Noticias em eLiteracias

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✇ Journal of Internet Services and Applications

Detecting web attacks with end-to-end deep learning

27 de Agosto de 2019, 00:00

Abstract

Web applications are popular targets for cyber-attacks because they are network-accessible and often contain vulnerabilities. An intrusion detection system monitors web applications and issues alerts when an attack attempt is detected. Existing implementations of intrusion detection systems usually extract features from network packets or string characteristics of input that are manually selected as relevant to attack analysis. Manually selecting features, however, is time-consuming and requires in-depth security domain knowledge. Moreover, large amounts of labeled legitimate and attack request data are needed by supervised learning algorithms to classify normal and abnormal behaviors, which is often expensive and impractical to obtain for production web applications.

This paper provides three contributions to the study of autonomic intrusion detection systems. First, we evaluate the feasibility of an unsupervised/semi-supervised approach for web attack detection based on the Robust Software Modeling Tool (RSMT), which autonomically monitors and characterizes the runtime behavior of web applications. Second, we describe how RSMT trains a stacked denoising autoencoder to encode and reconstruct the call graph for end-to-end deep learning, where a low-dimensional representation of the raw features with unlabeled request data is used to recognize anomalies by computing the reconstruction error of the request data. Third, we analyze the results of empirically testing RSMT on both synthetic datasets and production applications with intentional vulnerabilities. Our results show that the proposed approach can efficiently and accurately detect attacks, including SQL injection, cross-site scripting, and deserialization, with minimal domain knowledge and little labeled training data.

✇ Journal of Internet Services and Applications

Efficient data dissemination protocol based on complex networks’ metrics for urban vehicular networks

3 de Agosto de 2019, 00:00

Abstract

Services that aim to make the current transportation system more secure, sustainable, and efficient constitute the Traffic Management Systems (TMS). Vehicular Ad hoc Networks (VANETs) exert a strong influence for TMS applications, due to TMS services require data, communication, and processing for operation. Besides, VANET allows direct communication between vehicles, and data are exchanged and processed between them. Several TMS services require disseminated information among decision-making vehicles. However, such dissemination is a challenging task, due to the specific characteristics of VANETs, such as short-range communication and high node mobility, resulting in several variations in their topology. In this article, we introduce an extensive analysis of our proposed data dissemination protocol based on complex networks’ metrics for urban VANET scenarios, called DDRX. Each vehicle must build a subgraph to identify the relay node to continue the dissemination process. Based on the local graph, it is possible to select the relay nodes based on complex networks’ metrics. Simulation results show that DDRX offers high efficiency in terms of coverage, number of transmitted packets, delay, and packet collisions compared to well-known data dissemination protocols. Also, DDRX provides significant improvements to a TMS that needs efficient data dissemination.

✇ Journal of Internet Services and Applications

Thematic series on Social Network Analysis and Mining

22 de Julho de 2019, 00:00

Abstract

Social networks were first investigated in social, educational and business areas. Academic interest in this field though has been growing since the mid twentieth century, given the increasing interaction among people, data dissemination and exchange of information. As such, the development and evaluation of new techniques for social network analysis and mining (SNAM) is a current key research area for Internet services and applications. Key topics include contextualized analysis of social and information networks, crowdsourcing and crowdfunding, economics in networks, extraction and treatment of social data, mining techniques, modeling of user behavior and social networks, and software ecosystems. These topics have important areas of application in a wide range of fields, such as academia, politics, security, business, marketing, and science.

✇ Journal of Internet Services and Applications

A participatory sensing framework to classify road surface quality

9 de Julho de 2019, 00:00

Abstract

Participatory sensing networks rely on gathering personal data from mobile devices to infer global knowledge. Participatory sensing has been used for real-time traffic monitoring, where the global traffic conditions are based on information provided by individual devices. However, fewer initiatives address asphalt quality conditions, which is an essential aspect of the route decision process. This article proposes Streetcheck, a framework to classify road surface quality through participatory sensing. Streetcheck gathers mobile devices’ sensors such as Global Positioning System (GPS) and accelerometer, as well as users’ ratings on road surface quality. A classification system aggregates the data, filters them, and extracts a set of features as input for supervised learning algorithms. Twenty volunteers carried out tests using Streetcheck on 1,200 km of urban roads of Minas Gerais (Brazil). Streetcheck reached up to 90.64% of accuracy on classifying road surface quality.

