Modern smartphone operating systems support the development of third-party applications with open system APIs. In addition to an open API, the Android operating system also provides a rich inter-application message passing system. This encourages inter-application collaboration and reduces developer burden by facilitating component reuse. Unfortunately, message passing is also an application attack surface. The content of messages can be sniffed, modified, stolen, or replaced, which can compromise user privacy. Also, a malicious application can inject forged or otherwise malicious messages, which can lead to breaches of user data and violate application security policies.We examine Android application interaction and identify security risks in application components. We provide a tool, ComDroid, that detects application communication vulnerabilities. ComDroid can be used by developers to analyze their own applications before release, by application reviewers to analyze applications in the Android Market, and by end users. We analyzed 20 applications with the help of ComDroid and found 34 exploitable vulnerabilities; 12 of the 20 applications have at least one vulnerability.

/pdf/analyzing-inter-application-communication-in-android-ugwi6nj0xw.pdf

Analyzing inter-application communication in Android

https://research.ece.ncsu.edu/netwis/papers/13wl-comnet.pdf

Survey Cyber security in the Smart Grid: Survey and challenges

This survey provides a structured and comprehensive overview of research on security and privacy in computer and communication networks that use game-theoretic approaches. We present a selected set of works to highlight the application of game theory in addressing different forms of security and privacy problems in computer networks and mobile applications. We organize the presented works in six main categories: security of the physical and MAC layers, security of self-organizing networks, intrusion detection systems, anonymity and privacy, economics of network security, and cryptography. In each category, we identify security problems, players, and game models. We summarize the main results of selected works, such as equilibrium analysis and security mechanism designs. In addition, we provide a discussion on the advantages, drawbacks, and future direction of using game theory in this field. In this survey, our goal is to instill in the reader an enhanced understanding of different research approaches in applying game-theoretic methods to network security. This survey can also help researchers from various fields develop game-theoretic solutions to current and emerging security problems in computer networking.

/pdf/game-theory-meets-network-security-and-privacy-1r8g3nc948.pdf

Game theory meets network security and privacy

Measurement of software security is a long-standing challenge to the research community. At the same time, practical security metrics and measurements are essential for secure software development. Hence, the need for metrics is more pressing now due to a growing demand for secure software. In this paper, we propose using a software system's attack surface measurement as an indicator of the system's security. We formalize the notion of a system's attack surface and introduce an attack surface metric to measure the attack surface in a systematic manner. Our measurement method is agnostic to a software system's implementation language and is applicable to systems of all sizes; we demonstrate our method by measuring the attack surfaces of small desktop applications and large enterprise systems implemented in C and Java. We conducted three exploratory empirical studies to validate our method. Software developers can mitigate their software's security risk by measuring and reducing their software's attack surfaces. Our attack surface reduction approach complements the software industry's traditional code quality improvement approach for security risk mitigation and is useful in multiple phases of the software development lifecycle. Our collaboration with SAP demonstrates the use of our metric in the software development process.

/pdf/an-attack-surface-metric-395l6r2ma5.pdf

An Attack Surface Metric

Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison

Attack graphs are important tools for analyzing security vulnerabilities in enterprise networks. Previous work on attack graphs has not provided an account of the scalability of the graph generating process, and there is often a lack of logical formalism in the representation of attack graphs, which results in the attack graph being difficult to use and understand by human beings. Pioneer work by Sheyner, et al. is the first attack-graph tool based on formal logical techniques, namely model-checking. However, when applied to moderate-sized networks, Sheyner's tool encountered a significant exponential explosion problem. This paper describes a new approach to represent and generate attack graphs. We propose logical attack graphs, which directly illustrate logical dependencies among attack goals and configuration information. A logical attack graph always has size polynomial to the network being analyzed. Our attack graph generation tool builds upon MulVAL, a network security analyzer based on logical programming. We demonstrate how to produce a derivation trace in the MulVAL logic-programming engine, and how to use the trace to generate a logical attack graph in quadratic time. We show experimental evidence that our logical attack graph generation algorithm is very efficient. We have generated logical attack graphs for fully connected networks of 1000 machines using a Pentium 4 CPU with 1GB of RAM.

