Mason Wright

A moving target defense approach to mitigate DDoS attacks against proxy-based architectures

Distributed Denial of Service attacks against high-profile targets have become more frequent in recent years. In response to such massive attacks, several architectures have adopted proxies to introduce layers of indirection between end users and target services and reduce the impact of a DDoS attack by migrating users to new proxies and shuffling clients across proxies so as to isolate malicious clients. However, the reactive nature of these solutions presents weaknesses that we leveraged to develop a new attack - the proxy harvesting attack - which enables malicious clients to collect information about a large number of proxies before launching a DDoS attack. We show that current solutions are vulnerable to this attack, and propose a moving target defense technique consisting in periodically and proactively replacing one or more proxies and remapping clients to proxies. Our primary goal is to disrupt the attackers reconnaissance effort. Additionally, to mitigate ongoing attacks, we propose a new client-to-proxy assignment strategy to isolate compromised clients, thereby reducing the impact of attacks. We validate our approach both theoretically and through simulation, and show that the proposed solution can effectively limit the number of proxies an attacker can discover and isolate malicious clients.

Programming in K-12 science classrooms

Introducing students to visual programming as a pathway to text-based programming.

From Agents to Continuous Change via Aesthetics: Learning Mechanics with Visual Agent-Based Computational Modeling.

Novice learners find motion as a continuous process of change challenging to understand. In this paper, we present a pedagogical approach based on agent-based, visual programming to address this issue. Integrating agent-based programming, in particular, Logo programming, with curricular science has been shown to be challenging in previous research on educational computing. We present a new Logo-based visual programming language—ViMAP—and, a sequence of learning activities involving programming and modeling, designed specifically to support seamless integration between programming and learning kinematics. We describe relevant affordances of the ViMAP environment that supports such seamless integration. We then present ViMAP-MoMo, a curricular unit designed in ViMAP for modeling kinematics, for a wide range of students (elementary—high school). Finally, we describe in detail a sequence of learning activities in three phases, discuss the underlying rationale for each phase, and where relevant, report results in the form of observational data from two studies.

Moving Target Defense against DDoS Attacks: An Empirical Game-Theoretic Analysis

Distributed denial-of-service attacks are an increasing problem facing web applications, for which many defense techniques have been proposed, including several moving-target strategies. These strategies typically work by relocating targeted services over time, increasing uncertainty for the attacker, while trying not to disrupt legitimate users or incur excessive costs. Prior work has not shown, however, whether and how a rational defender would choose a moving-target method against an adaptive attacker, and under what conditions. We formulate a denial-of-service scenario as a two-player game, and solve a restricted-strategy version of the game using the methods of empirical game-theoretic analysis. Using agent-based simulation, we evaluate the performance of strategies from prior literature under a variety of attacks and environmental conditions. We find evidence for the strategic stability of various proposed strategies, such as proactive server movement, delayed attack timing, and suspected insider blocking, along with guidelines for when each is likely to be most effective.

Mathematical Machines and Integrated Stem: An Intersubjective Constructionist Approach

In this chapter, we report two studies in which 3rd- and 4th-grade students used a distributed computing infrastructure (ViMAP-Tangible) in order to collaboratively invent “mathematical machines” for generating geometric shapes. ViMAP-Tangible combines the ViMAP visual programming language with a distributed computing infrastructure, in which students collaboratively control the behavior of a virtual agent using both mechanical devices and virtual algorithms. The curricular activities integrate engineering practices such as user-centered design; agent-based computer programming; mathematical reasoning about multiplication, rates, and geometry; and physical science concepts central to learning Newtonian mechanics. In Study 1, we investigate the key affordances of such a distributed computing environment for learning Integrated STEM, and identify the relationships between the various elements of students’ physical constructions and computational models, and their STEM learning outcomes. Study 2 is a deeper investigation of the effect of iterative user testing on the refinement of children’s designs and their STEM learning.

Welfare Effects of Market Making in Continuous Double Auctions

We investigate the effects of market making on market performance, focusing on allocative efficiency as well as gains from trade accrued by background traders. We employ empirical simulation-based methods to evaluate heuristic strategies for market makers as well as background investors in a variety of complex trading environments. Our market model incorporates private and common valuation elements, with dynamic fundamental value and asymmetric information. In this context, we compare the surplus achieved by background traders in strategic equilibrium, with and without a market maker. Our findings indicate that the presence of the market maker strongly tends to increase not only total surplus across a variety of environments, but also background-trader surplus in thin markets with impatient investors, with urgency captured by a limited trading horizon. Comparison across environments reveals factors that influence the existence and magnitude of benefits provided by the market maker function.

A Multi-Agent Approach for Modeling Oligarchs' Campaign Donations with Simulated Spatial Elections

We present the OLIGO model, a multi-agent simulation of oligarchy. We extend previous multi-agent-based, spatial models of democracy by adding a new class of agents, oligarchs, which represent leaders of firms in a common industry who lobby for beneficial subsidies through campaign donations. We test hypotheses from the literature in political economics on the behavior of oligarchs and political parties as they interact, under conditions of imperfect information and bounded rationality. By verifying that central hypotheses from the economics literature hold for the OLIGO model, we accomplish two goals: (1) We show that the simple rules agents follow in our model are sufficient to capture much of the complex dynamics of this politico-economic system; (2) we validate these results from prior studies that used analytic methods, using an alternative, agent-based modeling method; and (3) we derive support for the claim that the OLIGO model is a useful test environment for novel hypotheses about oligarchs’ campaign donation behavior.