You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Survey of Physics-Based Attack Detection in Cyber-Physical Systems 
Chapter Title:  INTRODUCTION 
1. Abstract of Cited Paper (BIB001):  A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including interacting bad measurements introduced by arbitrary, nonrandom causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers. In this article, we expose an unknown vulnerability of existing bad measurement detection algorithms by presenting and analyzing a new class of attacks, called false data injection attacks, against state estimation in electric power grids. Under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations, such attacks can introduce arbitrary errors into certain state variables without being detected by existing algorithms. Moreover, we look at two scenarios, where the attacker is either constrained to specific meters or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios to change the results of state estimation in arbitrary ways. We also extend these attacks to generalized false data injection attacks, which can further increase the impact by exploiting measurement errors typically tolerated in state estimation. We demonstrate the success of these attacks through simulation using IEEE test systems, and also discuss the practicality of these attacks and the real-world constraints that limit their effectiveness. 
2. Abstract of Cited Paper (BIB002):  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. 
3. Abstract of Cited Paper (BIB003):  In recent years we have witnessed several complex and high-impact attacks specifically targeting "binary" protocols (RPC, Samba and, more recently, RDP). These attacks could not be detected by current --- signature-based --- detection solutions, while --- at least in theory --- they could be detected by state-of-the-art anomaly-based systems. This raises once again the still unanswered question of how effective anomaly-based systems are in practice. To contribute to answering this question, in this paper we investigate the effectiveness of a widely studied category of network intrusion detection systems: anomaly-based algorithms using n-gram analysis for payload inspection. Specifically, we present a thorough analysis and evaluation of several detection algorithms using variants of n-gram analysis on real-life environments. Our tests show that the analyzed systems, in presence of data with high variability, cannot deliver high detection and low false positive rates at the same time. 
4. Abstract of Cited Paper (BIB004):  This work describes a new type of efficiency attack that can be used to degrade the performance of automated vehicular transportation systems. Next-generation transportation technologies will leverage increasing use of vehicle automation. Proposed vehicular automation systems include cooperative adaptive cruise control and vehicle platooning strategies which require cooperation and coordination among vehicles. These strategies are intended to optimize through-put and energy usage in future highway systems, but, as we demonstrate, they also introduce new vulnerabilities. In this work we show that a typical platooning system would allow a maliciously controlled vehicle to exert subtle influence on the motion of surrounding vehicles. This effect can be used to increase the energy expenditure of surrounding vehicles by 20% to 300%. 
5. Abstract of Cited Paper (BIB005):  Smart grid deployment initiatives have been witnessed in the past recent years. Smart grids provide bi-directional communication between meters and headend system through Advanced Metering Infrastructure (AMI). Recent studies highlight the threats targeting AMI. Despite the need of tailored Intrusion Detection Systems (IDS) for the smart grid, very limited progress has been made in this area. Unlike traditional networks, smart grid has its own unique challenges, such as limited computational power devices and potentially high deployment cost, that restrict the deployment options of intrusion detectors. We show that smart grid exhibits deterministic and predictable behavior that can be accurately modeled to develop intrusion detection system. In this paper, we show that AMI behavior can be modeled using event logs collected at smart collectors, which in turn can be verified using the specifications invariant generated from the configurations of the AMI devices. Event logs are modeled using fourth order Markov Chain and specifications are written in Linear Temporal Logic (LTL). The approach provides robustness against evasion and mimicry attacks, however, we discuss that it still can be evaded to a certain extent. We validate our approach on a real-world dataset of thousands of meters collected at the AMI of a leading utility provider. 
6. Abstract of Cited Paper (BIB006):  Networked control systems used in energy, manufacturing, and transportation combine large, vulnerable attack surfaces with far overprovisioned privileges. Often, compromising a single computer or user account is sufficient to give an attacker free reign over physical machinery. Significant reduction of attack surface size is an ongoing problem, so we shift our focus to reducing the privileges granted to system operators and embedded controllers. To this end, we introduce C2, an enforcement mechanism for policies governing the usage of electromechanical devices. In presenting C2, we address two basic problems: (i.) How should a policy for physical device usage be expressed and enforced? This is a challenging question, as the safe usage of physical devices is dependent on mechanical limitations and the behavior of nearby devices. (ii.) What actions should be taken if a physical machine is issued an operation that violates the policy? C2 takes measures to ensure unsafe behaviors are not caused when denying slightly erroneous yet legitimate operations. We evaluate C2 against six representative control systems, and show that it can efficiently perform policy checks with less than 3.7% overhead, while not introducing new unsafe behaviors into a control system. 
7. Abstract of Cited Paper (BIB007):  Pervasive healthcare systems, smart grids, and unmanned aircraft systems are examples of Cyber-Physical Systems (CPSs) that have become highly integrated in the modern world. As this integration deepens, the importance of securing these systems increases. In order to identify gaps and propose research directions in CPS intrusion detection research, we survey the literature of this area. Our approach is to classify modern CPS Intrusion Detection System (IDS) techniques based on two design dimensions: detection technique and audit material. We summarize advantages and drawbacks of each dimension’s options. We also summarize the most and least studied CPS IDS techniques in the literature and provide insight on the effectiveness of IDS techniques as they apply to CPSs. Finally, we identify gaps in CPS IDS research and suggest future research areas. 