https://people.cis.ksu.edu/~xou/publications/ccs06.pdf

A scalable approach to attack graph generation

Real power injections at loads and generators, and real power flows on selected lines in a transmission network are monitored and transmitted over a SCADA network to the system operator. These are used in state estimation algorithms to make dispatch, re-balance and other energy management system [EMS] decisions. Coordinated cyber attacks on power meter readings can be designed to be undetectable by any bad data detection algorithm. These unobservable attacks present a serious threat to grid operations. Of particular interest are sparse attacks that involve the compromise of a modest number of meter readings. An efficient algorithm to find all unobservable attacks [under standard DC load flow approximations] involving the compromise of exactly two power injection meters and an arbitrary number of power meters on lines is presented. This requires O(n2m) flops for a power system with n buses and m line meters. If all lines are metered, there exist canonical forms that characterize all 3, 4, and 5-sparse unobservable attacks. These can be quickly detected with O(n2) flops using standard graph algorithms. Known-secure phasor measurement units [PMUs] can be used as countermeasures against a given collection of cyber attacks. Finding the minimum number of necessary PMUs is NP-hard. It is shown that p+1 PMUs at carefully chosen buses are sufficient to neutralize a collection of p cyber attacks.

/pdf/smart-grid-data-integrity-attacks-1atgepsse3.pdf

Smart Grid Data Integrity Attacks

Since digital control systems were introduced to the market more than 30 years ago, the operational efficiency and stability gained through their use have fueled our migration and ultimate dependence on them for the monitoring and control of critical infrastructure. While these systems have been designed for functionality and reliability, a hostile cyber environment and uncertainties in complex networks and human interactions have placed additional parameters on the design expectations for control systems.

/pdf/resilient-control-systems-next-generation-design-research-43oz294p5b.pdf

Resilient control systems: Next generation design research

Coordinated cyberattacks of power meter readings can be arranged to be undetectable by any bad data detection algorithm in the power system state estimation process These unobservable attacks present a potentially serious threat to grid operations Of particular interest are sparse attacks that involve the compromise of a modest number of meter readings An efficient algorithm to find all unobservable attacks [under standard DC load flow approximations] involving the compromise of exactly two power injection meters and an arbitrary number of line power meters is presented This requires O(n2m) flops for a power system with n buses and m line meters If all lines are metered, there exist canonical forms that characterize all 3, 4, and 5-sparse unobservable attacks These can be quickly detected in power systems using standard graph algorithms Known-secure phasor measurement units [PMUs] can be used as countermeasures against an arbitrary collection of cyberattacks Finding the minimum number of necessary PMUs is NP-hard It is shown that p + 1 PMUs at carefully chosen buses are sufficient to neutralize a collection of p cyberattacks

https://digital.library.unt.edu/ark:/67531/metadc829721/m2/1/high_res_d/1035890.pdf

Smart grid data integrity attacks: characterizations and countermeasures π

We propose a new model for estimating the time to compromise a system component that is visible to an attacker. The model provides an estimate of the expected value of the time-to-compromise as a function of known and visible vulnerabilities, and attacker skill level. The time-to-compromise random process model is a composite of three subprocesses associated with attacker actions aimed at the exploitation of vulnerabilities. In a case study, the model was used to aid in a risk reduction estimate between a baseline Supervisory Control and Data Acquisition (SCADA) system and the baseline system enhanced through a specific set of control system security remedial actions. For our case study, the total number of system vulnerabilities was reduced by 86% but the dominant attack path was through a component where the number of vulnerabilities was reduced by only 42% and the time-to-compromise of that component was increased by only 13% to 30% depending on attacker skill level.

/pdf/time-to-compromise-model-for-cyber-risk-reduction-estimation-22byn44a99.pdf

Miles McQueen

Papers

A scalable approach to attack graph generation

Smart Grid Data Integrity Attacks

Resilient control systems: Next generation design research

Smart grid data integrity attacks: characterizations and countermeasures π

Time-to-Compromise Model for Cyber Risk Reduction Estimation