✇ Journal of Internet Services and Applications

An optimization-based approach for efficient network monitoring using in-band network telemetry

25 de Junho de 2019, 00:00

Abstract

In recent years, as a result of the proliferation of non-elastic services and the adoption of novel paradigms, monitoring networks with high level of detail is becoming crucial to correctly identify and characterize situations related to faults, performance, and security. In-band Network Telemetry (INT) emerges in this context as a promising approach to meet this demand, enabling production packets to directly report their experience inside a network. This type of telemetry enables unprecedented monitoring accuracy and precision, but leads to performance degradation if applied indiscriminately using all network traffic. One alternative to avoid this situation is to orchestrate telemetry tasks and use only a portion of traffic to monitor the network via INT. The general problem, in this context, consists in assigning subsets of traffic to carry out INT and provide full monitoring coverage while minimizing the overhead. In this paper, we introduce and formalize two variations of the In-band Network Telemetry Orchestration (INTO) problem, prove that both are NP-Complete, and propose polynomial computing time heuristics to solve them. In our evaluation using real WAN topologies, we observe that the heuristics produce solutions close to optimal to any network in under one second, networks can be covered assigning a linear number of flows in relation to the number of interfaces in them, and that it is possible to minimize telemetry load to one interface per flow in most networks.

✇ Journal of Internet Services and Applications

Towards business partnership recommendation using user opinion on Facebook

18 de Junho de 2019, 00:00

Abstract

The identification of strategic business partnerships can potentially provide competitive advantages for businesses; however, due to the dynamics and uncertainty present in business environments, this task could be challenging. To help businesses in this task, this study presents a similarity model between businesses that consider the opinions of users on content shared by businesses on social media. Thus, this model captures significant virtual relationships among businesses that are generated by users in the virtual world. Besides, we propose an algorithm for detecting business communities in the considered model. We also propose an algorithm to identify possible business outliers in the detected communities, which could represent an automatic way to identify non-obvious relations that might deserve particular attention of business owners. By exploring approximately 280 million user reactions on Facebook, we show that our results could favor the development of, for example, a new strategic business partnership recommendation service.

✇ Journal of Internet Services and Applications

A semantic-based discovery service for the Internet of Things

15 de Maio de 2019, 00:00

Abstract

With the Internet of Things (IoT), applications should interact with a huge number of devices and retrieve context data produced by those objects, which have to be discovered and selected a priori. Due to the number, heterogeneity, and dynamicity of resources, discovery services are required to consider many selection criteria, e.g., device capabilities, location, context data type, contextual situations, and quality. In this paper, we describe QoDisco, a semantic-based discovery service that addresses this requirement in IoT. QoDisco is composed of a set of repositories storing resource descriptions according to an ontology-based information model and it provides multi-attribute and range querying capabilities. We have evaluated different approaches to reduce the inherent cost of semantic search, namely parallel interactions with multiple repositories and publish-subscribe interactions. This paper also reports the results of some performance experiments on QoDisco with respect to these approaches to handle resource discovery requests in IoT.

✇ Journal of Internet Services and Applications

Multi-objective routing aware of mixed IoT traffic for low-cost wireless Backhauls

1 de Maio de 2019, 00:00

Abstract

The futuristic wireless networks expects to provide adequate support for distinct kind of applications, their diverse requirements, and scenarios for future Internet systems, such as Internet of Things based on multimedia and sensor data, while figuring out low cost solutions to offload the mobile communication core. In this context, Low-cost Wireless Backhauls (LWBs) can be useful, since they are based on cheap WLAN technologies, such as Wireless Mesh Networks that provide capacity for future IoT applications based on mixed traffic. The routing is a fundamental process to provide communication in these multi-hop networks and multi-objective routing optimization algorithms based on Integer Linear Programming (ILP) models have been studied in the literature to address this problem, but there is a lack of solutions for mixed traffic. For this reason, we propose a novel ILP multi-objective approach, called Multi-objective routing Aware of miXed traffIc (MAXI), which employs three weighted objectives to guide the routing in WMNs with different applications and requirements. In addition, we provide a comparative analysis with other relevant approaches of routing using NS-3 to evaluation based on simulation, that takes into account different types and levels of interference (e.g. co-channel interference and external interference) focused on mixed IoT traffic for elderly healthcare scenario. Finally, we demonstrate the effectiveness of the proposed approach to support the requirements of each application through the appropriate combination of objective functions, mainly in dense scenarios with high level of interference.

