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

共 4934 条记录，以下是141-150 订阅

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IoBT-OS: Optimizing the Sensing-to-Decision Loop for the Internet of Battlefield Things 31

IoBT-OS: Optimizing the Sensing-to-Decision Loop for the Int...

引用

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

作者： Liu, Dongxin Abdelzaher, Tarek Wang, Tianshi Hu, Yigong Li, Jinyang Liu, Shengzhong Caesar, Matthew Kalasapura, Deepti Bhattacharyya, Joydeep Srour, Nassy Wigness, Maggie Kim, Jae Wang, Guijun Kimberly, Greg Osipychev, Denis Yao, Shouchao Univ Illinois Dept Comp Sci Urbana IL 61801 USA DEVCOM Army Res Lab Adelphi MD 20783 USA Boeing Co Seattle WA 98124 USA George Mason Univ Dept Comp Sci Fairfax VA 22030 USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Recent concepts in defense herald an increasing degree of automation of future military systems, with an emphasis on accelerating sensing-to-decision loops at the tactical edge, reducing their network communication footprint, and improving the inference quality of intelligent components in the loop. These requirements pose resource management challenges, calling for operating-system-like constructs that optimize the use of limited computational resources at the tactical edge. This paper describes these challenges and presents IoBT-OS, an operating system for the Internet of Battlefield Things that aims to optimize decision latency, improve decision accuracy, and reduce corresponding resource demands on computational and network components. A simple case-study with initial evaluation results is shown from a target tracking application scenario.

关键词： Internet of Battlefield Things Edge Intelligence Sensing-to-Decision Loops

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Real-time Application Identification of RTC Media Streams via Encrypted Traffic Analysis 31

Real-time Application Identification of RTC Media Streams vi...

引用

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

作者： Wu, Hua Zhu, Chengfei Cheng, Guang Hu, Xiaoyan Southeast Univ Sch Cyber Sci & Engn Nanjing Peoples R China Purple Mt Labs Network & Commun Secur Nanjing Peoples R China Southeast Univ Key Lab Comp Network & Informat Integrat Nanjing Peoples R China Jiangsu Prov Engn Res Ctr Secur Ubiquitous Networ Nanjing Peoples R China

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

The globalization of the economy and the increase in network bandwidth have contributed significantly to the development and popularity of real-time communication (RTC) social applications. RTC media streams, such as video meetings and calls, require more network resources and real-time performance than other services. In order to meet the requirements of RTC application providers to offer a higher level of service to their subscribers, Internet Service Providers (ISPs) need to identify the application to which the RTC media stream belongs. There are already some studies on traffic identification. However, the extant work is not yet able to distinguish the corresponding applications from the same type of media streams in real time. In addition, most of the work is not validated with actual data containing massive background traffic. Hence, we propose a real-time application identification method for meeting and calling RTC media streams in social networks. By analyzing the encrypted traffic, the method extracts features from the unit-time traffic aggregation without using payload and related information fields. The generated feature sequences are fed to our lightweight model. Our proposed method does not depend on initial packets or whole flows, and only an arbitrary 3-second traffic block is needed to achieve over 99% accuracy. Moreover, experiments using high-speed network traffic reflect that our approach can identify corresponding applications from RTC media streams in real time. Besides, comparisons with similar work show that this method requires only 1/160th of the memory and 1/10th of the processing time.

关键词： Social networks Media Streams Real-time Communication Application Identification Deep Learning

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R²P³: Renewal-Reward Process-Based Password Protection in Internet of Things 31

R<SUP>2</SUP>P<SUP>3</SUP>: Renewal-Reward Process-Based Pas...

引用

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

作者： Neumann, Thomas Welsh, Kyle Perez, Caden Sha, Kewei Wu, Yalong North Cent Coll Dept Comp Sci & Engn Naperville IL USA Univ Houston Dept Comp Sci Clear Lake TX USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Given the eruption of Internet of Things (IoT) systems, it has become critical for connected devices to have persistent security. Password-based security measures provide an interface for users to effectively secure their personal data. Nonetheless, passwords are often stolen by cyber criminals due to inferior user security awareness. To address these issues, in this paper, we develop a renewal-reward process-based password protection (R-2 P-3) scheme to prevent unauthorized users from breaching IoT devices even after they obtain user passwords. Specifically, R-2 P-3 utilizes the renewal-reward process to accumulate a tendency to trust (T-3) score for any IoT device password attempt on the basis of keystroke dynamics (i.e., dwell time and flight time) and assures device authentication by comparing user attempt T-3 scores to a predefined threshold. We have validated the security efficacy of (RP3)-P-2. Our experimental results demonstrate that (RP3)-P-2 achieves superior security performance in terms of unauthorized user blocking ratio.

