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Future Internet, Volume 10, Issue 5 (May 2018) – 7 articles

Cover Story (view full-size image): In 1897, the American jurist, Oliver Wendell Holmes stated: “for the rational study of the law, the man of the future is the man of statistics” advocating the rise of new quantitative and scientific approaches to legal issues. One hundred and twenty years later, the future foreseen by Holmes is becoming reality. The combination of data-driven computational methods and law allows for innovative answers to the needs of legal science and practice; answers becoming available that range from quantitative legal prediction to the use of network analysis and machine learning in legal analysis and information retrieval. Analytical platforms are an integral part of this future... View this paper.

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11 pages, 636 KiB

Open AccessArticle

Botnet Detection Based On Machine Learning Techniques Using DNS Query Data

by Xuan Dau Hoang and Quynh Chi Nguyen

Future Internet 2018, 10(5), 43; https://doi.org/10.3390/fi10050043 - 18 May 2018

Cited by 79 | Viewed by 9055

Abstract

In recent years, botnets have become one of the major threats to information security because they have been constantly evolving in both size and sophistication. A number of botnet detection measures, such as honeynet-based and Intrusion Detection System (IDS)-based, have been proposed. However, IDS-based solutions that use signatures seem to be ineffective because recent botnets are equipped with sophisticated code update and evasion techniques. A number of studies have shown that abnormal botnet detection methods are more effective than signature-based methods because anomaly-based botnet detection methods do not require pre-built botnet signatures and hence they have the capability to detect new or unknown botnets. In this direction, this paper proposes a botnet detection model based on machine learning using Domain Name Service query data and evaluates its effectiveness using popular machine learning techniques. Experimental results show that machine learning algorithms can be used effectively in botnet detection and the random forest algorithm produces the best overall detection accuracy of over 90%. Full article

(This article belongs to the Section Big Data and Augmented Intelligence)

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20 pages, 4448 KiB

Open AccessArticle

Test Bed of Semantic Interaction of Smart Objects in the Web of Things

by Santiago Guerrero-Narváez, Miguel-Ángel Niño-Zambrano, Dalila-Jhoana Riobamba-Calvache and Gustavo-Adolfo Ramírez-González

Future Internet 2018, 10(5), 42; https://doi.org/10.3390/fi10050042 - 9 May 2018

Cited by 1 | Viewed by 4493

Abstract

Semantic interaction in the Internet of Things (IoT) is an important concept within current IoT development, given that smart things require further autonomy with greater processing, storage, and communication capacities. The problem is now becoming one of how to get these things to interact and collaborate with each other; to form intelligent environments amongst themselves and thus generate better services for users. This article explores a solution approach that consists in providing collaborative behavior to smart things, through the incorporation of an ontology and an architecture. It makes possible things that can communicate and collaborate with each other, allowing the generation of new services of interaction according to user needs. For this task, a real test bed of smart things was created, in which the proposed solution was deployed (Smart Room). Finally, it was concluded that the creation of these types of test bed is feasible, taking into account that response times and the information delivered by the different managed processes are acceptable. New challenges were encountered, however, such as problems of critical region in test beds with conflicting services and management of multiple users. Full article

(This article belongs to the Special Issue Big Data and Internet of Thing)

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19 pages, 3670 KiB

Open AccessArticle

Route Availability as a Communication Quality Metric of a Mobile Ad Hoc Network

by Tamotsu Yashima and Kazumasa Takami

Future Internet 2018, 10(5), 41; https://doi.org/10.3390/fi10050041 - 4 May 2018

Cited by 9 | Viewed by 4138

Abstract

Using ad hoc communication between mobile terminals, MANETs (mobile ad hoc networks) are independent of any communication infrastructure but their communication quality can degrade because, as terminals move about in the service area, routes are constantly disconnected and then re-established. There has been no proposal for a quality metric that models this unstable state, i.e., route nonuniformity. This paper proposes a new concept of route availability (RA) as a metric of route nonuniformity in a MANET and verifies how effectively it represents the quality of service (QoS) of a network or the quality of experience (QoE) of video streaming. We have built an environment that emulates a MANET capable of video streaming, and developed a method of measuring RA for two representative MANET routing methods: AODV (Ad hoc On-Demand Distance Vector) and OLSR (Optimized Link State Routing). We have examined the relationship between RA and conventional network QoS metrics: packet loss rate and throughput. We have also checked RA using a subjective quality assessment test. Full article