✇ Journal of Internet Services and Applications

DG2CEP: a near real-time on-line algorithm for detecting spatial clusters large data streams through complex event processing

15 de Abril de 2019, 00:00

Abstract

Spatial concentrations (or spatial clusters) of moving objects, such as vehicles and humans, is a mobility pattern that is relevant to many applications. Fast detection of this pattern and its evolution, e.g., if the cluster is shrinking or growing, is useful in numerous scenarios, such as detecting the formation of traffic jams or detecting a fast dispersion of people in a music concert. On-Line detection of this pattern is a challenging task because it requires algorithms that are capable of continuously and efficiently processing the high volume of position updates in a timely manner. Currently, the majority of approaches for spatial cluster detection operate in batch mode, where moving objects location updates are recorded during time periods of a certain length and then batch-processed by an external routine, thus delaying the result of the cluster detection until the end of the time period. Further, they extensively use spatial data structures and operators, which can be troublesome to maintain or parallelize in on-line scenarios. To address these issues, in this paper we propose DG2CEP, a parallel algorithm that combines the well-known density-based clustering algorithm DBSCAN with the data stream processing paradigm Complex Event Processing (CEP) to achieve continuous and timely detection of spatial clusters. Our experiments with real-world data streams indicate that DG2CEP is able to detect the formation and dispersion of clusters with small latency while having higher similarity to DBSCAN than batch-based approaches.

✇ Journal of Internet Services and Applications

Managing to release early, often and on time in the OpenStack software ecosystem

1 de Abril de 2019, 00:00

Abstract

The dictum of “Release early, release often.” by Eric Raymond as the Linux modus operandi highlights the importance of release management in open source software development. However, there are very few empirical studies addressing release management in this context. It is already known that most open source software communities adopt either a feature-based or time-based release strategy. Both have their own advantages and disadvantages that are also context-specific. Recent research reports that many prominent open source software projects have overcome a number of recurrent problems by moving from feature-based to time-based release strategies. In this longitudinal case study, we address the release management practices of OpenStack, a large scale open source project developing cloud computing technologies. We discuss how the release management practices of OpenStack have evolved in terms of chosen strategy and timeframes with close attention to processes and tools. We discuss the number of practical and managerial issues related to release management within the context of large and complex software ecosystems. Our findings also reveal that multiple release management cycles can co-exist in large and complex software ecosystems such as OpenStack.

✇ Journal of Internet Services and Applications

An agile and effective network function virtualization infrastructure for the Internet of Things

15 de Março de 2019, 00:00

Abstract

The processing and power-consumption constraints of the Internet of Things devices hinder them to offer more complex network services than the simple data transmission in smart city scenarios. The lack of complex services, such as security and quality of service, can even foster disasters in urban centers. In this paper, we propose the integration of complex network services from the IoT devices till a cloud environment through an agile and effective network function virtualization infrastructure of isolated IoT domains. Therefore, our proposal develops a simple gateway access node that virtualizes the domains to which the devices connect. A prototype for services of security and quality of service has been implemented and its evaluation shows that virtualization of the access node does not impact the performance of virtual network functions. The results also show that the proposal provides security for IoT devices, identifying malicious traffic with 99.8% accuracy, avoiding denial of essential services, and ensuring the quality of service.

✇ Journal of Internet Services and Applications

GARSAaaS: group activity recognition and situation analysis as a service

1 de Março de 2019, 00:00

Abstract

Human activity recognition using embedded mobile and embedded sensors is becoming increasingly important. Scaling up from individuals to groups, that is, group activity recognition, has attracted significant attention recently. This paper proposes a model and specification language for group activities called GroupSense-L, and a novel architecture called GARSAaaS (GARSA-as-a-Service) to provide services for mobile Group Activity Recognition and Situation Analysis (or GARSA) applications. We implemented and evaluated GARSAaaS which is an extension of a framework called GroupSense (Abkenar et al., 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), 2016) where sensor data, collected using smartphone sensors, smartwatch sensors and embedded sensors in things, are aggregated via a protocol for these different devices to share information, as required for GARSA. We illustrate our approach via a scenario for providing services for bush walking leaders and bush walkers in a bushwalking group activity. We demonstrate the feasibility of our model and expressiveness of our proposed model.

✇ Journal of Internet Services and Applications

Improving microservice-based applications with runtime placement adaptation

26 de Fevereiro de 2019, 00:00

Abstract

Microservices are a popular method to design scalable cloud-based applications. Microservice-based applications (μApps) rely on message passing for communication and to decouple each microservice, allowing the logic in each service to scale independently.

