Physics-Driven Page Fault Handling for Customized Deception against CPS Malware

The seL4 Microkernel – A Robust, Resilient, and Open-Source Foundation for Ground Vehicle Electronics Architecture

Chapter 4 - Paging Dynamics

Cyber-physical systems (CPS) are a collection of transformative technologies for managing interconnected physical and computational capabilities. Recent developments in technology are increasing the availability and affordability of sensors, data acquisition systems, and computer networks. The competitive nature of industry requires manufacturers to implement new methodologies. CPS is a broad area of engineering which supports applications across industries, such as manufacturing, healthcare, electric power grids, agriculture, and transportation. In particular, CPS is the core technology enabling the transition from Industry 3.0 to Industry 4.0 (I 4.0) and is transforming global advanced manufacturing. This paper provides a consolidated review of the latest CPS literature, a complete review of international standards, and a complete analysis of patent portfolios related to the 5C’s CPS architecture model by Lee et al. The critical evaluation of international standards and the intellectual property contained in CPS patents is unaddressed by the previous research and will benefit both academic scholars and industry practitioners. The analysis provides a basis for predicting research and development future trends and helps policy makers manage technology changes that will result from CPS in I 4.0. This paper covers the emerging I 4.0 standards from the International Organization for Standardization, the International Electrotechnical Commission, and China’s Guobiao standards followed by a patent analysis covering global patents issued in the U.S., Europe, China, and the World Intellectual Property Organization.

Demand prepaging was long ago proposed as a method for taking advantage of high disk bandwidths and avoiding long disk latencies by fetching, at each page fault, not only the demanded page but also other pages predicted to be used soon. Studies performed more than twenty years ago found that demand prepaging would not be generally beneficial. Those studies failed to examine thoroughly the interaction between prepaging and main memory caching. It is unclear how many main memory page frames should be allocated to cache pages that were prepaged but have not yet been referenced. This issue is critical to the efficacy of any demand prepaging policy.In this paper, we examine prepaged allocation and its interaction with two other important demand prepaging parameters: the degree, which is the number of extra pages that may be fetched at each page fault, and the predictor that selects which pages to prepage. The choices for these two parameters, the reference behavior of the workload, and the main memory size all substantially affect the appropriate choice of prepaged allocation. In some situations, demand prepaging cannot provide benefit, as any allocation to prepaged pages will increase page faults, while in other situations, a good choice of allocation will yield a substantial reduction in page faults. We will present a mechanism that dynamically adapts the prepaged allocation on-line, as well as experimental results that show that this mechanism typically reduces page faults by 10 to 40% and sometimes by more than 50%. In those cases where demand prepaging should not be used, the mechanism correctly allocates no space for prepaged pages and thus does not increase the number of page faults. Finally, we will show that prepaging offers substantial benefits over the simpler solution of sing larger pages, which can substantially increase page faults.

Demand prepaging was long ago proposed as a method for taking advantage of high disk bandwidths and avoiding long disk latencies by fetching, at each page fault, not only the demanded page but also other pages predicted to be used soon. Studies performed more than twenty years ago found that demand prepaging would not be generally beneficial. Those studies failed to examine thoroughly the interaction between prepaging and main memory caching. It is unclear how many main memory page frames should be allocated to cache pages that were prepaged but have not yet been referenced. This issue is critical to the efficacy of any demand prepaging policy.In this paper, we examine prepaged allocation and its interaction with two other important demand prepaging parameters: the degree, which is the number of extra pages that may be fetched at each page fault, and the predictor that selects which pages to prepage. The choices for these two parameters, the reference behavior of the workload, and the main memory size all substantially affect the appropriate choice of prepaged allocation. In some situations, demand prepaging cannot provide benefit, as any allocation to prepaged pages will increase page faults, while in other situations, a good choice of allocation will yield a substantial reduction in page faults. We will present a mechanism that dynamically adapts the prepaged allocation on-line, as well as experimental results that show that this mechanism typically reduces page faults by 10 to 40% and sometimes by more than 50%. In those cases where demand prepaging should not be used, the mechanism correctly allocates no space for prepaged pages and thus does not increase the number of page faults. Finally, we will show that prepaging offers substantial benefits over the simpler solution of sing larger pages, which can substantially increase page faults.

Malware that attack the electrical power grid consist of exploits and operations modules. The exploits are similar to those of traditional malware. These malware hack into an industrial computer and subsequently deploy operational modules. Some operational modules penetrate the operating system of the compromised industrial computer to take over computing functions and hence facilitate further attacks. Examples include interception of cryptographic keys, and generation of deceptive status data that indicate normal operation of a power transformer, while in reality the transformer is in distress due to the attacks. Other operational modules are designed to recognize and disrupt the physics of the physical equipment. We refer to these operations modules as physics-centric modules. The subject of this research is how physics-centric modules of malware can cause physical damage to power grid equipment. This research simulates a power transformer and a set of its protection algorithms. We make several contributions in this research, namely: i) we emulate in Python the protection algorithms that run on an industrial computer and monitor and protect a power transformer from a variety of faults; ii) we leverage these emulations to analyze the cyberattack surface of a power transformer; iii) with these insights at hand, we devise attack modus operandi that malware could use against a power transformer; and iv) we emulate these cyberattacks in Python to empirically observe and quantify their destructive effects on a power transformer. Our overall research findings in this paper serve the purpose of informing better defense against the physics-centric modules of malware that attack the electrical power grid.