8. Abstract of Cited Paper (BIB008):  Off-the-shelf intrusion detection systems prove an ill fit for protecting industrial control systems, as they do not take their process semantics into account. Specifically, current systems fail to detect recent process control attacks that manifest as unauthorized changes to the configuration of a plant's programmable logic controllers (PLCs). In this work we present a detector that continuously tracks updates to corresponding process variables to then derive variable-specific prediction models as the basis for assessing future activity. Taking a specification-agnostic approach, we passively monitor plant activity by extracting variable updates from the devices' network communication. We evaluate the capabilities of our detection approach with traffic recorded at two operational water treatment plants serving a total of about one million people in two urban areas. We show that the proposed approach can detect direct attacks on process control, and we further explore its potential to identify more sophisticated indirect attacks on field device measurements as well. 
9. Abstract of Cited Paper (BIB009):  Advanced false data injection attack in targeted malware intrusion is becoming an emerging severe threat to the Supervisory Control And Data Acquisition SCADA system. Several intrusion detection schemes have been proposed previously [1, 2]. However, designing an effective real-time detection system for a resource-constraint device is still an open problem for the research community. In this paper, we propose a new relation-graph-based detection scheme to defeat false data injection attacks at the SCADA system, even when injected data may seemly fall within a valid/normal range. To balance effectiveness and efficiency, we design a novel detection model, alternation vectors with state relation graph. Furthermore, we propose a new inference algorithm to infer the injection points, i.e., the attack origin, in the system. We evaluate SRID with a real-world power plant simulator. The experiment results show that SRID can detect various false data injection attacks with a low false positive rate at 0.0125%. Meanwhile, SRID can dramatically reduce the search space of attack origins and accurately locate most of attack origins. 
10. Abstract of Cited Paper (BIB010):  Embedded sensing systems are pervasively used in life- and security-critical systems such as those found in airplanes, automobiles, and healthcare. Traditional security mechanisms for these sensors focus on data encryption and other post-processing techniques, but the sensors themselves often remain vulnerable to attacks in the physical/analog domain. If an adversary manipulates a physical/analog signal prior to digitization, no amount of digital security mechanisms after the fact can help. Fortunately, nature imposes fundamental constraints on how these analog signals can behave. This work presents PyCRA, a physical challenge-response authentication scheme designed to protect active sensing systems against physical attacks occurring in the analog domain. PyCRA provides secure active sensing by continually challenging the surrounding environment via random but deliberate physical probes. By analyzing the responses to these probes, the system is able to ensure that the underlying physics involved are not violated, providing an authentication mechanism that not only detects malicious attacks but provides resilience against them. We demonstrate the effectiveness of PyCRA in detecting and mitigating attacks through several case studies using two sensing systems: (1) magnetic sensors like those found on gear and wheel speed sensors in robotics and automotive, and (2) commercial Radio Frequency Identification (RFID) tags used in many security-critical applications. In doing so, we evaluate both the robustness and the limitations of the PyCRA security scheme, concluding by outlining practical considerations as well as further applications for the proposed authentication mechanism.

Literature Review:
One of the fundamentally unique properties of industrial control-when compared to general Information Technology (IT) systems-is that the physical evolution of the state of a system has to follow immutable laws of nature. For example, the physical properties of water systems (fluid dynamics) or the power grid (electromagnetics) can be used to create time-series models that we can false control signals like manipulating vehicle platoons BIB005 , manipulating demand-response systems  , and the sabotage Stuxnet [25,  created by manipulating the rotation frequency of centrifuges. The question we address is how to detect these false sensor or false control attacks. One of the first papers to consider intrusion detection in industrial control networks was Cheung et al.  . Their work articulated that network anomaly detection might be more effective in control networks where communication patterns are more regular and stable than in traditional IT networks. Similar work has been done in smart grid networks BIB006 BIB001 and in general CPS systems BIB008 ; however, as Hadvziosmanovic et al. showed BIB004 , intrusion detection systems that fail to incorporate domain-specific knowledge and the context in which they are operating will still perform poorly in practical scenarios. Even worse, an attacker that has obtained control of a sensor, an actuator, or a PLC can send manipulated sensor or control values to the physical process while complying to typical traffic patterns such as Internet Protocol (IP) addresses, protocol specifications with finite automata or Markov models, connection logs, and so on. In contrast to work in CPS intrusion detection that focuses on monitoring such low-level IT observations, in this article, we systematize the recent and growing literature in computer security conferences (e.g., CCS'15 BIB011 , CCS'09 BIB002 , ACSAC'13 BIB007 , ACSAC'14 BIB009 , ASIACCS'11 BIB003 , and ESORICS'14 BIB010 ) studying how monitoring sensor values from physical observations, and control signals sent to actuators, can be used to detect attacks. We also systematize similar results by other fields like control theory conferences with the goal of helping security practitioners understand recent results from control theory, and control theory practitioners understand research results from the security community. Our selection criteria for including a paper in the survey is to identify all the papers (that we are aware of) where the system monitors sensor and/or control signals, and then raises an alert whenever these observations deviate from a model of the physical system.