Complex μApps can contain hundreds of microservices, complicating the ability of DevOps engineers to reason about and automatically optimize the deployment. In particular, the performance and resource utilization of a μApp depends on the placement of the microservices that compose it. However, existing tools for μApps, like Kubernetes, provide minimal ability to influence the placement and utilization of a μApp deployment.

In this paper, we first identify the runtime aspects of microservice execution that impact the placement of microservices in a μApp. We then review the challenges of reconfiguring a μApp based on these aspects. Our main contribution is an adaptation mechanism, named REMaP, to manage the placement of microservices in an μApp automatically. To achieve this, REMaP uses microservice affinities and resource usage history. We evaluate our REMaP prototype and demonstrate that our solution is autonomic, lowers resource utilization, and can substantially improve μApp performance.

✇ Journal of Internet Services and Applications

Adaptive placement & chaining of virtual network functions with NFV-PEAR

4 de Fevereiro de 2019, 00:00

Abstract

The design of flexible and efficient mechanisms for proper placement and chaining of virtual network functions (VNFs) is key for the success of Network Function Virtualization (NFV). Most state-of-the-art solutions, however, consider fixed (and immutable) flow processing and bandwidth requirements when placing VNFs in the Network Points of Presence (N-PoPs). This limitation becomes critical in NFV-enabled networks having highly dynamic flow behavior, and in which flow processing requirements and available N-PoP resources change constantly. To bridge this gap, we present NFV-PEAR, a framework for adaptive VNF placement and chaining. In NFV-PEAR, network operators may periodically (re)arrange previously determined placement and chaining of VNFs, with the goal of maintaining acceptable end-to-end flow performance despite fluctuations of flow processing costs and requirements. In parallel, NFV-PEAR seeks to minimize network changes (e.g., reallocation of VNFs or network flows). The results obtained from an analytical and experimental evaluation provide evidence that NFV-PEAR has potential to deliver more stable operation of network services, while significantly reducing the number of network changes required to ensure end-to-end flow performance.

✇ Journal of Internet Services and Applications

SCOPE: self-adaptive and policy-based data management middleware for federated clouds

30 de Janeiro de 2019, 00:00

Abstract

A federated cloud storage setup which integrates and utilizes storage resources from multiple cloud storage providers has become an increasingly popular and attractive paradigm for the persistence tier in cloud-based applications (e.g., SaaS applications, IoT applications, etc).

However, federated cloud storage setups are prone to run-time dynamicity: many dynamic properties impact the way such a setup is governed and evolved over time, e.g., storage providers enter or leave the market; QoS metrics and SLA guarantees may change over time; etc. In general, existing federated cloud systems are oblivious to dynamic properties of the underlying operational environment, resulting in both sub-optimal data management decisions and costly SLA violations. Additionally, due to the sheer complexity of cloud-based applications coupled with the heterogeneous and volatile nature of federated cloud setups, the complexity of building, maintaining, and expending such applications increases dramatically and therefore managing them manually is no longer simply an option.

To address these concerns, we present SCOPE, a policy-based and autonomic middleware that provides self-adaptiveness for data management in federated clouds. We have validated SCOPE in the context of a realistic SaaS application, performed an extensive functional validation, and conducted a thorough experimental evaluation. The evaluation results demonstrate (i) the ability of the middleware to perform data management decisions that take into account the run-time dynamicity (i.e., dynamic properties) of a federated cloud storage setup to meet the promised SLAs, and (ii) the self-adaptive behavior of SCOPE without the need for operator intervention. In addition, our in-depth performance evaluation results indicate that the benefits are achieved with acceptable performance overhead, and as such highlight the applicability of the proposed middleware for real-world application cases.

