Journal of High Speed Networks - Volume 25, issue 4

Authors: Apare, Ravindra S. | Gujar, Satish N.

Article Type: Research Article

Abstract: IoT (Internet of Things) is a sophisticated analytics and automation system that utilizes networks, big data, artificial intelligence, and sensing technology, and is controlled by an embedded module. It allows one to use affordable wireless technology and transmits the data into the cloud at a component level. It also provides a place to save the data – however, the significant challenges in IoT relay on security restrictions related with device cost. Moreover, the increasing amount of devices further generate opportunities for attacks. Hence, to overcome this issue, this paper intends to develop a promising methodology associated with data privacy preservation …for handling the IoT network. It is obvious that the IoT devices often generate time series data, where the range of respective time series data can be vast. Under such circumstances, proper information extraction through effective analysis and relevant privacy preservation of sensitive data from IoT is challenging. In this paper, the problem that occurred in the data preservation is formulated as a non-linear objective model. To solve this objective model, an improved, optimized Dragonfly Algorithm (DA) is adopted, which is termed the Improved DA (IDA) algorithm. Here, the proposed model focused on preserving the physical activity of human monitoring data in the IoT sector. Moreover, the proposed IDA algorithm is compared with conventional schemes such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Bee Colony (ABC), Firefly (FF) and DA and the outcomes prove that the suggested scheme is highly used for preserving the sensitive information uploaded in IoT. Show more

Keywords: Internet of Things, sensitive data, privacy preservation, Improved Dragonfly Algorithm

DOI: 10.3233/JHS-190619

Citation: Journal of High Speed Networks, vol. 25, no. 4, pp. 331-348, 2019

Authors: Catillo, Marta | Rak, Massimiliano | Villano, Umberto

Article Type: Research Article

Abstract: Intrusion detection is one of the major challenges in today’s security industry. Currently attack surfaces are more extensive than in the past, and the use of anomaly detection tools, able to detect intrusions and malicious activities, is essential to avoid infrastructure damages. Furthermore, attackers are able to exploit techniques that bypass security countermeasures and avoid straight detection. Machine learning techniques are widely used to perform effective intrusion detection. In this context, deep learning networks may play an important role, by analyzing network flows and classifying them as “normal” or “intrusion”. This paper presents a deep learning architecture for DoS …attacks detection, which is the first result of an on-going project aiming at the design and implementation of tools for the detection of 0-day threats (ZED-IDS, Zero Day Intrusion Detection System). The problem is tackled as a semi-supervised task, and the anomaly detector is based on a deep autoencoder. The model is described, and the detection performance results obtained on the CICIDS2017 dataset are presented and commented. The performance comparison with the most common supervised classifiers shows the potential of the proposal for 0-day attack detection. Show more

Keywords: DoS attack, anomaly detection, deep Learning, autoencoder, 0-day

DOI: 10.3233/JHS-190620

Citation: Journal of High Speed Networks, vol. 25, no. 4, pp. 349-365, 2019

Authors: Almasaeid, Hisham M. | Al-Kofahi, Osameh | Alnabelsi, Sharhabeel H. | Saifan, Ramzi

Article Type: Research Article

Abstract: With the emergence of cognitive radios, the open spectrum access paradigm that is proposed to overcome the shortcomings of the traditional spectrum allocation paradigm became viable. Researchers have been accumulating efforts to verify the validity of existing networking schemes and protocols as well as designing new ones for this new paradigm. As link failures, due to the activity of primary users, are common in cognitive radio networks, it is essential not to overlook their effect when developing networking solutions including those for multicasting. In this paper, we study the problem of provisioning a multicast session via a tree that has …the maximum achievable immunity against any single spectrum failure. The immunity is measured as the minimum percentage of multicast receivers that remain connected with the root of the multicast tree upon the occurrence of a single spectrum failure. The problem is formulated an Integer Linear Program. We also propose a suboptimal algorithm to solve the problem and compare its performance to the optimal performance obtained using the ILP. Results proved the good performance of our algorithm which was always within ≈ 10 % from the optimal solution. Experiments were also conducted to understand how different network parameters affect the achievable immunity. Show more

Keywords: Multicasting, fault tolerance, spectrum failure, Cognitive Radio Networks

