Distributed Data-Gathering and -Processing in Smart Cities: An Information-Centric Approach

The technological advancements along with the proliferation of smart and connected devices (things) motivated the exploration of the creation of smart cities aimed at improving the quality of life, economic growth, and efficient resource utilization. Some recent initiatives defined a smart city network as the interconnection of the existing independent and heterogeneous networks and the infrastructure. However, considering the heterogeneity of the devices, communication technologies, network protocols, and platforms the interoperability of these networks is a challenge requiring more attention. In this paper, we propose the design of a novel Information-Centric Smart City architecture (iSmart), focusing on the demand of the future applications, such as efficient machineto-machine communication, low latency computation offloading, large data communication requirements, and advanced security. In designing iSmart, we use the Named-Data Networking (NDN) architecture as the underlying communication substrate to promote semantics-based communication and achieve seamless compute/data sharing

Prehospital Emergency Medical Services Challenges in Disaster; a Qualitative Study

Introduction: Prehospital Emergency Medical Care (EMC) is a critical service in disaster management. The aim of this study was to explore the challenges of prehospital Emergency Medical Services (EMS) during disaster response in Iran.Methods: A qualitative study was conducted from April 2015 to March 2017. Data were collected through in-depth, semi-structured interviews with 23 experienced individuals in the field of disaster that were selected using purposeful sampling. Data were analyzed using content analysis approach.Results: Fifteen sub-themes and the following six themes emerged in the analysis: challenges related to people, challenges related to infrastructure, challenges related to information management systems, challenges related to staff, challenges related to managerial issues and challenges related to medical care.Conclusions: Iran’s prehospital EMS has been chaotic in past disasters. Improvement of this process needs infrastructure reform, planning, staff training and public education.

A Generative Framework for Low-Cost Result Validation of Outsourced Machine Learning Tasks

The growing popularity of Machine Learning (ML) has led to its deployment in various sensitive domains, which has resulted in significant research focused on ML security and privacy. However, in some applications, such as autonomous driving, integrity verification of the outsourced ML workload is more critical--a facet that has not received much attention. Existing solutions, such as multi-party computation and proof-based systems, impose significant computation overhead, which makes them unfit for real-time applications. We propose Fides, a novel framework for real-time validation of outsourced ML workloads. Fides features a novel and efficient distillation technique--Greedy Distillation Transfer Learning--that dynamically distills and fine-tunes a space and compute-efficient verification model for verifying the corresponding service model while running inside a trusted execution environment. Fides features a client-side attack detection model that uses statistical analysis and divergence measurements to identify, with a high likelihood, if the service model is under attack. Fides also offers a re-classification functionality that predicts the original class whenever an attack is identified. We devised a generative adversarial network framework for training the attack detection and re-classification models. The evaluation shows that Fides achieves an accuracy of up to 98% for attack detection and 94% for re-classification.Comment: 16 pages, 11 figure

[Accepted Article Manuscript Version (Postprint)] Distributed Data-Gathering and -Processing in Smart Cities: An Information-Centric Approach

The technological advancements along with the proliferation of smart and connected devices (things) motivated the exploration of the creation of smart cities aimed at improving the quality of life, economic growth, and efficient resource utilization. Some recent initiatives defined a smart city network as the interconnection of the existing independent and heterogeneous networks and the infrastructure. However, considering the heterogeneity of the devices, communication technologies, network protocols, and platforms the interoperability of these networks is a challenge requiring more attention. In this paper, we propose the design of a novel Information-Centric Smart City architecture (iSmart), focusing on the demand of the future applications, such as efficient machineto-machine communication, low latency computation offloading, large data communication requirements, and advanced security. In designing iSmart, we use the Named-Data Networking (NDN) architecture as the underlying communication substrate to promote semantics-based communication and achieve seamless compute/data sharing

Uncertainty avoidance, risk tolerance and corporate takeover decisions

In this paper, we examine the role of national culture in corporate takeover decisions, by arguing that managerial risk tolerance (a combination of risk aversion and risk perception), at the national level, is a cultural trait and affects the expected net synergies CEOs require. We propose a theoretical framework that links CEO risk tolerance to the expected net synergies. We empirically show that CEOs of firms located in countries with lower levels of risk tolerance, measured by Hofstede’s (1980, 2001) uncertainty avoidance score, require higher premiums on takeovers, and show that uncertainty avoidance plays a greater role in relatively large takeovers. Additional testing reveals that CEOs from high uncertainty avoiding nations engage less in cross-border/cross-industry takeovers, suggesting that uncertainty avoidance captures more the CEO’s risk perception than his/her risk aversion

Catch Me If You Can: A Practical Framework to Evade Censorship in Information-Centric Networks

ABSTRACT Internet traffic is increasingly becoming multimedia-centric. Its growth is driven by the fast-growing mobile user base that is more interested in the content rather than its origin. These trends have motivated proposals for a new Internet networking paradigm-information-centric networking (ICN). This paradigm requires unique names for packets to leverage pervasive in-network caching, name-based routing, and nameddata provenance. However named-data routing makes user censorship easy. Hence an anti-censorship mechanism is imperative to help users mask their named queries to prevent censorship and identification. However, this masking mechanism should not adversely affect request rates. In this paper, we propose such an anti-censorship framework, which is lightweight and specifically targets low compute power mobile devices. We analyze our framework's information-theoretic secrecy and present perfect secrecy thresholds under different scenarios. We also analyze its breakability and computational security. Experimental results prove the framework's effectiveness: for requests it adds between 1.3-1.8 times in latency overhead over baseline ICN; significantly lesser than the overhead of the state of the art Tor (up to 38 times over TCP)