On Time-sensitive Control Dependencies

We present efficient algorithms for time-sensitive control dependencies (CDs). If statement y is time-sensitively control dependent on statement x , then x decides not only whether y is executed but also how many timesteps after x . If y is not standard control dependent on x , but time-sensitively control dependent, then y will always be executed after x , but the execution time between x and y varies. This allows us to discover, e.g., timing leaks in security-critical software. We systematically develop properties and algorithms for time-sensitive CDs, as well as for nontermination-sensitive CDs. These work not only for standard control flow graphs (CFGs) but also for CFGs lacking a unique exit node (e.g., reactive systems). We show that Cytron’s efficient algorithm for dominance frontiers [ 10 ] can be generalized to allow efficient computation not just of classical CDs but also of time-sensitive and nontermination-sensitive CDs. We then use time-sensitive CDs and time-sensitive slicing to discover cache timing leaks in an AES implementation. Performance measurements demonstrate scalability of the approach.

A new and efficient algorithm to look for periodic patterns on spatio-temporal databases

Big Data is a generic term that involves the storing and processing of a large amount of data. This large amount of data has been promoted by technologies such as mobile applications, Internet of Things (IoT), and Geographic Information Systems (GIS). An example of GIS is a Spatio-Temporal Database (STDB). A complex problem to address in terms of processing time is pattern searching on STDB. Nowadays, high information processing capacity is available everywhere. Nevertheless, the pattern searching problem on STDB using traditional Data Mining techniques is complex because the data incorporate the temporal aspect. Traditional techniques of pattern searching, such as time series, do not incorporate the spatial aspect. For this reason, traditional algorithms based on association rules must be adapted to find these patterns. Most of the algorithms take exponential processing times. In this paper, a new efficient algorithm (named Minus-F1) to look for periodic patterns on STDB is presented. Our algorithm is compared with Apriori, Max-Subpattern, and PPA algorithms on synthetic and real STDB. Additionally, the computational complexities for each algorithm in the worst cases are presented. Empirical results show that Minus-F1 is not only more efficient than Apriori, Max-Subpattern, and PAA, but also it presents a polynomial behavior.

Efficient Intersection Computation of the Bezier and Hermite Curves with Axis Aligned Bounding Box

Cubic parametric curves are used in many applications including the CAD/CAM systems. Especially the Hermite, Bezier and Coons formulations of a cubic parametric curve are used in E2 and E3 space. This paper presents efficient algorithm for the intersection computation of a cubic parametric curve with the Axis Aligned Bounding Box (AAB Box). Usual solution is to represent the cubic curve by a polyline, i.e. actually by sampled points of the given curve. However, this approach is dependent on the sampling frequency and can lead to problems especially in CAD/CAM systems and numerically controlled machines use.