![]() Nagarajan, Senthil Murugan ![]() in Computer Communications (2022), 195 In recent infrastructures, Internet of Things (IoT) have become an important technology for connecting various actuators and sensors over wireless networks. Due to increase in mission-critical ... [more ▼] In recent infrastructures, Internet of Things (IoT) have become an important technology for connecting various actuators and sensors over wireless networks. Due to increase in mission-critical infrastructures, we make use of these new technologies for reliable communication but their security is always not promising in terms of availability, confidentiality, integrity, and privacy of network services. Users can be compromised and vulnerable by a motivated malicious opponent unless they are not adequately protected by a robust defense. Due to this reason, an ambient intelligence approach for Intrusion Detection System (IDS) is required. In this research, ww proposed Ambient Approach based on Reinforcement Learning Integrated Deep Q-Neural Network (RL-DQN) model for WSNs and IoT in which it leverages the Markov decision process (MDP) formalism to enhance the decision performance in IDS. We deploy RL-DQN-IDS over Edge-cloud intrusion detection infrastructure in which binary attack classification of the network traffic is performed at the edge network while multi-attack classification is performed at the cloud network. To identify intrusions, we use a two-phase process that includes an initial learning phase that relies on RL, followed by a detection and classification phase that relies on DQN. We used four datasets namely UNSW-NB-15, BoTNeTIoT-L01, CICIDS2017 and IoTID20 with a smart house simulation environment configured with WSN and IoT technologies to evaluate performance. Accuracy, precision, and recall were all considered while assessing the dataset under consideration. When compared to five other machine learning models, the RL-DQN model method has demonstrated superior performance. This model outperforms the other five that were tested. [less ▲] Detailed reference viewed: 51 (5 UL)![]() Turcanu, Ion ![]() in Computer Communications (2018), 123 Collecting data from a large number of agents scattered over a region of interest is becoming an increasingly appealing paradigm to feed big data archives that lay the ground for a vast array of ... [more ▼] Collecting data from a large number of agents scattered over a region of interest is becoming an increasingly appealing paradigm to feed big data archives that lay the ground for a vast array of applications. Vehicular Floating Car Data (FCD) collection is a major representative of this paradigm. Massive data collection from floating vehicles is the key to Intelligent Transportation Systems. We address the design and performance evaluation of a data collection protocol for the use case of periodic data collection. We target robustness, optimizing the amount of data and the value of the collection period, keeping in mind the goals of autonomous node operation and minimal coordination effort. From a system point of view, we believe that best solutions should jointly exploit the Long Term Evolution (LTE) cellular access network and the Dedicated Short-Range Communication (DSRC) based Vehicular Ad Hoc Network (VANET). Through a detailed comparative analysis, we show that such a hybrid approach offers superior performance, especially as for offloading the cellular radio access. A lightweight signaling procedure is designed, based on the DSRC VANET, which is able to avoid most of the duplicated data records, even if a distributed operation approach is pursued. The impact of the proposed protocol on the VANET load is evaluated and proved to be quite small, so that it does not interfere with other VANET-specific messages. [less ▲] Detailed reference viewed: 206 (15 UL)![]() Mitseva, Asya ![]() ![]() ![]() in Computer Communications (2018) Detailed reference viewed: 331 (7 UL)![]() ![]() ; ; et al in Computer Communications (2016), 76 Detailed reference viewed: 116 (0 UL)![]() ; Mauw, Sjouke ![]() ![]() in Computer Communications (2015), 67 Detailed reference viewed: 130 (7 UL)![]() Emara, Karim Ahmed Awad El-Sayed ![]() in Computer Communications (2015), 63(1), 11--23 Location privacy in vehicular ad hoc networks has gained considerable attention in the past few years. The majority of studies concern changing pseudonyms to prevent linking messages of the same pseudonym ... [more ▼] Location privacy in vehicular ad hoc networks has gained considerable attention in the past few years. The majority of studies concern changing pseudonyms to prevent linking messages of the same pseudonym. However, the precise spatiotemporal information included in beacons (i.e., timestamp, position, speed and heading) makes them vulnerable to tracking even if they are completely anonymous. One of the most important issues in designing location privacy scheme is to preserve the quality of service of the application. This issue is more significant for safety applications, since they require precise and frequent state updates. Thus, it is crucial to consider this trade-off between location privacy and quality of service of the safety application when designing and evaluating privacy schemes. In this paper, we propose a methodology to measure both the protection level of a privacy scheme and its impact on safety applications. We employ an empirical vehicle tracker to measure the effectiveness of a privacy scheme in terms of a number of confusions. We also measure its impact on a safety application by estimating the probability of correctly identifying the fundamental factors of that application using Monte Carlo analysis. Further, we propose an obfuscation privacy scheme which perturbs position and beacon frequency. Finally, we apply our methodology to evaluate the proposed scheme and compare it with the popular privacy scheme, random silent period. [less ▲] Detailed reference viewed: 148 (1 UL)![]() ; ; et al in Computer Communications (1997), 20 Detailed reference viewed: 99 (3 UL) |
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