Optimized mobile thin clients through a MPEG-4 BiFS semantic remote display framework

According to the thin client computing principle, the user interface is physically separated from the application logic. In practice only a viewer component is executed on the client device, rendering the display updates received from the distant application server and capturing the user interaction. Existing remote display frameworks are not optimized to encode the complex scenes of modern applications, which are composed of objects with very diverse graphical characteristics. In order to tackle this challenge, we propose to transfer to the client, in addition to the binary encoded objects, semantic information about the characteristics of each object. Through this semantic knowledge, the client is enabled to react autonomously on user input and does not have to wait for the display update from the server. Resulting in a reduction of the interaction latency and a mitigation of the bursty remote display traffic pattern, the presented framework is of particular interest in a wireless context, where the bandwidth is limited and expensive. In this paper, we describe a generic architecture of a semantic remote display framework. Furthermore, we have developed a prototype using the MPEG-4 Binary Format for Scenes to convey the semantic information to the client. We experimentally compare the bandwidth consumption of MPEG-4 BiFS with existing, non-semantic, remote display frameworks. In a text editing scenario, we realize an average reduction of 23% of the data peaks that are observed in remote display protocol traffic

Towards Human Computable Passwords

An interesting challenge for the cryptography community is to design authentication protocols that are so simple that a human can execute them without relying on a fully trusted computer. We propose several candidate authentication protocols for a setting in which the human user can only receive assistance from a semi-trusted computer --- a computer that stores information and performs computations correctly but does not provide confidentiality. Our schemes use a semi-trusted computer to store and display public challenges $C_i\in[n]^k$. The human user memorizes a random secret mapping $\sigma:[n]\rightarrow\mathbb{Z}_d$ and authenticates by computing responses $f(\sigma(C_i))$ to a sequence of public challenges where $f:\mathbb{Z}_d^k\rightarrow\mathbb{Z}_d$ is a function that is easy for the human to evaluate. We prove that any statistical adversary needs to sample $m=\tilde{\Omega}(n^{s(f)})$ challenge-response pairs to recover $\sigma$, for a security parameter $s(f)$ that depends on two key properties of $f$. To obtain our results, we apply the general hypercontractivity theorem to lower bound the statistical dimension of the distribution over challenge-response pairs induced by $f$ and $\sigma$. Our lower bounds apply to arbitrary functions $f$ (not just to functions that are easy for a human to evaluate), and generalize recent results of Feldman et al. As an application, we propose a family of human computable password functions $f_{k_1,k_2}$ in which the user needs to perform $2k_1+2k_2+1$ primitive operations (e.g., adding two digits or remembering $\sigma(i)$), and we show that $s(f) = \min\{k_1+1, (k_2+1)/2\}$. For these schemes, we prove that forging passwords is equivalent to recovering the secret mapping. Thus, our human computable password schemes can maintain strong security guarantees even after an adversary has observed the user login to many different accounts.Comment: Fixed bug in definition of Q^{f,j} and modified proofs accordingl

Logics and practices of transparency and opacity in real-world applications of public sector machine learning

Machine learning systems are increasingly used to support public sector decision-making across a variety of sectors. Given concerns around accountability in these domains, and amidst accusations of intentional or unintentional bias, there have been increased calls for transparency of these technologies. Few, however, have considered how logics and practices concerning transparency have been understood by those involved in the machine learning systems already being piloted and deployed in public bodies today. This short paper distils insights about transparency on the ground from interviews with 27 such actors, largely public servants and relevant contractors, across 5 OECD countries. Considering transparency and opacity in relation to trust and buy-in, better decision-making, and the avoidance of gaming, it seeks to provide useful insights for those hoping to develop socio-technical approaches to transparency that might be useful to practitioners on-the-ground. An extended, archival version of this paper is available as Veale M., Van Kleek M., & Binns R. (2018). `Fairness and accountability design needs for algorithmic support in high-stakes public sector decision-making' Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI'18), http://doi.org/10.1145/3173574.3174014.Comment: 5 pages, 0 figures, presented as a talk at the 2017 Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2017), Halifax, Canada, August 14, 201

Data communication network at the ASRM facility

The main objective of the report is to present the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi. This report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing critical and manufacturing non-critical. The manufacturing critical buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B 1000. The manufacturing non-critical buildings will be connected by 10BASE-FL to the Business Information System (BIS) in the main computing center. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing critical hub and one of the OIS hubs. The network structure described in this report will be the basis for simulations to be carried out next year. The Comdisco's Block Oriented Network Simulator (BONeS) will be used for the network simulation. The main aim of the simulations will be to evaluate the loading of the OIS, the BIS, the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site

Code White: A Signed Code Protection Mechanism for Smartphones

This research develops Code White, a hardware-implemented trusted execution mechanism for the Symbian mobile operating system. Code White combines a signed whitelist approach with the execution prevention technology offered by the ARM architecture. Testing shows that it prevents all untrusted user applications from executing while allowing all trusted applications to load and run. Performance testing in contrast with an unmodified Symbian system shows that the difference in load time increases linearly as the application file size increases. The predicted load time for an application with a one megabyte code section remains well below one second, ensuring uninterrupted experience for the user. Smartphones have proven to be invaluable to military, civic, and business users due in a large part to their ability to execute code just like any desktop computer can. While many useful applications have been developed for these users, numerous malicious programs have also surfaced. And while smartphones have desktop-like capabilities to execute software, they do not have the same resources to scan for malware. More efficient means, like Code White, which minimize resource usage are needed to protect the data and capabilities found in smartphones

A Method and Tool for Finding Concurrency Bugs Involving Multiple Variables with Application to Modern Distributed Systems

Concurrency bugs are extremely hard to detect due to huge interleaving space. They are happening in the real world more often because of the prevalence of multi-threaded programs taking advantage of multi-core hardware, and microservice based distributed systems moving more and more applications to the cloud. As the most common non-deadlock concurrency bugs, atomicity violations are studied in many recent works, however, those methods are applicable only to single-variable atomicity violation, and don\u27t consider the specific challenge in distributed systems that have both pessimistic and optimistic concurrency control. This dissertation presents a tool using model checking to predict atomicity violation concurrency bugs involving two shared variables or shared resources. We developed a unique method inferring correlation between shared variables in multi-threaded programs and shared resources in microservice based distributed systems, that is based on dynamic analysis and is able to detect the correlation that would be missed by static analysis. For multi-threaded programs, we use a binary instrumentation tool to capture runtime information about shared variables and synchronization events, and for microservice based distributed systems, we use a web proxy to capture HTTP based traffic about API calls and the shared resources they access including distributed locks. Based on the detected correlation and runtime trace, the tool is powerful and can explore a vast interleaving space of a multi-threaded program or a microservice based distributed system given a small set of captured test runs. It is applicable to large real-world systems and can predict atomicity violations missed by other related works for multi-threaded programs and a couple of previous unknown atomicity violation in real world open source microservice based systems. A limitation is that redundant model checking may be performed if two recorded interleaved traces yield the same partial order model