Information Disclosure as a Means to Security

Lecture Notes in Computer Science, 2010

Even the most well-motivated models of information security have application limitations due to the inherent uncertainties involving risk. This paper exemplifies a formal mechanism for resolving this kind of uncertainty in interdependent security (IDS) scenarios. We focus on a single IDS model involving a computer network, and adapt the model to capture a notion that players have only a very rough idea of security threats and underlying structural ramifications. We formally resolve uncertainty by means of a probability distribution on risk parameters that is common knowledge to all players. To illustrate how this approach might yield fruitful applications, we postulate a well-motivated distribution, compute Bayesian Nash equilibria and tipping conditions for the derived model, and compare these with the analogous conditions for the original IDS model.

2018

Strong Stackelberg equilibrium (SSE) is the standard solution concept of Stackelberg security games. The SSE assumes that the follower breaks ties in favor of the leader and this is widely acknowledged and justified by the assertion that the defender can often induce the attacker to choose a preferred action by making an infinitesimal adjustment to her strategy. Unfortunately, in security games with resource assignment constraints, the assertion might not be valid. To overcome this issue, inspired by the notion of inducibility and the pessimistic Stackelberg equilibrium [20, 21], this paper presents the inducible Stackelberg equilibrium (ISE), which is guaranteed to exist and avoids overoptimism as the outcome can always be induced with infinitesimal strategy deviation. Experimental evaluation unveils the significant overoptimism and sub-optimality of SSE and thus, verifies the advantage of the ISE as an alternative solution concept.

Proceedings of the AAAI Conference on Artificial Intelligence, 2019

Strong Stackelberg equilibrium (SSE) is the standard solution concept of Stackelberg security games. As opposed to the weak Stackelberg equilibrium (WSE), the SSE assumes that the follower breaks ties in favor of the leader and this is widely acknowledged and justified by the assertion that the defender can often induce the attacker to choose a preferred action by making an infinitesimal adjustment to her strategy. Unfortunately, in security games with resource assignment constraints, the assertion might not be valid; it is possible that the defender cannot induce the desired outcome. As a result, many results claimed in the literature may be overly optimistic. To remedy, we first formally define the utility guarantee of a defender strategy and provide examples to show that the utility of SSE can be higher than its utility guarantee. Second, inspired by the analysis of leader’s payoff by Von Stengel and Zamir (2004), we provide the solution concept called the inducible Stackelberg e...

… . Bayesian Stackelberg …, 2008

In a class of games known as Stackelberg games, one agent (the leader) must commit to a strategy that can be observed by the other agent (the adversary/follower) before the adversary chooses its own strategy. We consider Bayesian Stackelberg games, in which the leader is uncertain about the type of the adversary it may face. Such games are important in security domains, where, for example, a security agent (leader) must commit to a strategy of patrolling certain areas, and an adversary (follower) can observe this strategy over time before choosing where to attack. We present here two different MIP-formulations, ASAP (providing approximate policies with controlled randomization) and DOBSS (providing optimal policies) for Bayesian Stackelberg games. DOBSS is currently the fastest optimal procedure for Bayesian Stackelberg games and is in use by police at the Los Angeles International Airport(LAX) to schedule their activities.

Economics of Information Security and Privacy, 2010

In the realm of information security, lack of information about other users' incentives in a network can lead to inefficient security choices and reductions in individuals' payoffs. We propose, contrast and compare three metrics for measuring the price of uncertainty due to the departure from the payoffoptimal security outcomes under complete information. Per the analogy with other efficiency metrics, such as the price of anarchy, we define the price of uncertainty as the maximum discrepancy in expected payoff in a complete information environment versus the payoff in an incomplete information environment. We consider difference, payoff-ratio, and cost-ratio metrics as canonical nontrivial measurements of the price of uncertainty.

