit Quantal Response Dynamics (LQRD) model to quantify the cognitive differences of real-world players. We propose an optimal decision-making plan by calculating the stable evolutionary equilibrium that balances a trade-off between defense cost and benefit. Cases studies conducted on Energy Delivery Systems (EDS) indicate that the proposed method can help the defender predict possible attack action, select the related optimal cyber defense remediation over time, and gain the maximum defense payoff.

关键词： APT Cyber Defense Cyber-Physical Systems (CPS) Energy Delivery Systems (EDS)

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