Many browser-based attacks can be prevented by using separate browsers for separate web sites. However, most users access the web with only one browser. We explain the security benefits that using multiple browsers provides in terms of two concepts: entry-point restriction and state isolation. We combine these concepts into a general app isolation mechanism that can provide the same security benefits in a single browser. While not appropriate for all types of web sites, many sites with high-value user data can opt in to app isolation to gain defenses against a wide variety of browser-based attacks. We implement app isolation in the Chromium browser and verify its security properties using finite-state model checking. We also measure the performance overhead of app isolation and conduct a large-scale study to evaluate its adoption complexity for various types of sites, demonstrating how the app isolation mechanisms are suitable for protecting a number of high-value Web applications, such as online banking.

There is a growing concern about the increasing vulnerability of future computing systems to errors in the underlying hardware. Traditional redundancy techniques are expensive for designing energy-efficient systems that are resilient to high error rates. We present Error Resilient System Architecture (ERSA), a low-cost robust system architecture for emerging killer probabilistic applications such as Recognition, Mining and Synthesis (RMS) applications. While resilience of such applications to errors in low-order bits of data is well-known, execution of such applications on error-prone hardware significantly degrades output quality (due to high-order bit errors and crashes). ERSA achieves high error resilience to high-order bit errors and control errors (in addition to low-order bit errors) using a judicious combination of 3 key ideas: (1) asymmetric reliability in many-core architectures, (2) error-resilient algorithms at the core of probabilistic applications, and (3) intelligent software optimizations. Error injection experiments on a multi-core ERSA hardware prototype demonstrate that, even at very high error rates of 20,000 errors/second/core or 2×10-4error/cycle/core (with errors injected in architecturally-visible registers), ERSA maintains 90% or better accuracy of output results, together with minimal impact on execution time, for probabilistic applications such as K-Means clustering, LDPC decoding and Bayesian networks. Moreover, we demonstrate the effectiveness of ERSA in tolerating high rates of static memory errors that are characteristic of emerging challenges such as Vccmin problems and erratic bit errors. Using the concept of configurable reliability, ERSA platforms may also be adapted for general-purpose applications that are less resilient to errors (but at higher costs).

Black-box web application vulnerability scanners are automated tools that probe web applications for security vulnerabilities. In order to assess the current state of the art, we obtained access to eight leading tools and carried out a study of: (i) the class of vulnerabilities tested by these scanners, (ii) their effectiveness against target vulnerabilities, and (iii) the relevance of the target vulnerabilities to vulnerabilities found in the wild. To conduct our study we used a custom web application vulnerable to known and projected vulnerabilities, and previous versions of widely used web applications containing known vulnerabilities. Our results show the promise and effectiveness of automated tools, as a group, and also some limitations. In particular, "stored" forms of Cross Site Scripting (XSS) and SQL Injection (SQLI) vulnerabilities are not currently found by many tools. Because our goal is to assess the potential of future research, not to evaluate specific vendors, we do not report comparative data or make any recommendations about purchase of specific tools.