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11 pages, 1260 KiB

Open AccessArticle

An EV Charging Scheduling Mechanism Based on Price Negotiation

by Baocheng Wang, Yafei Hu, Yu Xiao and Yi Li

Future Internet 2018, 10(5), 40; https://doi.org/10.3390/fi10050040 - 3 May 2018

Cited by 9 | Viewed by 4684

Abstract

Scheduling EV user’s charging behavior based on charging price and applying renewable energy resources are the effective methods to release the load pressure of power grids brought about by the large-scale popularity of electric vehicles (EVs). This paper presents a novel approach for EV charging scheduling based on price negotiation. Firstly, the EV charging system framework based on price negotiation and renewable energy resources is discussed. Secondly, the price negotiation model is presented, including the initial price models and the conditions of transactions. Finally, an EV charging scheduling mechanism based on price negotiation (CSM-PN), including the price adjustment strategies of both the operator and EV users is proposed to seek a final transaction during multi-round price negotiation. Simulation results show that this novel approach can effectively improve the charging station operator’s income, reduce the EV users’ costs, and balance the load of the power grid while improving the efficiency of the EV charging system. Full article

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10 pages, 6902 KiB

Open AccessArticle

A Fair Cooperative MAC Protocol in IEEE 802.11 WLAN

by Seyed Davoud Mousavi, Rasool Sadeghi, Mohamadreza Karimi, Erfan Karimian and Mohammad Reza Soltan Aghaei

Future Internet 2018, 10(5), 39; https://doi.org/10.3390/fi10050039 - 3 May 2018

Cited by 3 | Viewed by 4213

Abstract

Cooperative communication techniques have recently enabled wireless technologies to overcome their challenges. The main objective of these techniques is to improve resource allocation. In this paper, we propose a new protocol in medium access control (MAC) of the IEEE 802.11 standard. In our new protocol, which is called Fair Cooperative MAC (FC-MAC), every relay node participates in cooperation proportionally to its provided cooperation gain. This technique improves network resource allocation by exploiting the potential capacity of all relay candidates. Simulation results demonstrate that the FC-MAC protocol presents better performance in terms of throughput, fairness, and network lifetime. Full article

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18 pages, 4333 KiB

Open AccessArticle

MinHash-Based Fuzzy Keyword Search of Encrypted Data across Multiple Cloud Servers

by Jingsha He, Jianan Wu, Nafei Zhu and Muhammad Salman Pathan

Future Internet 2018, 10(5), 38; https://doi.org/10.3390/fi10050038 - 1 May 2018

Cited by 2 | Viewed by 4799

Abstract

To enhance the efficiency of data searching, most data owners store their data files in different cloud servers in the form of cipher-text. Thus, efficient search using fuzzy keywords becomes a critical issue in such a cloud computing environment. This paper proposes a method that aims at improving the efficiency of cipher-text retrieval and lowering storage overhead for fuzzy keyword search. In contrast to traditional approaches, the proposed method can reduce the complexity of Min-Hash-based fuzzy keyword search by using Min-Hash fingerprints to avoid the need to construct the fuzzy keyword set. The method will utilize Jaccard similarity to rank the results of retrieval, thus reducing the amount of calculation for similarity and saving a lot of time and space overhead. The method will also take consideration of multiple user queries through re-encryption technology and update user permissions dynamically. Security analysis demonstrates that the method can provide better privacy preservation and experimental results show that efficiency of cipher-text using the proposed method can improve the retrieval time and lower storage overhead as well. Full article

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25 pages, 1789 KiB

Open AccessFeature PaperArticle

Ex Machina: Analytical platforms, Law and the Challenges of Computational Legal Science

by Nicola Lettieri, Antonio Altamura, Rosalba Giugno, Alfonso Guarino, Delfina Malandrino, Alfredo Pulvirenti, Francesco Vicidomini and Rocco Zaccagnino

Future Internet 2018, 10(5), 37; https://doi.org/10.3390/fi10050037 - 26 Apr 2018

Cited by 11 | Viewed by 7721

Abstract

Over the years, computation has become a fundamental part of the scientific practice in several research fields that goes far beyond the boundaries of natural sciences. Data mining, machine learning, simulations and other computational methods lie today at the hearth of the scientific endeavour in a growing number of social research areas from anthropology to economics. In this scenario, an increasingly important role is played by analytical platforms: integrated environments allowing researchers to experiment cutting-edge data-driven and computation-intensive analyses. The paper discusses the appearance of such tools in the emerging field of computational legal science. After a general introduction to the impact of computational methods on both natural and social sciences, we describe the concept and the features of an analytical platform exploring innovative cross-methodological approaches to the academic and investigative study of crime. Stemming from an ongoing project involving researchers from law, computer science and bioinformatics, the initiative is presented and discussed as an opportunity to raise a debate about the future of legal scholarship and, inside of it, about the challenges of computational legal science. Full article

(This article belongs to the Special Issue Computation, Law and the Net—The Future of Law in the Computational Social Science Era)

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