Alvaro A. Cárdenas

Secure Control: Towards Survivable Cyber-Physical Systems

In this position paper we investigate the security of cyber-physical systems. We (1) identify and define the problem of secure control, (2) investigate the defenses that information security and control theory can provide, and (3) propose a set of challenges that need to be addressed to improve the survivability of cyber-physical systems.

Attacks against process control systems: risk assessment, detection, and response

In the last years there has been an increasing interest in the security of process control and SCADA systems. Furthermore, recent computer attacks such as the Stuxnet worm, have shown there are parties with the motivation and resources to effectively attack control systems. While previous work has proposed new security mechanisms for control systems, few of them have explored new and fundamentally different research problems for securing control systems when compared to securing traditional information technology (IT) systems. In particular, the sophistication of new malware attacking control systems--malware including zero-days attacks, rootkits created for control systems, and software signed by trusted certificate authorities--has shown that it is very difficult to prevent and detect these attacks based solely on IT system information. In this paper we show how, by incorporating knowledge of the physical system under control, we are able to detect computer attacks that change the behavior of the targeted control system. By using knowledge of the physical system we are able to focus on the final objective of the attack, and not on the particular mechanisms of how vulnerabilities are exploited, and how the attack is hidden. We analyze the security and safety of our mechanisms by exploring the effects of stealthy attacks, and by ensuring that automatic attack-response mechanisms will not drive the system to an unsafe state. A secondary goal of this paper is to initiate the discussion between control and security practitioners--two areas that have had little interaction in the past. We believe that control engineers can leverage security engineering to design--based on a combination of their best practices--control algorithms that go beyond safety and fault tolerance, and include considerations to survive targeted attacks.

Safe and Secure Networked Control Systems under Denial-of-Service Attacks

We consider the problem of security constrained optimal control for discrete-time, linear dynamical systems in which control and measurement packets are transmitted over a communication network. The packets may be jammed or compromised by a malicious adversary. For a class of denial-of-service (DoS) attack models, the goal is to find an (optimal) causal feedback controller that minimizes a given objective function subject to safety and power constraints. We present a semi-definite programming based solution for solving this problem. Our analysis also presents insights on the effect of attack models on solution of the optimal control problem.

Detection and prevention of MAC layer misbehavior in ad hoc networks

Selfish behavior at the MAC layer can have devastating side effects on the performance of wireless networks, similar to the effects of DoS attacks. In this paper we focus on the prevention and detection of the manipulation of the backoff mechanism by selfish nodes in 802.11. We first propose an algorithm to ensure honest backoffs when at least one, either the receiver or the sender is honest. Then we discuss detection algorithms to deal with the problem of colluding selfish nodes. Although we have focused on the MAC layer of 802.11, our approach is general and can serve as a guideline for the design of any probabilistic distributed MAC protocol.

Big Data Analytics for Security

Big data is changing the landscape of security tools for network monitoring, security information and event management, and forensics; however, in the eternal arms race of attack and defense, security researchers must keep exploring novel ways to mitigate and contain sophisticated attackers.

Semantic middleware for the Internet of Things

The Internet of Things (IoT) refers to extending the Internet to devices such as home appliances, consumer electronics, and sensor networks. As multiple heterogeneous devices attempt to create area networks, one of the major challenges is the interoperability and com-posability of their services. The traditional way to address interoperability is to define standards; however, there are many standards and specifications that are incompatible with each other. In this paper we propose an application layer solution for interoperability. The key idea is to utilize device semantics provided by existing specifications and dynamically wrap them in our middleware into semantic services. Next, with the help of Semantic Web technologies, users can create and then execute complex tasks involving multiple heterogeneous devices. We demonstrate how our framework automates interoperability without any modifications to existing standards, devices, or technologies, while providing to the user an intuitive semantic interface with services that can be executed by combining devices in the network.

Towards a secure and interoperable DRM architecture

In this paper we look at the problem of interoperability of digital rights management (DRM)systems in home networks. We introduce an intermediate module called the Domain Interoperability Manager (DIM) to efficiently deal with the problem of content and license translation across different DRM regimes. We also consider the threat model specific to interoperability systems, and introduce threats such as the cross-compliancy and splicing attacks. We formalize the adversary model and define security of an interoperable DRM system with respect to this adversary. We finalize by proposing detailed protocols which achieve our security requirements. In order to achieve these requirements we provide novel applications of recently proposed proxy resignature and proxy re-encryption algorithms.

Understanding the physical and economic consequences of attacks on control systems

Abstract This paper describes an approach for developing threat models for attacks on control systems. These models are useful for analyzing the actions taken by an attacker who gains access to control system assets and for evaluating the effects of the attacker’s actions on the physical process being controlled. The paper proposes models for integrity attacks and denial-of-service (DoS) attacks, and evaluates the physical and economic consequences of the attacks on a chemical reactor system. The analysis reveals two important points. First, a DoS attack does not have a significant effect when the reactor is in the steady state; however, combining the DoS attack with a relatively innocuous integrity attack rapidly causes the reactor to move to an unsafe state. Second, an attack that seeks to increase the operational cost of the chemical reactor involves a radically different strategy than an attack on plant safety (i.e., one that seeks to shut down the reactor or cause an explosion).

Rethinking security properties, threat models, and the design space in sensor networks: A case study in SCADA systems

In recent years we have witnessed the emergence and establishment of research in sensor network security. The majority of the literature has focused on discovering numerous vulnerabilities and attacks against sensor networks, along with suggestions for corresponding countermeasures. However, there has been little guidance for understanding the holistic nature of sensor network security for practical deployments. In this paper, we discuss these concerns and propose a taxonomy composed of the security properties of the sensor network, the threat model, and the security design space. In particular, we try to understand the application-layer goals of a sensor network, and provide a guide to research challenges that need to be addressed in order to prioritize our defenses against threats to application-layer goals.

A framework for the evaluation of intrusion detection systems

Classification accuracy in intrusion detection systems (IDSs) deals with such fundamental problems as how to compare two or more IDSs, how to evaluate the performance of an IDS, and how to determine the best configuration of the IDS. In an effort to analyze and solve these related problems, evaluation metrics such as the Bayesian detection rate, the expected cost, the sensitivity and the intrusion detection capability have been introduced. In this paper, we study the advantages and disadvantages of each of these performance metrics and analyze them in a unified framework. Additionally, we introduce the intrusion detection operating characteristic (IDOC) curves as a new IDS performance tradeoff which combines in an intuitive way the variables that are more relevant to the intrusion detection evaluation problem. We also introduce a formal framework for reasoning about the performance of an IDS and the proposed metrics against adaptive adversaries. We provide simulations and experimental results to illustrate the benefits of the proposed framework