✇ Journal of Internet Services and Applications

Pseudonymization risk analysis in distributed systems

8 de Janeiro de 2019, 00:00

Abstract

In an era of big data, online services are becoming increasingly data-centric; they collect, process, analyze and anonymously disclose growing amounts of personal data in the form of pseudonymized data sets. It is crucial that such systems are engineered to both protect individual user (data subject) privacy and give back control of personal data to the user. In terms of pseudonymized data this means that unwanted individuals should not be able to deduce sensitive information about the user. However, the plethora of pseudonymization algorithms and tuneable parameters that currently exist make it difficult for a non expert developer (data controller) to understand and realise strong privacy guarantees. In this paper we propose a principled Model-Driven Engineering (MDE) framework to model data services in terms of their pseudonymization strategies and identify the risks to breaches of user privacy. A developer can explore alternative pseudonymization strategies to determine the effectiveness of their pseudonymization strategy in terms of quantifiable metrics: i) violations of privacy requirements for every user in the current data set; ii) the trade-off between conforming to these requirements and the usefulness of the data for its intended purposes. We demonstrate through an experimental evaluation that the information provided by the framework is useful, particularly in complex situations where privacy requirements are different for different users, and can inform decisions to optimize a chosen strategy in comparison to applying an off-the-shelf algorithm.

✇ Journal of Internet Services and Applications

Networking architectures and protocols for smart city systems

20 de Dezembro de 2018, 00:00

Abstract

The smart city model is used by many organizations for large cities around the world to significantly enhance and improve the quality of life of the inhabitants, improve the utilization of city resources, and reduce operational costs. This model includes various heterogeneous technologies such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Wireless Sensor Networks (WSNs), Cloud Computing, and Unmanned Aerial Vehicles (UAVs). However, in order to reach these important objectives, efficient networking and communication protocols are needed to provide the necessary coordination and control of the various system components. In this paper, we identify the networking characteristics and requirements of smart city applications, and identify the networking protocols that can be used to support the various data traffic flows that are needed between the different components. In addition, we provide illustrations of networking architectures of selected smart city systems, which include smart grid, smart home energy management, smart water, UAV and commercial aircraft safety, and pipeline monitoring and control systems.

✇ Journal of Internet Services and Applications

Is it possible to describe television series from online comments?

15 de Dezembro de 2018, 00:00

Abstract

Due to the omnipresence of the Internet and Social Media in current society, it has become easy to find groups or communities of people discussing the most varied subjects in discussion forums, social network interactions, or comments on web pages. In this paper, we try to answer the question about whether, even when nothing is explicitly known about the entity referred to in the discussion, it is possible to formulate a general and brief idea of its characteristics when reading comments about it. To study this problem, we characterize a collection of online discussions about television series episodes, investigate the potential that comments have to describe these series, implement several different summarization methods, and finally evaluate these different methods and analyze the results obtained from them. Results reveal that a small set of comments can describe the corresponding episodes and, when taken together, the series as a whole.

✇ Journal of Internet Services and Applications

The computer for the 21st century: present security & privacy challenges

4 de Dezembro de 2018, 00:00

Abstract

Decades went by since Mark Weiser published his influential work on the computer of the 21st century. Over the years, some of the UbiComp features presented in that paper have been gradually adopted by industry players in the technology market. While this technological evolution resulted in many benefits to our society, it has also posed, along the way, countless challenges that we have yet to surpass. In this paper, we address major challenges from areas that most afflict the UbiComp revolution:

  1. Software Protection: weakly typed languages, polyglot software, and networked embedded systems.

  2. Long-term Security: recent advances in cryptanalysis and quantum attacks.

  3. Cryptography Engineering: lightweight cryptosystems and their secure implementation.

  4. Resilience: issues related to service availability and the paramount role of resilience.

  5. Identity Management: requirements to identity management with invisibility.

  6. Privacy Implications: sensitivity data identification and regulation.

  7. Forensics: trustworthy evidence from the synergy of digital and physical world.

We point out directions towards the solutions of those problems and claim that if we get all this right, we will turn the science fiction of UbiComp into science fact.

✇ Journal of Internet Services and Applications

Graph mining for the detection of overcrowding and waste of resources in public transport

15 de Novembro de 2018, 00:00

Abstract

The imbalance between the quantity of supply and demand in public transport systems causes a series of disruptions in large metropolises. While extremely crowded vehicles are uncomfortable for passengers, virtually empty vehicles generate economic losses for system managers, and this usually comes back to passengers in the form of fare increases. In this article a new data processing methodology will be presented for the evaluation of collective transportation systems. It proposes the construction and mining of graphs that represent complex networks of supply and demand of the system to find such imbalances. In a case study with the bus system of a large Brazilian metropolis, it was shown that the methodology in question is capable of identifying global imbalances in the system based on an evaluation of the weight distributions of the edges of the supply and demand networks. It has also been shown that even in a scenario where information about the demand is incomplete, using community detection techniques it is possible to identify the stretches of the network that are potentially causing these imbalances on a global scale.

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