State of The Art and Hot Aspects in Cloud Data Storage Security

Along with the evolution of cloud computing and cloud storage towards matu- rity, researchers have analyzed an increasing range of cloud computing security aspects, data security being an important topic in this area. In this paper, we examine the state of the art in cloud storage security through an overview of selected peer reviewed publications. We address the question of defining cloud storage security and its different aspects, as well as enumerate the main vec- tors of attack on cloud storage. The reviewed papers present techniques for key management and controlled disclosure of encrypted data in cloud storage, while novel ideas regarding secure operations on encrypted data and methods for pro- tection of data in fully virtualized environments provide a glimpse of the toolbox available for securing cloud storage. Finally, new challenges such as emergent government regulation call for solutions to problems that did not receive enough attention in earlier stages of cloud computing, such as for example geographical location of data. The methods presented in the papers selected for this review represent only a small fraction of the wide research effort within cloud storage security. Nevertheless, they serve as an indication of the diversity of problems that are being addressed

Design and development of protocol log analyzer for cellular modem

Abstract. Telecommunications protocols and cellular modems are used in devices to facilitate wireless communication. Cellular modems produce log files, which have to be analyzed by engineers when issues occur. Performing the analysis for large logs manually can be very time consuming, thus different approaches for trying to automate or simplify the process exist. This thesis presents design and development for a cellular modem log analysis tool. The tool is designed to take into account peculiarities of telecommunications protocols and cellular modems, especially of 5G New Radio Radio Resource Control protocol. A notation for defining analysis rules used by the tool is presented to be used alongside the tool. The developed tool is a proof-of-concept, with focus being on how the tool performs the analysis and how the notation can be used to define the wanted analysis rules. The features of the notation include defining expected content of protocol messages and order of log message sequences. The tool performs well with artificial modem logs, though some flaws in the notation are recognized. In the future, the tool and the notation should be updated with support for real cellular modem logs and evaluated in field use cases by cellular modem engineers.Matkapuhelinmodeemien lokitiedostojen analysointityökalun suunnittelu ja toteutus. Tiivistelmä. Tietoliikenneprotokollia ja matkapuhelinmodeemeja käytetään laitteissa langattoman tiedonsiirron mahdollistamiseksi. Matkapuhelinmodeemit tuottavat lokitiedostoja, joita insinöörien täytyy analysoida ongelmatilanteissa. Suurten lokitiedostojen analysointi manuaalisesti on työlästä, joten on olemassa keinoja prosessin automatisointiin tai yksinkertaistamiseen. Tämä työ esittelee suunnitelman ja toteutuksen matkapuhelinmodeemin lokitiedostojen analysointityökalulle. Työkalun suunnittelussa on otettu huomioon tietoliikenneprotokollien, erityisesti 5G New Radion radioresurssien hallintaprotokollan (RRC), ja matkapuhelinmodeemien erikoisuudet. Merkintäsäännöstö, jolla voidaan määritellä analyysisäännöt, esitellään työkalulle. Kehitetty työkalu on karkea prototyyppi. Kehityksessä keskitytään työkalun analyysiominaisuuksiin ja mahdollisuuksiin käyttää merkintäsäännöstöä määrittämään halutut analyysisäännöt. Merkintäsäännöstön ominaisuuksiin kuuluu odotettujen lokiviestien sisällön ja järjestyksen määrittely. Työkalu suoriutuu keinotekoisien modeemilokitiedostojen kanssa hyvin, mutta joitain vikoja merkintäsäännöstöstä havaittiin. Tulevaisuuden kehitystä ajatellen työkalu kannattaisi päivittää toimimaan aitojen matkapuhelinmodeemien lokitiedostojen kanssa, että sen kykyä suoriutua aidoista käyttötilanteista voitaisiin arvioida

MediateSpace: applying contextual mediation to the tuple space paradigm

I designed, implemented and evaluated a decentralised context-aware content distribution middleware. It can support a variety of applications, with all network communication handled transparently behind a tuple space based interface. Content is inserted into the network with an associated condition stipulating the context that must be matched to receive it. Conditions can be expressed using conjunctions, disjunctions, a form of universal and existential quantification and nested block scopes. Conditions are mapped onto a set of spatial indexes to enable lookup; and these are inserted into a distributed multi-dimensional spatial data structure (e.g. an R-Tree). They are also translated into an OWL representation to enable evaluation. Nodes bind to their most geographically proximate neighbours which allows distance-sensitive context sharing. The middleware is capability-aware, pushing computationally expensive tasks onto more capable nodes. I evaluated my system through benchmarks and simulation, defining condition classes which collectively represent a large portion of the condition space. Random conditions were generated from these classes. Node mobility was controlled through a number of probability distributions. Benchmark evaluation times were reasonable, evaluating 500 typical messages in 1.4 seconds each. When the number of stored contexts were reduced, this improved dramatically, evaluating 500 much more complicated conditions in one-tenth of a second each. The number and complexity of context parameters has a major impact on efficiency. The number of spatial indexes generated was reasonable for most conditions, with a 95th percentile of 6. However, existential quantification was a challenge for both condition evaluation and index generation due to the potentially large number of possible combinations of conditions. As expected, simulations found that the distribution of workload was very uneven because nodes tend to cluster in large cities; meaning that most communication is localised within these areas. Also, node density had a dramatic impact on the number of received messages as nodes within sparse areas were unable to obtain context information which precluded condition evaluation. I achieved my research goals of developing a distributed context-aware content distribution framework