2015

Stackelberg security games have been widely deployed in recent years to schedule security resources. An assumption in most existing security game models is that one security resource assigned to a target only protects that target. However, in many important real-world security scenarios, when a resource is assigned to a target, it exhibits protection externalities: that is, it also protects other "neighbouring" targets. We investigate such Security Games with Protection Externalities (SPEs). First, we demonstrate that computing a strong Stackelberg equilibrium for an SPE is NP-hard, in contrast with traditional Stackelberg security games which can be solved in polynomial time. On the positive side, we propose a novel column generation based approach—CLASPE—to solve SPEs. CLASPE features the following novelties: 1) a novel mixed-integer linear programming formulation for the slave problem; 2) an extended greedy approach with a constant-factor approximation ratio to speed up...

2015

Stackelberg security games (SSGs) are now established as a powerful tool in security domains. In this paper , we consider a new dimension of security games: the risk preferences of the attacker. Previous work assumes a risk-neutral attacker that maximizes his expected reward. However, extensive studies show that the attackers in some domains are in fact risk-averse, e.g., terrorist groups in counter-terrorism domains. The failure to incorporate the risk aversion in SSG models may lead the defender to suffer significant losses. Additionally, defenders are uncertain about the degree of attacker’s risk aversion. Motivated by this challenge this paper provides the following five contributions: (i) we propose a novel model for security games against risk-averse attackers with uncertainty in the degree of their risk aversion; (ii) we develop an intuitive MIBLP formulation based on previous security games research, but find that it finds locally optimal solutions and is unable to scale up;...

2011

Attackers' private information is one of the main issues in defensive resource allocation games in homeland security. The outcome of a defense resource allocation decision critically depends on the accuracy of estimations about the attacker's attributes. However, terrorists' goals may be unknown to the defender, necessitating robust decisions by the defender.

2009 IEEE International Conference on Communications, 2009

We study two-player security games which can be viewed as sequences of nonzero-sum matrix games where at each stage of the iterations the players make imperfect observations of each other's previous actions. The players are the Attacker and the Defense System, who have at their disposal two possible actions each. For the former, the two actions are "attack" and "not to attack", and for the latter they are "defend" and "not to defend". The underlying decision process can be viewed as a fictitious play (FP) game, but what differentiates this class from the standard one is that the communication channels that carry action information from one player to the other, or the sensor systems, are error prone. Two possible scenarios are addressed in the paper: (i) the error probabilities associated with the sensor systems are known to the players, then our analysis provides guidelines for each player to reach the Nash equilibrium (NE), which is related to the NE of the underlying static game; (ii) the error probabilities are unknown to the players, in which case we study the effect of errors in the observations on the convergence to the NE and the final outcome of the game. We discuss both classical FP and stochastic FP, where for the latter the payoff function of each player includes an entropy term to randomize its own strategy, which can be interpreted as a way of concealing its true strategy.

International Journal of Communications, Network and System Sciences, 2017

To protect the systems exposed to the Internet against attacks, a security system with the capability to engage with the attacker is needed. There have been attempts to model the engagement/interactions between users, both benign and malicious, and network administrators as games. Building on such works, we present a game model which is generic enough to capture various modes of such interactions. The model facilitates stochastic games with imperfect information. The information is imperfect due to erroneous sensors leading to incorrect perception of the current state by the players. To model this error in perception distributed over other multiple states, we use Euclidean distances between the outputs of the sensors. We build a 5-state game to represent the interaction of the administrator with the user. The states correspond to 1) the user being out of the system in the Internet, and after logging in to the system; 2) having low privileges; 3) having high privileges; 4) when he successfully attacks and 5) gets trapped in a honeypot by the administrator. Each state has its own action set. We present the game with a distinct perceived action set corresponding to each distinct information set of these states. The model facilitates stochastic games with imperfect information. The imperfect information is due to erroneous sensors leading to incorrect perception of the current state by the players. To model this error in perception distributed over the states, we use Euclidean distances between outputs of the sensors. A numerical simulation of an example game is presented to show the evaluation of rewards to the players and the preferred strategies. We also present the conditions for formulating the strategies when dealing with more than one attacker and making collaborations.