41 research outputs found
Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK
Cyber adversaries have increasingly leveraged social engineering attacks to
breach large organizations and threaten the well-being of today's online users.
One clever technique, the "watering hole" attack, compromises a legitimate
website to execute drive-by download attacks by redirecting users to another
malicious domain. We introduce a game-theoretic model that captures the salient
aspects for an organization protecting itself from a watering hole attack by
altering the environment information in web traffic so as to deceive the
attackers. Our main contributions are (1) a novel Social Engineering Deception
(SED) game model that features a continuous action set for the attacker, (2) an
in-depth analysis of the SED model to identify computationally feasible
real-world cases, and (3) the CyberTWEAK algorithm which solves for the optimal
protection policy. To illustrate the potential use of our framework, we built a
browser extension based on our algorithms which is now publicly available
online. The CyberTWEAK extension will be vital to the continued development and
deployment of countermeasures for social engineering.Comment: IAAI-20, AICS-2020 Worksho
Mathematical Programming formulations for the efficient solution of the -sum approval voting problem
In this paper we address the problem of electing a committee among a set of
candidates and on the basis of the preferences of a set of voters. We
consider the approval voting method in which each voter can approve as many
candidates as she/he likes by expressing a preference profile (boolean
-vector). In order to elect a committee, a voting rule must be established
to `transform' the voters' profiles into a winning committee. The problem
is widely studied in voting theory; for a variety of voting rules the problem
was shown to be computationally difficult and approximation algorithms and
heuristic techniques were proposed in the literature. In this paper we follow
an Ordered Weighted Averaging approach and study the -sum approval voting
(optimization) problem in the general case . For this problem we
provide different mathematical programming formulations that allow us to solve
it in an exact solution framework. We provide computational results showing
that our approach is efficient for medium-size test problems ( up to 200,
up to 60) since in all tested cases it was able to find the exact optimal
solution in very short computational times
Top-k Multiclass SVM
Class ambiguity is typical in image classification problems with a large
number of classes. When classes are difficult to discriminate, it makes sense
to allow k guesses and evaluate classifiers based on the top-k error instead of
the standard zero-one loss. We propose top-k multiclass SVM as a direct method
to optimize for top-k performance. Our generalization of the well-known
multiclass SVM is based on a tight convex upper bound of the top-k error. We
propose a fast optimization scheme based on an efficient projection onto the
top-k simplex, which is of its own interest. Experiments on five datasets show
consistent improvements in top-k accuracy compared to various baselines.Comment: NIPS 201
An optimal randomized algorithm for d-variate zonoid depth
AbstractA randomized linear expected-time algorithm for computing the zonoid depth [R. Dyckerhoff, G. Koshevoy, K. Mosler, Zonoid data depth: Theory and computation, in: A. Prat (Ed.), COMPSTAT 1996—Proceedings in Computational Statistics, Physica-Verlag, Heidelberg, 1996, pp. 235–240; K. Mosler, Multivariate Dispersion, Central Regions and Depth. The Lift Zonoid Approach, Lecture Notes in Statistics, vol. 165, Springer-Verlag, New York, 2002] of a point with respect to a fixed dimensional point set is presented
Averaging the k largest distances among n: k-centra in Banach spaces
Given a Banach space X let A ⊂ X containing at least k points. In location theory, reliability analysis, and theoretical computer science, it is useful to minimize the sum of distances from the k furthest points of A: this problem has received some attention for X a finite metric space (a network), see, e.g., [Discrete Appl. Math. 109 (2001) 293]; in the case X = En, k = 2 or 3, and A compact some results have been given in [Math. Notes 59 (1996) 507]; also, in the field of theoretical computer science it has been considered in [T. Tokuyama, Minimax parametric optimization problems in multidimensional parametric searching, in: Proc. 33rd Annu. ACM Symp. on Theory of Computing, 2001, pp. 75–84]. Here we study the above problem for a finite set A ⊂ X, generalizing—among others things—the results in [Math. Notes 59 (1996) 507].Ministerio de Ciencia y TecnologÃ
Mathematical programming formulations for the efficient solution of the k-sum approval voting problem
In this paper we address the problem of electing a committee among a set of m candidates and on the basis of the preferences of a set of n voters. We consider the approval voting method in which each voter can approve as many candidates as she/he likes by expressing a preference profile (boolean m-vector). In order to elect a committee, a voting rule must be established to ‘transform’ the n voters’ profiles into a winning committee. The problem
is widely studied in voting theory; for a variety of voting rules the problem was shown to be computationally difficult and approximation algorithms and heuristic techniques were proposed in the literature. In this paper we follow an Ordered Weighted Averaging approach and study the k-sum approval voting (optimization) problem in the general case 1 ≤ k < n. For this problem we provide different mathematical programming formulations that allow us
to solve it in an exact solution framework. We provide computational results showing that our approach is efficient for medium-size test problems (n up to 200, m up to 60) since in all tested cases it was able to find the exact optimal solution in very short computational times.Ministerio de EconomÃa y CompetitividadFondo Europeo de Desarrollo Regiona