A buffer based page replacement algorithm to reduce page fault

Article Evaluation of memory system extensions Share on Authors: Kai Li Department of Computer Science, Princeton University Department of Computer Science, Princeton UniversityView Profile , Karin Petersen Department of Computer Science, Princeton University Department of Computer Science, Princeton UniversityView Profile Authors Info & Claims ISCA '91: Proceedings of the 18th annual international symposium on Computer architectureApril 1991 Pages 84–93https://doi.org/10.1145/115952.115962Published:01 April 1991 10citation391DownloadsMetricsTotal Citations10Total Downloads391Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

In this paper we describe and evaluate two possible architectures using 3D DRAMs and PCMs in the processor memory hierarchy. We explore using (a) 3D DRAM as main memory with PCM as backing store and (b) 3D DRAM as the Last Level Cache and PCM as the main memory. In each of these configurations, since the proposed main memories are significantly faster than today's off-chip 2D DRAMs for main memory and either flash memory based SSDs or magnetic hard drives for secondary storage, we will introduce hardware assistance for virtual to physical address translation and to speed up page-fault handling. We use Simics, a full system simulator and benchmarks from both SPEC 2006 and OLTP suites to evaluate our designs. Our experiments measure energy consumed and execution performance; we use CACTI for obtaining energy and latency values for our memory configurations.

Cyber-physical systems are vulnerable to a variety of cyber, physical and cyber-physical attacks. The security of cyber-physical systems can be enhanced beyond what can be achieved through firewalls and trusted components by building trust from observed and/or expected behaviors. These behaviors can be encoded as invariants. Information flows that do not satisfy the invariants are used to identify and isolate malfunctioning devices and cyber intrusions. However, the distributed architectures of cyber-physical systems often contain multiple access points that are physically and/or digitally linked. Thus, invariants may be difficult to determine and/or computationally prohibitive to check in real time. Researchers have employed various methods for determining the invariants by analyzing the designs of and/or data generated by cyber-physical systems such as water treatment plants and electric power grids. This chapter compares the effectiveness of detecting attacks on a water treatment plant using design-centric invariants versus data-centric rules, the latter generated using a variety of data mining methods. The methods are compared based on the maximization of true positives and minimization of false positives.

The latest progress in industrial control systems is to implement information technology solutions to support such features as administrative control based on network-based information connectivity. This paper focuses on an electrical power grid as a sample of such systems. A fundamental understanding of grid information hierarchy is essential to meet new challenges due to increasing needs of grid efficiency, flexibility, and control, and greater security risks and reliability challenges for large cyber-physical systems. Methods used in visualizing and representing electrical grids are an important tool for achieving comprehension and facilitating control (e.g., UML use cases). The problem is that current high-level representation grids are a heterogeneous mix of diagrams (e.g., UML use cases) flowcharts, graphs, technical drawings, and maps that do not furnish a base on which to discuss the characteristics, uses, behavior, interfaces, requirements, and standards of the grid. This paper proposes a solution in the form of a conceptual diagrammatic specification of grid architecture and applies it to the electric grid in the state of Kuwait. The approach is the skeleton of a method based on generic stages that make up any process and embraces input, processing, creation, and output. It provides a base that can be supplemented with extra notions from various current diagrammatic methods. The results indicate the viability of the proposed method as a foundation for zooming in and out on specifications of the grid in a uniform way.

A cyber-physical system (CPS) integrates a physical infrastructure with cyber computation for improved performance and reliability. The US National Science Foundation established a CPS funding program [1] in the mid-2000s and the National Institute of Standards and Technology established a public working group in 2014 on defining a framework for CPS [10]. Application areas include water distribution, transportation, the electric power grid, chemical process plants, manufacturing, aviation, and medical devices. While control can be centralized, most CPSs are distributed systems in which several cyber processes cooperate to control a set of physical resources. An individual process does not have the complete system state, and must communicate over some network to share information with its peers. It is vital that processes share accurate state information to ensure that the distributed system makes the correct control decisions. Failure in a CPS can result in physical consequences such as damage to the machines or harm to the humans involved in the system operation.

Cyber-Physical Systems (CPS) are integrated systems that combine software and physical components. CPS has experienced rapid growth over the past decade in fields as disparate as telemedicine, smart manufacturing, autonomous vehicles, the Internet of Things, industrial control systems, smart power grids, remote laboratory environments, and many more. With the widespread integration of Cyber-Physical Systems (CPS) in various aspects of contemporary society, the frequency of malicious assaults carried out by adversaries has experienced a substantial surge in recent times. Incidents targeting vital civilian infrastructure, such as electrical power grids and oil pipelines, have become alarmingly common due to the expanded connectivity to the public internet, which significantly expands the vulnerability of CPS. This article presents a comprehensive review of existing literature that examines the latest advancements in anomaly detection techniques for identifying security threats in Cyber-Physical Systems. The primary emphasis is placed on addressing life safety concerns within industrial control networks (ICS). A total of 296 papers are reviewed, with common themes and research gaps identified. This paper makes a novel contribution by identifying the key challenges that remain in the field, which include resource constraints, a lack of standardized communication protocols, extreme heterogeneity that hampers industry consensus, and different information security priorities between Operational Technology (OT) and Information Technology (IT) networks. Potential solutions and/or opportunities for further research are identified to address these selected challenges.

Cyber-Physical Systems (CPS) are integrations of computation and physical processes. This kind of systems is being increasingly used in different domains such as healthcare, transportation, process control, manufacturing or electric power grids. CPS interact with the physical world and must operate dependably, safely, securely, efficiently and, frequently, in real-time. Consequently, they require new computing and networking technologies capable of supporting them adequately in environments qualitatively different from those found in general purpose computing. This paper analyzes the applicability of different middleware technologies as data distribution means for CPS.

Faults Monitoring System in the Electric Power Grid of Medium Voltage