关键词： Internet of Things renewal-reward process password security tendency to trust score

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Tracing Tor Hidden Service Through Protocol Characteristics 31

Tracing Tor Hidden Service Through Protocol Characteristics

引用

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

作者： Qin, Yi Zheng, Tianming Wu, Yue Zou, Futai Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Tor is a relay-based communication network that provides users with anonymous access to the Internet. Tor hidden services protect the identities of the content publishers to achieve anonymity and anti-censorship. However, hidden services are abused to conduct illegal activities, including hosting botnets and trading drugs. This paper proposes a tracing approach to locate illegal hidden services based on the Tor protocol characteristics, which allows a Tor client to embed a signal into a Tor circuit connecting with the illegal hidden service. Once the Tor node nearest to the the hidden service detects the signal, the identity of the hidden service can be revealed. Our approach is simple, powerful, and stable compared with previous methods. We implemented the approach and performed experiments over the Tor network, whose results show that our approach is feasible and effective, with 100% accuracy, 99.25% true positive rate, and zero false positive rate.

关键词： Tor network Hidden service Deanonymization

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Deep Reinforcement Learning Based Computation Offloading in SWIPT-assisted MEC networks 31

Deep Reinforcement Learning Based Computation Offloading in ...

引用

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

作者： Wan, Changwei Guo, Songtao Yang, Yuanyuan Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Computation offloading is an effective method to relieve user equipment (UE) from the limited battery capacity and computation resource in mobile edge computing (MEC) networks. However, it is challenging to obtain offloading strategy timely and accurately under diverse computation task requirements and changeable network channel states in multi-user and resource-constrained network environment. In this paper, we consider the network dynamics and UE's resource constraints and aim to minimize the energy consumption of all UEs by jointly optimizing the offloading decision, the central processing unit (CPU) frequency and the power split ratio in a dynamic MEC network. To be specific, we introduce simultaneous wireless information and power transmission (SWIPT) technology in MEC networks to prolong UE's operation time. More importantly, we propose an online computation offloading algorithm based on deep deterministic policy-gradient (DDPG), named Enhanced DDPG (EDDPG), to solve the energy consumption minimization problem. In particular, EDDPG can make real-time decisions without complete network information and adapt to time-varying environments and different requirements. Furthermore, we introduce the priority experience replay technology in EDDPG to accelerate the convergence by using experience tuples. Simulation results show that our proposed algorithm can effectively reduce the energy consumption of UEs and enable them complete more computing tasks within the time limit. Compared with other baseline methods, it can accelerate the convergence and improve the system performance effectively.

关键词： Computation offloading Mobile edge computing Deep reinforcement learning Wireless information and power transmission Energy consumption

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Automatic Field Extraction of Extended TLV for Binary Protocol Reverse Engineering 31

Automatic Field Extraction of Extended TLV for Binary Protoc...

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

作者： Huang, Zewen Wu, Kui Huang, Shengqiang Zhou, Yang Giagone, Ronnie Salvador Univ Victoria Dept Comp Sci Victoria BC Canada Huawei Technol Canada Co Ltd Burnaby BC Canada

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Type Length Value (TLV) is one of the main structures commonly used in network protocols. A large number of proprietary protocols, whose specification is unknown to the public, run in the current Internet as well as domain-specific Internet of Things (IoT) applications. It is critical to infer the TLV fields within a packet because this information can help network administrators quickly identify abnormal traffic and potential attacks. Inferring TLV fields belongs to the general task of protocol reverse engineering and is particularly challenging for binary protocols, where the boundaries of TLV fields have many possible positions. Existing methods for reverse engineering binary protocols involve many parameters and only work for protocols strictly following the conventional TLV format. We extend the concept of TLV to accommodate a broader category of structural patterns in various binary protocols, such as TCP, IP, ModBus, and MQTT. We then design algorithms to automatically extract the extended-TLV fields from packets. Via a series of experiments over several protocols, we demonstrate that our algorithms can accurately and quickly identify the extended-TLV fields in all the tested protocols. Our approach can thus be deployed as a general method for automatically reverse engineering binary protocol format.

关键词： Extended TLV Binary Protocol Reverse Engineering

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Intelligent Fuzzing Algorithm for 5G NAS Protocol Based on Predefined Rules 31

Intelligent Fuzzing Algorithm for 5G NAS Protocol Based on P...

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

作者： He, Fengjiao Yang, Wenchuan Cui, Baojiang Cui, Jia Beijing Univ Posts & Telecommun Natl Engn Lab Mobile Network Secur Beijing Peoples R China China Informat Technol Secur Evaluat Ctr Informat Dept Beijing Peoples R China

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

The fifth-generation mobile communication network (5G) is a significant infrastructure with the support of enhanced mobile broadband, ultra-reliable and low latency communication, and massive machine type communication. Due to the large-scale application of 5G in industrial control field, the security of 5G network has become an important issue. In order to efficiently perform security detection on 5G radio access network protocols, we propose an intelligent fuzzing algorithm for 5G NAS protocol based on predefined rules. Through the analysis of the 3GPP NAS protocol technical specification and captured packets, a message structure table is extracted based on the NAS message format and field properties. Different mutation strategies are then dynamically assigned to different key fields to realize the intelligence of the message mutation process. Furthermore, in order to evaluate the performance of the algorithm, we implement a fuzzing prototype system based on this intelligent mutation algorithm, and then conduct practical security detection on 5G NAS protocol in OAI, an open-source software radio simulation environment. Experimental results show that our proposed intelligent mutation algorithm has better performance in terms of protocol state coverage and the scale of test cases. In addition, five types of security vulnerabilities in OAI are also exposed in this paper, namely buffer overflow, use-after-free, infinite loop, memory access for uninitialized address, and memory access for NULL pointers. These vulnerabilities could result in denial of registration services to users.

关键词： 5G fuzzing security detection NAS protocol

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Neural networks for DDoS Attack Detection using an Enhanced Urban IoT Dataset 31

Neural Networks for DDoS Attack Detection using an Enhanced ...

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

作者： Hekmati, Arvin Grippo, Eugenio Krishnamachari, Bhaskar Univ Southern Calif Dept Comp Sci Los Angeles CA USA Univ Southern Calif Dept Elect & Comp Engn Los Angeles CA USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

We investigate the application of artificial intelligence to cybersecurity, to contribute to the safe and secure growth of the internet of things (IoT). Specifically, we train and evaluate different neural networks models to detect distributed denial of service (DDoS) attacks in a large-scale IoT system. We consider futuristic attacks launched by sophisticated malicious entities that take over multiple distributed IoT nodes and are able to disguise their intrusion by closely mimicking the benign traffic of the network. Using data from prior work, we find that a truncated Cauchy distribution is a suitable fit for benign traffic volume from IoT devices, and we model the attack traffic volume as following the same distribution but with different parameters for location and scale. We emulate both benign and attack traffic by overlaying these traffic volume distributions on top of an activity status data trace from a real urban IoT deployment consisting of about 4000 nodes. Using our enhanced dataset, we compare four neural network models: multi-layer perceptron (MLP), convolutional neural network (CNN), long short-term memory (LSTM), and autoencoder (AEN), analyzing their performance as a function of a parameter that measures the deviation of the attacks from the benign data. We observe that all four models are sensitive to the distance between benign and attack traffic. We further observe that LSTM gives the best overall performance in terms of both high accuracy and high recall.

关键词： IoT DDoS Attacks datasets neural networks machine learning botnet Cauchy distribution

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An Energy-Efficient Load Balancing Scheme in Heterogeneous Clusters by Linear Programming 31

An Energy-Efficient Load Balancing Scheme in Heterogeneous C...

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

作者： Zhang, Yujian Li, Mingde Tong, Fei Southeast Univ Sch Cyber Sci & Engn Nanjing Peoples R China Southeast Univ Key Lab Comp Network & Informat Integrat Minist Educ Nanjing Peoples R China Purple Mt Labs Nanjing Peoples R China

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

The growing power consumption of heterogeneous clusters has attracted great interests from both academia and industry. Although there have been extensive studies on energy-efficient task scheduling algorithms to address this problem, most of them are task-centric. However, as a task is fine-grained enough, the scheduling algorithm can put more efforts on utilizing different power characteristics of heterogeneous servers, which has not been fully explored. This paper presents a Linear Programming-based Energy-efficient Load Balancing (LP-ELB) scheme for heterogeneous clusters. The power model of each sever in the cluster is obtained in advance, and the overall optimization problem is formulated as a mixed integer linear programming problem. LP-ELB tackles this problem through a two-phase heuristic: a server selection phase for choosing a minimal set of servers, and a load partition phase for calculating load distribution. An optimal solution to the relaxed problem in the second phase can be provided finally. Experiments on both simulated and real-world testbeds validate the effectiveness of the proposed method, and reveal that LP-ELB is superior to competitor algorithms, such as Round-Robin and power-aware Weighted Round-Robin.

关键词： Heterogeneous cluster Load balancing Energy efficient Linear programming

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Multi-Controller Load Balancing Mechanism Based on Improved Genetic Algorithm 31

Multi-Controller Load Balancing Mechanism Based on Improved ...

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

作者： Xu, Aixin Sun, Shimin Wang, Ze Wang, Xiaofan Han, Li Tiangong Univ Tianjin Key Lab Autonomous Intelligent Technol Sch Software Tianjin Peoples R China Tiangong Univ Sch Software Tianjin Peoples R China Tianjin Univ Technol Tianjin Sch Comp Sci & Engn Tianjin Peoples R China

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

To solve the load imbalance problem of controllers in Software Defined networks (SDN), we present a controller reselection mechanism based on non-cooperative game theory. Load balancing among controller clusters is achieved by dynamic migration of SDN switches. The load balance of controller cluster, the average latency and the switch migration cost were adopted as utility functions. To meet Nash equilibrium strategy, we propose a Genetic Algorithm for Improved Multi-objective Optimization (GAIMO). To prevent global optimal solution from slipping into a local optimum, a similarity operator is designed to speed up the convergence and to improve the accuracy of the proposed algorithm. Experimental results show that the mechanism effectively optimizes overall resource utilization of controllers, and reduces average network latency, communication overhead, as well as the cost of switch migration, and thus optimizes entire network performance.

关键词： Software Defined Networking Non-cooperative Game Load Balancing Switch Migration Genetic Algorithm

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