In recent years, LEO satellite constellations have been used to solve many problems in communication, navigation, and observation, thanks to the low cost of launching satellites into LEO orbit and the low communication latency compared with GEO orbit. In order for LEO constellations to provide global coverage, the satellites must be able to communicate with each other, typically with a grid-like topology. In this work, we show that a static grid-like topology results in high communication latency. We propose the LEO Approximate Minimum Propagation delay (LAMP) topology, an alternative topology design method using dynamic links. The LAMP topology starts with a backbone network of persistent inter-satellite links to ensure connectivity in the constellation. Then, with the unused laser transceivers, temporary links are added such that the mean communication latency across the constellation is reduced. We show that with the LAMP topology, the average latency can be reduced by 18.5% compared to the static grid topology, and 5.61% compared to the existing Dynamic Topology of Satellites. Additionally, the LAMP topology has lower variability on mean propagation delay as the constellation parameters change compared to the static grid topology; regardless of constellation configuration, the mean propagation delay remains low.

Contact tracing can limit the spread of infectious diseases by notifying people of potential exposure to disease. Manual contact tracing is resource-intensive, but much of it can be automated using mobile phones, which are ubiquitous and can detect and record nearby contacts. Two major problems arise with automated contact tracing (ACT): preventing abuse for mass surveillance and accurately determining contacts. For example, the most widely adopted solution---Google and Apple's Exposure Notification (GAEN)---protects user privacy but suffers from inaccurate distance measurements that result in poor risk assessments. We propose to use collaboration among nearby devices to increase distance estimation accuracy, and therefore risk assessment accuracy, while minimizing the loss of user privacy. Our protocol, CoCoT, extends GAEN, a proximity-based, distributed ACT protocol, by adding an additional broadcast to share locally-derived distance estimates. To evaluate CoCoT, we develop a method for merging phone sensor datasets with human interaction datasets to approximate realistic scenarios and test our protocol. CoCoT improves distance estimate accuracy by 28% over the current best distance estimators and we analytically show impact on privacy, security, and battery consumption are minimal.

Compared to ordinary concurrent and distributed systems, cryptographic protocols are distinguished by the need to reason about interference by adversaries. We suggest a new layered approach to tame that complexity, via an executable protocol language whose semantics does not reveal an adversary directly, instead enforcing a set of intuitive hygiene rules. By virtue of those rules, protocols written in this language provably behave identically with or without interference by active Dolev-Yao-style adversaries. As a result, formal reasoning about protocols can be simplified enough that even naïve model checking can establish correctness of a multiparty protocol, through analysis of a state space with no adversary. We present the design and implementation of SPICY, short for Secure Protocols Implemented CorrectlY, including the semantics of its input languages; the essential safety proofs, formalized in the Coq theorem prover; and the automation techniques. We provide a preliminary evaluation of the tool's performance and capabilities via a handful of case studies.

This panel will explore how security topics are integrated into academic programs and future directions for improvements. It will address how early in time security should be introduced in programs like computer science and software engineering; and identify the critical takeaways that each graduating student should learn. We will try to separate out the important, practical concepts from the purely academic ones. We will also consider how well security programs translate to industry-focused needs: do students emerge with an understanding that is both deep and broad enough to be useful? In general, we will try to identify the pitfalls of current security education and how we can move forward as an academic community, in tandem with industry and government.

Protected database search systems cryptographically isolate the roles of reading from, writing to, and administering the database. This separation limits unnecessary administrator access and protects data in the case of system breaches. Since protected search was introduced in 2000, the area has grown rapidly, systems are offered by academia, start-ups, and established companies. However, there is no best protected search system or set of techniques. Design of such systems is a balancing act between security, functionality, performance, and usability. This challenge is made more difficult by ongoing database specialization, as some users will want the functionality of SQL, NoSQL, or NewSQL databases. This database evolution will continue, and the protected search community should be able to quickly provide functionality consistent with newly invented databases. At the same time, the community must accurately and clearly characterize the tradeoffs between different approaches. To address these challenges, we provide the following contributions:1) An identification of the important primitive operations across database paradigms. We find there are a small number of base operations that can be used and combined to support a large number of database paradigms.2) An evaluation of the current state of protected search systems in implementing these base operations. This evaluation describes the main approaches and tradeoffs for each base operation. Furthermore, it puts protected search in the context of unprotected search, identifying key gaps in functionality.3) An analysis of attacks against protected search for different base queries.4) A roadmap and tools for transforming a protected search system into a protected database, including an open-source performance evaluation platform and initial user opinions of protected search.

Abstract Modern mobile devices place a wide variety of sensors and services within the personal space of their users. As a result, these devices are capable of transparently monitoring many sensitive aspects of these users’ lives (e.g., location, health, or correspondences). Users typically trade access to this data for convenient applications and features, in many cases without a full appreciation of the nature and extent of the information that they are exposing to a variety of third parties. Nevertheless, studies show that users remain concerned about their privacy and vendors have similarly been increasing their utilization of privacy-preserving technologies in these devices. Still, despite significant efforts, these technologies continue to fail in fundamental ways, leaving users’ private data exposed. In this work, we survey the numerous components of mobile devices, giving particular attention to those that collect, process, or protect users’ private data. Whereas the individual components have been generally well studied and understood, examining the entire mobile device ecosystem provides significant insights into its overwhelming complexity. The numerous components of this complex ecosystem are frequently built and controlled by different parties with varying interests and incentives. Moreover, most of these parties are unknown to the typical user. The technologies that are employed to protect the users’ privacy typically only do so within a small slice of this ecosystem, abstracting away the greater complexity of the system. Our analysis suggests that this abstracted complexity is the major cause of many privacy-related vulnerabilities, and that a fundamentally new, holistic, approach to privacy is needed going forward. We thus highlight various existing technology gaps and propose several promising research directions for addressing and reducing this complexity.

We present IREP++, a rule learning algorithm similar to RIPPER and IREP. Like these other algorithms IREP++ produces accurate, human readable rules from noisy data sets. However IREP++ is able to produce such rule sets more quickly and can often express the target concept with fewer rules and fewer literals per rule resulting in a concept description that is easier for humans to understand. The new algorithm is fast enough for interactive training with very large data sets.

Macroscope is a network-based intrusion detection system that uses bottleneck verification (BV) to detect user-to-superuser attacks. BV detects novel computer attacks by looking for users performing high privilege operations without passing through legal "bottleneck" checkpoints that grant those privileges. Macroscope's BV implementation models many common Unix commands, and has extensions to detect intrusions that exploit trust relationships, as well as previously installed Trojan programs. BV performs at a false alarm rate more than two orders of magnitude lower than a reference signature verification system, while simultaneously increasing the detection rate from roughly 20% to 80% of user-to-superuser attacks.

We describe an object-oriented architecture for intelligent tutoring systems. The architecture is oriented around objects that represent the various knowledge elements that are to be taught by the tutor. Each of these knowledge elements, called bites, inherits both a knowledge organization describing the kind of knowledge represented and tutoring components that provide the functionality to accomplish standard tutoring tasks like diagnosis, student modeling, and task selection. We illustrate the approach with several tutors implemented in our lab.