DOI: 10.3233/JHS-190621

Citation: Journal of High Speed Networks, vol. 25, no. 4, pp. 367-384, 2019

Authors: Byun, Heejung

Article Type: Research Article

Abstract: Wireless sensor network (WSN) is a group of spatially dispersed sensors for monitoring the physical conditions of the environment and organizing the collected data at a central location. Since WSNs typically have no infrastructure, one of the challenges in WSNs is the lack of appropriate method for an operator to interact with the WSN. Practical tasks for WSNs require sensor node adaptive to changes in WSN configuration, user input, and commands hence, monitoring and interaction with the WSN is needed. In this paper, a new scheme for configuration dissemination with monitoring of sensor state is proposed to control dynamically sensor …node operation in real time. Moreover, a method is provided for the operator to observe the state of the sensor node, which helps the operator provide an appropriate control input to the WSN. We prove the stability properties of the proposed algorithm and show the simulation results. Show more

Keywords: Wireless sensor networks, dissemination, monitoring of sensor state

DOI: 10.3233/JHS-190622

Citation: Journal of High Speed Networks, vol. 25, no. 4, pp. 385-394, 2019

Authors: Yoon, Yohaan | Go, Kyungmin | Kim, Myungchul

Article Type: Research Article

Abstract: Although 3D video has become popular, successful 3D video streaming over wireless networks involves a number of challenges. Due to the frequent frame damages and losses in wireless networks, temporal asynchrony occurs and results in serious visual fatigue for viewers. In order to provide higher quality 3D video, this paper proposes a new scheme termed the Temporal Synchronization Scheme (TSS) for live 3D video streaming. TSS delivers video frames for the left and right views in the same frame sequence with the same transmission priority, and it compensates for frame damage and losses during the decoding phase. In addition, a …new metric called the Stereoscopic Temporal Variation Index (STVI) is proposed; it measures the degree of temporal asynchrony in 3D video. Subjective assessments demonstrate that STVI is an objective metric for measuring subjective quality given that it exhibits a strong positive correlation with the subjective MOS rating. This paper demonstrates that TSS significantly improves the visual quality of 3D videos given the use of STVI and the Mean Opinion Score (MOS) even when frame damage and losses occur. The contributions of the paper are as follows: i) The proposed TSS is the first scheme to address the temporal asynchrony issue in live 3D video streaming over wireless networks. ii) TSS only requires slight modifications to decoders. iii) A new metric (i.e., STVI) is proposed to measure the degree of temporal asynchrony in 3D videos. Therefore, 3D video streaming over wireless networks can be performed with temporal synchronization, and it is expected using TSS will reduce visual fatigue. Show more

Keywords: 3D video streaming, Temporal synchronization in 3D video, 3D video quality assessment, IEEE 802.11 wireless networks

DOI: 10.3233/JHS-190623

Citation: Journal of High Speed Networks, vol. 25, no. 4, pp. 395-411, 2019

Authors: Najafimehr, Mohammad | Ahmadi, Mahmood

Article Type: Research Article

Abstract: Approximate Membership Query (AMG) data structures are widely used in the networking area recently. The most popular AMQ data structures are Bloom, Quotient and Cuckoo Filter (CF). The CF is more efficient than the Quotient and Bloom filters in term of the lookup time and false positive rate. An issue in CF is utilization of two hash functions in the query phase that increases the lookup time. Another issue is the relocation loop problem in the programming phase that attempts to find an empty bucket for the collied items. In this paper, a new approach called Single-hash Lookup Cuckoo Filter …(SLCF) using one hash function to lookup an item is proposed. In the programming phase, SLCF utilizes a sequence of hash functions without any relocation to find an empty bucket and storing the overflowed items. It finds a bucket with an empty place and sets an index in the original bucket to the address of found bucket. To accelerate the query phase, a handle as a tiny part of the fingerprint is placed in conjunction with the index value in the bucket. In the query phase, only one hash function is used and if the queried item cannot be found in the bucket, the handle is investigated to membership checking. Otherwise, the second bucket pointed by the index is accessed. The simulation results for name search in the named data networking demonstrate that the lookup time is improved 27% for 16 million names in comparison to CF. Show more

Keywords: Single hash-lookup Cuckoo filter, approximate membership query, Bloom filter

DOI: 10.3233/JHS-190624

Citation: Journal of High Speed Networks, vol. 25, no. 4, pp. 413-424, 2019