Poster: User-space Networking Libraries Control Plane Negotiations for Seamless Multi-connectivity

Offering seamless connectivity to devices capable of simultaneously using multiple communication interfaces continues to be a hard problem. This problem is important for edge computing because edge services may be available only on a subset of networks to which the device is capable of connecting to. We argue that various aspects of this problem can be addressed by leveraging the current trends of using user space libraries for networking, and allowing control plane negotiations between user devices and networks.Peer reviewe

Real, forged or deep fake? Enabling the ground truth on the internet

The proliferation of smartphones and mobile communication has enabled users to capture images or videos and share them immediately on social networking and messaging platforms. Unfortunately, these platforms are also used to manipulate the masses by performing social engineering attacks by sharing fabricated images (or videos). These attacks cause public shame, ethnic violence and claim lives. With the rise of advanced image processing tools, the deep fakes are automated, and their implications are boundless. In this article, we discuss different types of modification of images/videos and survey the corresponding methods and tools. We also highlight the ongoing efforts to detect fake images and videos using advanced machine learning tools and fact-checking. Along with these tools, we also need different complementary approaches discouraging the production and propagation of manipulative forged images and videos on the Internet. This paper further emphasizes that we desperately need socio-technological solutions that empower end-users with the right tools to make an informed moral decision while producing, uploading, and sharing media. Finally, supporting this, we discuss a holistic blockchain-based solution

A scalable infrastructure for CMS data analysis based on OpenStack Cloud and Gluster file system

Volume: 513Peer reviewe

Intelligent Air Pollution Sensors Calibration for Extreme Events and Drifts Monitoring

Air quality low-cost sensors are affordable and can be deployed in massive scale in order to enable high-resolution spatio-temporal air pollution information. However, they often suffer from sensing accuracy, in particular when they are used for capturing extreme events. We propose an intelligent sensors calibration method that facilitates correcting low-cost sensors' measurements accurately and detecting the calibrators' drift. The proposed calibration method uses Bayesian framework to establish white-box and black-box calibrators. We evaluate the method in a controlled experiment under different types of smoking events. The calibration results show that the method accurately estimates the aerosol mass concentration during the smoking events. We show that black-box calibrators are more accurate than white-box calibrators. However, black-box calibrators may drift easily when a new smoking event occurs, while white-box calibrators remain robust. Therefore, we implement both of the calibrators in parallel to extract both calibrators' strengths and also enable drifting monitoring for calibration models. We also discuss that our method is implementable for other types of low-cost sensors suffered from sensing accuracy.Peer reviewe

An overview of the DII-HEP Open Stack based CMS data analysis

An OpenStack based private cloud with the Gluster File System has been built and used with both CMS analysis and Monte Carlo simulation jobs in the Datacenter Indirection Infrastructure for Secure High Energy Physics (DII-HEP) project. On the cloud we run the ARC middleware that allows running CMS applications without changes on the job submission side. Our test results indicate that the adopted approach provides a scalable and resilient solution for managing resources without compromising on performance and high availability. To manage the virtual machines (VM) dynamically in an elastic fasion, we are testing the EMI authorization service (Argus) and the Execution Environment Service (Argus-EES). An OpenStack plugin has been developed for Argus-EES. The Host Identity Protocol (HIP) has been designed for mobile networks and it provides a secure method for IP multihoming. HIP separates the end-point identifier and locator role for IP address which increases the network availability for the applications. Our solution leverages HIP for traffic management. This presentation gives an update on the status of the work and our lessons learned in creating an OpenStack based cloud for HEP.Peer reviewe

The Bloom Clock for Causality Testing

Testing for causality between events in distributed executions is a fundamental problem. Vector clocks solve this problem but do not scale well. The probabilistic Bloom clock can determine causality between events with lower space, time, and message-space overhead than vector clock; however, predictions suffer from false positives. We give the protocol for the Bloom clock based on Counting Bloom filters and study its properties including the probabilities of a positive outcome and a false positive. We show the results of extensive experiments to determine how these above probabilities vary as a function of the Bloom timestamps of the two events being tested, and to determine the accuracy, precision, and false positive rate of a slice of the execution containing events in the temporal proximity of each other. Based on these experiments, we make recommendations for the setting of the Bloom clock parameters. We postulate the causality spread hypothesis from the application's perspective to indicate whether Bloom clocks will be suitable for correct predictions with high confidence. The Bloom clock design can serve as a viable space-, time-, and message-space-efficient alternative to vector clocks if false positives can be tolerated by an application

Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation

Background Techniques have been developed to compute statistics on distributed datasets without revealing private information except the statistical results. However, duplicate records in a distributed dataset may lead to incorrect statistical results. Therefore, to increase the accuracy of the statistical analysis of a distributed dataset, secure deduplication is an important preprocessing step. Methods We designed a secure protocol for the deduplication of horizontally partitioned datasets with deterministic record linkage algorithms. We provided a formal security analysis of the protocol in the presence of semi-honest adversaries. The protocol was implemented and deployed across three microbiology laboratories located in Norway, and we ran experiments on the datasets in which the number of records for each laboratory varied. Experiments were also performed on simulated microbiology datasets and data custodians connected through a local area network. Results The security analysis demonstrated that the protocol protects the privacy of individuals and data custodians under a semi-honest adversarial model. More precisely, the protocol remains secure with the collusion of up to N − 2 corrupt data custodians. The total runtime for the protocol scales linearly with the addition of data custodians and records. One million simulated records distributed across 20 data custodians were deduplicated within 45 s. The experimental results showed that the protocol is more efficient and scalable than previous protocols for the same problem. Conclusions The proposed deduplication protocol is efficient and scalable for practical uses while protecting the privacy of patients and data custodians