Developing a Wireless Sensor Network Programming Language Application Guide Using Memsic Devices and LabVIEW

The principal objective of this project is to develop a wireless sensor network (WSN) programming language application guide for junior and senior undergraduate students in College of Technology, Architecture and Applied Engineering in Bowling Green State University. Memsic device, MoteWorks and LabVIEW software are used to conduct experiments in developing WSN applications after both software and hardware platform are verified to be usable with experimental and statistical analysis. The guide is divided into six chapters including both theoretical knowledge and practical experiments in WSN area. Programs, both in nesC language and LabVIEW are improved from previous work, tested to run successfully and noted in detail

The State-of-the-Art Survey on Optimization Methods for Cyber-physical Networks

Cyber-Physical Systems (CPS) are increasingly complex and frequently integrated into modern societies via critical infrastructure systems, products, and services. Consequently, there is a need for reliable functionality of these complex systems under various scenarios, from physical failures due to aging, through to cyber attacks. Indeed, the development of effective strategies to restore disrupted infrastructure systems continues to be a major challenge. Hitherto, there have been an increasing number of papers evaluating cyber-physical infrastructures, yet a comprehensive review focusing on mathematical modeling and different optimization methods is still lacking. Thus, this review paper appraises the literature on optimization techniques for CPS facing disruption, to synthesize key findings on the current methods in this domain. A total of 108 relevant research papers are reviewed following an extensive assessment of all major scientific databases. The main mathematical modeling practices and optimization methods are identified for both deterministic and stochastic formulations, categorizing them based on the solution approach (exact, heuristic, meta-heuristic), objective function, and network size. We also perform keyword clustering and bibliographic coupling analyses to summarize the current research trends. Future research needs in terms of the scalability of optimization algorithms are discussed. Overall, there is a need to shift towards more scalable optimization solution algorithms, empowered by data-driven methods and machine learning, to provide reliable decision-support systems for decision-makers and practitioners

Intelligent search in social communities of smartphone users

Social communities of smartphone users have recently gained significant interest due to their wide social penetration. The applications in this domain,however, currently rely on centralized or cloud-like architectures for data sharing and searching tasks, introducing both data-disclosure and performance concerns. In this paper, we present a distributed search architecture for intelligent search of objects in a mobile social community. Our framework, coined SmartOpt, is founded on an in-situ data storage model, where captured objects remain local on smartphones and searches then take place over an intelligent multi-objective lookup structure we compute dynamically. Our MO-QRT structure optimizes several conflicting objectives, using a multi-objective evolutionary algorithm that calculates a diverse set of high quality non-dominated solutions in a single run. Then a decision-making subsystem is utilized to tune the retrieval preferences of the query user. We assess our ideas both using trace-driven experiments with mobility and social patterns derived by Microsoft’s GeoLife project, DBLP and Pics ‘n’ Trails but also using our real Android SmartP2P3 system deployed over our SmartLab4 testbed of 40+ smartphones. Our study reveals that SmartOpt yields high query recall rates of 95%, with one order of magnitude less time and two orders of magnitude less energy than its competitors

Systemic Design for Food Self-Sufficiency in Urban Areas

This article adopts a systemic approach to address the problem of the operationalization of relationships between actors conducive to food self-sufficiency in urban areas. Through the use of Social Network Analysis (SNA), the literature on urban agriculture was analyzed, detecting eight key trends and topic areas. This information was used to design a generic recursive organizational structure with the identification of the key roles and functions for management and governance in the multi-level and multi-stakeholder relationships of a sustainable urban self-sufficient food production system, inspired by the principles of complexity management and organizational cybernetics. Methodologically, this is the first application that combines the exploratory capability of SNA and the recursive structure of the Viable System Model (VSM) to propose applicable organizational structures in any urban area, suggesting a new route for the study and application of systemic thinking in the development of urban agriculture schemes. However, due to the conceptual nature of this work, this study opens a discussion on how we can rethink interactions to seek continuous adaptation in food self-sufficiency, provide tools that foster inclusion, and adapt to every context to support the relevant actors and academics in urban agriculture.</jats:p

Symbol Emergence in Robotics: A Survey

Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic