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Elfar, Mahmoud, Zhu, Haibei, Cummings, M. L., Pajic, Miroslav.  2019.  Security-Aware Synthesis of Human-UAV Protocols. 2019 International Conference on Robotics and Automation (ICRA). :8011–8017.
In this work, we synthesize collaboration protocols for human-unmanned aerial vehicle (H-UAV) command and control systems, where the human operator aids in securing the UAV by intermittently performing geolocation tasks to confirm its reported location. We first present a stochastic game-based model for the system that accounts for both the operator and an adversary capable of launching stealthy false-data injection attacks, causing the UAV to deviate from its path. We also describe a synthesis challenge due to the UAV's hidden-information constraint. Next, we perform human experiments using a developed RESCHU-SA testbed to recognize the geolocation strategies that operators adopt. Furthermore, we deploy machine learning techniques on the collected experimental data to predict the correctness of a geolocation task at a given location based on its geographical features. By representing the model as a delayed-action game and formalizing the system objectives, we utilize off-the-shelf model checkers to synthesize protocols for the human-UAV coalition that satisfy these objectives. Finally, we demonstrate the usefulness of the H-UAV protocol synthesis through a case study where the protocols are experimentally analyzed and further evaluated by human operators.
Ibarra, Jaime, Javed Butt, Usman, Do, Anh, Jahankhani, Hamid, Jamal, Arshad.  2019.  Ransomware Impact to SCADA Systems and its Scope to Critical Infrastructure. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). :1–12.
SCADA systems are being constantly migrated to modern information and communication technologies (ICT) -based systems named cyber-physical systems. Unfortunately, this allows attackers to execute exploitation techniques into these architectures. In addition, ransomware insertion is nowadays the most popular attacking vector because it denies the availability of critical files and systems until attackers receive the demanded ransom. In this paper, it is analysed the risk impact of ransomware insertion into SCADA systems and it is suggested countermeasures addressed to the protection of SCADA systems and its components to reduce the impact of ransomware insertion.
Wright, James G., Wolthusen, Stephen D..  2018.  Stealthy Injection Attacks Against IEC61850's GOOSE Messaging Service. 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe). :1–6.
IEC61850 and IEC62351 combined provide a set of security promises for the communications channels that are used to run a substation automation system (SAS), that use IEC61850 based technologies. However, one area that is largely untouched by these security promises is the generic object oriented substation events (GOOSE) messaging service. GOOSE is designed to multicast commands and data across a substation within hard real time quality of service (QoS) requirements. This means that GOOSE is unable to implement the required security technologies as the added latency to any message would violate the QoS.
Wang, Dinghua, Feng, Dongqin.  2018.  Intrusion Detection Model of SCADA Using Graphical Features. 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :1208–1214.
Supervisory control and data acquisition system is an important part of the country's critical infrastructure, but its inherent network characteristics are vulnerable to attack by intruders. The vulnerability of supervisory control and data acquisition system was analyzed, combining common attacks such as information scanning, response injection, command injection and denial of service in industrial control systems, and proposed an intrusion detection model based on graphical features. The time series of message transmission were visualized, extracting the vertex coordinates and various graphic area features to constitute a new data set, and obtained classification model of intrusion detection through training. An intrusion detection experiment environment was built using tools such as MATLAB and power protocol testers. IEC 60870-5-104 protocol which is widely used in power systems had been taken as an example. The results of tests have good effectiveness.
Tseng, Yuchia, Nait-Abdesselam, Farid, Khokhar, Ashfaq.  2018.  SENAD: Securing Network Application Deployment in Software Defined Networks. 2018 IEEE International Conference on Communications (ICC). :1–6.
The Software Defined Networks (SDN) paradigm, often referred to as a radical new idea in networking, promises to dramatically simplify network management by enabling innovation through network programmability. However, notable security issues, such as app-to-control threats, remain a significant concern that impedes SDN from being widely adopted. To cope with those app-to-control threats, this paper proposes a solution to securely deploy valid network applications while protecting the SDN controller against the injection of the malicious application. This problem is mitigated by proposing a novel SDN architecture, dubbed SENAD, which splits the well-known SDN controller into: (1) a data plane controller (DPC), and (2) an application plane controller (APC), to secure this latter by design. The role of the DPC is dedicated for interpreting the network rules into OpenFlow entries and maintaining the communication with the data plane. The role of the APC, however, is to provide a secured runtime for deploying the network applications, including authentication, access control, resource isolation, control, and monitoring applications. We show that this approach can easily shield against any deny of service, caused for instance by the resource exhaustion attack or the malicious command injection, that is caused by the co-existence of a malicious application on the controller's runtime. The evaluation of our architecture shows that the packet\_in messages take less than 5 ms to be delivered from the data plane to the application plane on the long range.
Khan, Rafiullah, McLaughlin, Kieran, Laverty, John Hastings David, David, Hastings, Sezer, Sakir.  2018.  Demonstrating Cyber-Physical Attacks and Defense for Synchrophasor Technology in Smart Grid. 2018 16th Annual Conference on Privacy, Security and Trust (PST). :1–10.
Synchrophasor technology is used for real-time control and monitoring in smart grid. Previous works in literature identified critical vulnerabilities in IEEE C37.118.2 synchrophasor communication standard. To protect synchrophasor-based systems, stealthy cyber-attacks and effective defense mechanisms still need to be investigated.This paper investigates how an attacker can develop a custom tool to execute stealthy man-in-the-middle attacks against synchrophasor devices. In particular, four different types of attack capabilities have been demonstrated in a real synchrophasor-based synchronous islanding testbed in laboratory: (i) command injection attack, (ii) packet drop attack, (iii) replay attack and (iv) stealthy data manipulation attack. With deep technical understanding of the attack capabilities and potential physical impacts, this paper also develops and tests a distributed Intrusion Detection System (IDS) following NIST recommendations. The functionalities of the proposed IDS have been validated in the testbed for detecting aforementioned cyber-attacks. The paper identified that a distributed IDS with decentralized decision making capability and the ability to learn system behavior could effectively detect stealthy malicious activities and improve synchrophasor network security.
Takahashi, Akira, Tibouchi, Mehdi.  2019.  Degenerate Fault Attacks on Elliptic Curve Parameters in OpenSSL. 2019 IEEE European Symposium on Security and Privacy (EuroS P). :371–386.
In this paper, we describe several practically exploitable fault attacks against OpenSSL's implementation of elliptic curve cryptography, related to the singular curve point decompression attacks of Blömer and Günther (FDTC2015) and the degenerate curve attacks of Neves and Tibouchi (PKC 2016). In particular, we show that OpenSSL allows to construct EC key files containing explicit curve parameters with a compressed base point. A simple single fault injection upon loading such a file yields a full key recovery attack when the key file is used for signing with ECDSA, and a complete recovery of the plaintext when the file is used for encryption using an algorithm like ECIES. The attack is especially devastating against curves with j-invariant equal to 0 such as the Bitcoin curve secp256k1, for which key recovery reduces to a single division in the base field. Additionally, we apply the present fault attack technique to OpenSSL's implementation of ECDH, by combining it with Neves and Tibouchi's degenerate curve attack. This version of the attack applies to usual named curve parameters with nonzero j-invariant, such as P192 and P256. Although it is typically more computationally expensive than the one against signatures and encryption, and requires multiple faulty outputs from the server, it can recover the entire static secret key of the server even in the presence of point validation. These various attacks can be mounted with only a single instruction skipping fault, and therefore can be easily injected using low-cost voltage glitches on embedded devices. We validated them in practice using concrete fault injection experiments on a Rapsberry Pi single board computer running the up to date OpenSSL command line tools-a setting where the threat of fault attacks is quite significant.
Chi, Po-Wen, Wang, Ming-Hung.  2018.  A Lightweight Compound Defense Framework Against Injection Attacks in IIoT. 2018 IEEE Conference on Dependable and Secure Computing (DSC). :1–8.
Industrial Internet of Things (IIoT) is a trend of the smart industry. By collecting field data from sensors, the industry can make decisions dynamically in time for better performance. In most cases, IIoT is built on private networks and cannot be reached from the Internet. Currently, data transmission in most of IIoT network protocols is in plaintext without encryption protection. Once an attacker breaks into the field, the attacker can intercept data and injects malicious commands to field agents. In this paper, we propose a compound approach for defending command injection attacks in IIOT. First, we leverage the power of Software Defined Networking (SDN) to detect the injection attack. When the injection attack event is detected, the system owner is alarmed that someone tries to pretend a controller or a field agent to deceive the other entity. Second, we develop a lightweight authentication scheme to ensure the identity of the command sender. Command receiver can verify commands first before processing commands.
Blue, Logan, Abdullah, Hadi, Vargas, Luis, Traynor, Patrick.  2018.  2MA: Verifying Voice Commands via Two Microphone Authentication. Proceedings of the 2018 on Asia Conference on Computer and Communications Security. :89–100.
Voice controlled interfaces have vastly improved the usability of many devices (e.g., headless IoT systems). Unfortunately, the lack of authentication for these interfaces has also introduced command injection vulnerabilities - whether via compromised IoT devices, television ads or simply malicious nearby neighbors, causing such devices to perform unauthenticated sensitive commands is relatively easy. We address these weaknesses with Two Microphone Authentication (2MA), which takes advantage of the presence of multiple ambient and personal devices operating in the same area. We develop an embodiment of 2MA that combines approximate localization through Direction of Arrival (DOA) techniques with Robust Audio Hashes (RSHs). Our results show that our 2MA system can localize a source to within a narrow physical cone (\$\textbackslashtextless30ˆ\textbackslashtextbackslashcirc \$) with zero false positives, eliminate replay attacks and prevent the injection of inaudible/hidden commands. As such, we dramatically increase the difficulty for an adversary to carry out such attacks and demonstrate that 2MA is an effective means of authenticating and localizing voice commands.
Baykara, M., Güçlü, S..  2018.  Applications for detecting XSS attacks on different web platforms. 2018 6th International Symposium on Digital Forensic and Security (ISDFS). :1–6.

Today, maintaining the security of the web application is of great importance. Sites Intermediate Script (XSS) is a security flaw that can affect web applications. This error allows an attacker to add their own malicious code to HTML pages that are displayed to the user. Upon execution of the malicious code, the behavior of the system or website can be completely changed. The XSS security vulnerability is used by attackers to steal the resources of a web browser such as cookies, identity information, etc. by adding malicious Java Script code to the victim's web applications. Attackers can use this feature to force a malicious code worker into a Web browser of a user, since Web browsers support the execution of embedded commands on web pages to enable dynamic web pages. This work has been proposed as a technique to detect and prevent manipulation that may occur in web sites, and thus to prevent the attack of Site Intermediate Script (XSS) attacks. Ayrica has developed four different languages that detect XSS explanations with Asp.NET, PHP, PHP and Ruby languages, and the differences in the detection of XSS attacks in environments provided by different programming languages.

Valente, Junia, Cardenas, Alvaro A..  2017.  Security & Privacy in Smart Toys. Proceedings of the 2017 Workshop on Internet of Things Security and Privacy. :19–24.

We analyze the security practices of three smart toys that communicate with children through voice commands. We show the general communication architecture, and some general security and privacy practices by each of the devices. Then we focus on the analysis of one particular toy, and show how attackers can decrypt communications to and from a target device, and perhaps more worryingly, the attackers can also inject audio into the toy so the children listens to any arbitrary audio file the attacker sends to the toy. This last attack raises new safety concerns that manufacturers of smart toys should prevent.

Zhang, Guoming, Yan, Chen, Ji, Xiaoyu, Zhang, Tianchen, Zhang, Taimin, Xu, Wenyuan.  2017.  DolphinAttack: Inaudible Voice Commands. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :103–117.

Speech recognition (SR) systems such as Siri or Google Now have become an increasingly popular human-computer interaction method, and have turned various systems into voice controllable systems (VCS). Prior work on attacking VCS shows that the hidden voice commands that are incomprehensible to people can control the systems. Hidden voice commands, though "hidden", are nonetheless audible. In this work, we design a totally inaudible attack, DolphinAttack, that modulates voice commands on ultrasonic carriers (e.g., f textgreater 20 kHz) to achieve inaudibility. By leveraging the nonlinearity of the microphone circuits, the modulated low-frequency audio commands can be successfully demodulated, recovered, and more importantly interpreted by the speech recognition systems. We validated DolphinAttack on popular speech recognition systems, including Siri, Google Now, Samsung S Voice, Huawei HiVoice, Cortana and Alexa. By injecting a sequence of inaudible voice commands, we show a few proof-of-concept attacks, which include activating Siri to initiate a FaceTime call on iPhone, activating Google Now to switch the phone to the airplane mode, and even manipulating the navigation system in an Audi automobile. We propose hardware and software defense solutions, and suggest to re-design voice controllable systems to be resilient to inaudible voice command attacks.

Moore, Michael R., Bridges, Robert A., Combs, Frank L., Starr, Michael S., Prowell, Stacy J..  2017.  Modeling Inter-Signal Arrival Times for Accurate Detection of CAN Bus Signal Injection Attacks: A Data-Driven Approach to In-Vehicle Intrusion Detection. Proceedings of the 12th Annual Conference on Cyber and Information Security Research. :11:1–11:4.

Modern vehicles rely on hundreds of on-board electronic control units (ECUs) communicating over in-vehicle networks. As external interfaces to the car control networks (such as the on-board diagnostic (OBD) port, auxiliary media ports, etc.) become common, and vehicle-to-vehicle / vehicle-to-infrastructure technology is in the near future, the attack surface for vehicles grows, exposing control networks to potentially life-critical attacks. This paper addresses the need for securing the controller area network (CAN) bus by detecting anomalous traffic patterns via unusual refresh rates of certain commands. While previous works have identified signal frequency as an important feature for CAN bus intrusion detection, this paper provides the first such algorithm with experiments using three attacks in five (total) scenarios. Our data-driven anomaly detection algorithm requires only five seconds of training time (on normal data) and achieves true positive / false discovery rates of 0.9998/0.00298, respectively (micro-averaged across the five experimental tests).

Song, Liwei, Mittal, Prateek.  2017.  POSTER: Inaudible Voice Commands. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2583–2585.

Voice assistants like Siri enable us to control IoT devices conveniently with voice commands, however, they also provide new attack opportunities for adversaries. Previous papers attack voice assistants with obfuscated voice commands by leveraging the gap between speech recognition system and human voice perception. The limitation is that these obfuscated commands are audible and thus conspicuous to device owners. In this poster, we propose a novel mechanism to directly attack the microphone used for sensing voice data with inaudible voice commands. We show that the adversary can exploit the microphone's non-linearity and play well-designed inaudible ultrasounds to cause the microphone to record normal voice commands, and thus control the victim device inconspicuously. We demonstrate via end-to-end real-world experiments that our inaudible voice commands can attack an Android phone and an Amazon Echo device with high success rates at a range of 2-3 meters.

Xiao, Zeli, Zhou, Zhiguo, Yang, Wenwei, Deng, Chunyan.  2017.  An Approach for SQL Injection Detection Based on Behavior and Response Analysis - IEEE Conference Publication.

Nowadays the Internet is closely related to our daily life. We enjoy the quality of service the provided by The Internet at the same time, but also suffer from the threat of network security. Among the many threats, SQL injection attacks are ranked in the first place. SQL injection attack refers to “when the user sends a request to the server, the malicious SQL command will be inserted into the web form or request URL parameters, leading to the server to perform illegal SQL query. The existing SQL injection detection methods include static analysis, dynamic analysis, parameterized query, intrusion detection system, parameter filtering and so on. However, these methods have some defects. Static analysis method can only detect the type and grammatical errors of SQL. Dynamic analysis can only detect the vulnerability predefined by application developers. Parameter filtering is based on regular expressions and black list to filter invalid characters. This method needs predefined regular expressions, but due to the diversity of SQL syntax and user input, resulting in a regular expression can't meet the requirements of detection, and has the defects that the attackers bypass detection to inject by the way of encoding parameters. In this paper, we propose a new approach to detect and prevent SQL injection. Our approach is based on the attack behavior and the analysis of response and state of the web application under different attacks. Our method perfectly solves the problems existing in methods mentioned above, and has higher accuracy.

Bezemskij, A., Loukas, G., Gan, D., Anthony, R. J..  2017.  Detecting Cyber-Physical Threats in an Autonomous Robotic Vehicle Using Bayesian Networks. 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). :98–103.

Robotic vehicles and especially autonomous robotic vehicles can be attractive targets for attacks that cross the cyber-physical divide, that is cyber attacks or sensory channel attacks affecting the ability to navigate or complete a mission. Detection of such threats is typically limited to knowledge-based and vehicle-specific methods, which are applicable to only specific known attacks, or methods that require computation power that is prohibitive for resource-constrained vehicles. Here, we present a method based on Bayesian Networks that can not only tell whether an autonomous vehicle is under attack, but also whether the attack has originated from the cyber or the physical domain. We demonstrate the feasibility of the approach on an autonomous robotic vehicle built in accordance with the Generic Vehicle Architecture specification and equipped with a variety of popular communication and sensing technologies. The results of experiments involving command injection, rogue node and magnetic interference attacks show that the approach is promising.

Tung, Yu-Chih, Shin, Kang G., Kim, Kyu-Han.  2016.  Analog Man-in-the-middle Attack Against Link-based Packet Source Identification. Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing. :331–340.

A novel attack model is proposed against the existing wireless link-based source identification, which classifies packet sources according to the physical-layer link signatures. A link signature is believed to be a more reliable indicator than an IP or MAC address for identifying packet source, as it is generally harder to modify/forge. It is therefore expected to be a future authentication against impersonation and DoS attacks. However, if an attacker is equipped with the same capability/hardware as the authenticator to process physical-layer signals, a link signature can be easily manipulated by any nearby wireless device during the training phase. Based on this finding, we propose an attack model, called the analog man-in-the-middle (AMITM) attack, which utilizes the latest full-duplex relay technology to inject semi-controlled link signatures into authorized packets and reproduce the injected signature in the fabricated packets. Our experimental evaluation shows that with a proper parameter setting, 90% of fabricated packets are classified as those sent from an authorized transmitter. A countermeasure against this new attack is also proposed for the authenticator to inject link-signature noise by the same attack methodology.

Qiu, Pengfei, Lyu, Yongqiang, Zhang, Jiliang, Wang, Xingwei, Zhai, Di, Wang, Dongsheng, Qu, Gang.  2016.  Physical Unclonable Functions-based Linear Encryption Against Code Reuse Attacks. Proceedings of the 53rd Annual Design Automation Conference. :75:1–75:6.

Recently, code reuse attacks (CRAs) have emerged as a new class of ingenious security threatens. Attackers can utilize CRAs to hijack the control flow of programs to perform malicious actions without injecting any codes. Existing defenses against CRAs often incur high memory and performance overheads or require extending the existing processors' instruction set architectures (ISAs). To tackle these issues, we propose a hardware-based control flow integrity (CFI) that employs physical unclonable functions (PUF)-based linear encryption architecture (LEA) to protect against CRAs with negligible hardware extending and run time overheads. The proposed method can protect ret and indirect jmp instructions from return oriented programming (ROP) and jump oriented programming (JOP) without any additional software manipulations and extending ISAs. The pre-process will be conducted on codes once the executable binary is loaded into memory, and the real-time control flow verification based on LEA can be done while ret and jmp instructions are executed. Performance evaluations on benchmarks show that the proposed method only introduces 0.61% run-time overhead and 0.63% memory overhead on average.

He, Wei, Breier, Jakub, Bhasin, Shivam, Chattopadhyay, Anupam.  2016.  Bypassing Parity Protected Cryptography Using Laser Fault Injection in Cyber-Physical System. Proceedings of the 2Nd ACM International Workshop on Cyber-Physical System Security. :15–21.

Lightweight cryptography has been widely utilized in resource constrained embedded devices of Cyber-Physical System (CPS) terminals. The hostile and unattended environment in many scenarios make those endpoints easy to be attacked by hardware based techniques. As a resource-efficient countermeasure against Fault Attacks, parity Concurrent Error Detection (CED) is preferably integrated with security-critical algorithm in CPS terminals. The parity bit changes if an odd number of faults occur during the cipher execution. In this paper, we analyze the effectiveness of fault detection of a parity CED protected cipher (PRESENT) using laser fault injection. The experimental results show that the laser perturbation to encryption can easily flip an even number of data bits, where the faults cannot be detected by parity. Due to the similarity of different parity structures, our attack can bypass almost all parity protections in block ciphers. Some suggestions are given to enhance the security of parity implementations.

Gruss, Daniel, Maurice, Clémentine, Fogh, Anders, Lipp, Moritz, Mangard, Stefan.  2016.  Prefetch Side-Channel Attacks: Bypassing SMAP and Kernel ASLR. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :368–379.

Modern operating systems use hardware support to protect against control-flow hijacking attacks such as code-injection attacks. Typically, write access to executable pages is prevented and kernel mode execution is restricted to kernel code pages only. However, current CPUs provide no protection against code-reuse attacks like ROP. ASLR is used to prevent these attacks by making all addresses unpredictable for an attacker. Hence, the kernel security relies fundamentally on preventing access to address information. We introduce Prefetch Side-Channel Attacks, a new class of generic attacks exploiting major weaknesses in prefetch instructions. This allows unprivileged attackers to obtain address information and thus compromise the entire system by defeating SMAP, SMEP, and kernel ASLR. Prefetch can fetch inaccessible privileged memory into various caches on Intel x86. It also leaks the translation-level for virtual addresses on both Intel x86 and ARMv8-A. We build three attacks exploiting these properties. Our first attack retrieves an exact image of the full paging hierarchy of a process, defeating both user space and kernel space ASLR. Our second attack resolves virtual to physical addresses to bypass SMAP on 64-bit Linux systems, enabling ret2dir attacks. We demonstrate this from unprivileged user programs on Linux and inside Amazon EC2 virtual machines. Finally, we demonstrate how to defeat kernel ASLR on Windows 10, enabling ROP attacks on kernel and driver binary code. We propose a new form of strong kernel isolation to protect commodity systems incuring an overhead of only 0.06-5.09%.

LeBlanc, Heath J., Hassan, Firas, Gomez, Edgar, Alsbou, Nesreen.  2016.  Inter-vehicle Communication Assisted Localization with Resilience to False Data Injection Attacks. Proceedings of the First ACM International Workshop on Smart, Autonomous, and Connected Vehicular Systems and Services. :64–65.

Vehicle localization is important in many applications of vehicular networks. The Global Positioning System (GPS) has been critical for vehicle localization. However, the case where the GPS is spoofed through a false data injection attack can be lead to devastating consequences, especially in localization solutions that make use of cooperation among multiple vehicles. Hence, resilient localization algorithms are needed that can achieve a baseline of performance in the case of a false data injection attack. This poster presents preliminary results of an inter-vehicle communication assisted localization algorithm that is resilient to false data injection attacks for the vehicles not directly attacked. The algorithm makes use of V2V and V2I communication – along with on-board GPS receiver, odometer, and compass – to achieve precise localization results.

Shahriar, Hossain, Haddad, Hisham.  2016.  Object Injection Vulnerability Discovery Based on Latent Semantic Indexing. Proceedings of the 31st Annual ACM Symposium on Applied Computing. :801–807.

Object Injection Vulnerability (OIV) is an emerging threat for web applications. It involves accepting external inputs during deserialization operation and use the inputs for sensitive operations such as file access, modification, and deletion. The challenge is the automation of the detection process. When the application size is large, it becomes hard to perform traditional approaches such as data flow analysis. Recent approaches fall short of narrowing down the list of source files to aid developers in discovering OIV and the flexibility to check for the presence of OIV through various known APIs. In this work, we address these limitations by exploring a concept borrowed from the information retrieval domain called Latent Semantic Indexing (LSI) to discover OIV. The approach analyzes application source code and builds an initial term document matrix which is then transformed systematically using singular value decomposition to reduce the search space. The approach identifies a small set of documents (source files) that are likely responsible for OIVs. We apply the LSI concept to three open source PHP applications that have been reported to contain OIVs. Our initial evaluation results suggest that the proposed LSI-based approach can identify OIVs and identify new vulnerabilities.

Amullen, Esther, Lin, Hui, Kalbarczyk, Zbigniew, Keel, Lee.  2016.  Multi-agent System for Detecting False Data Injection Attacks Against the Power Grid. Proceedings of the 2Nd Annual Industrial Control System Security Workshop. :38–44.

A class of cyber-attacks called False Data Injection attacks that target measurement data used for state estimation in the power grid are currently under study by the research community. These attacks modify sensor readings obtained from meters with the aim of misleading the control center into taking ill-advised response action. It has been shown that an attacker with knowledge of the network topology can craft an attack that bypasses existing bad data detection schemes (largely based on residual generation) employed in the power grid. We propose a multi-agent system for detecting false data injection attacks against state estimation. The multi-agent system is composed of software implemented agents created for each substation. The agents facilitate the exchange of information including measurement data and state variables among substations. We demonstrate that the information exchanged among substations, even untrusted, enables agents cooperatively detect disparities between local state variables at the substation and global state variables computed by the state estimator. We show that a false data injection attack that passes bad data detection for the entire system does not pass bad data detection for each agent.

Min, Byungho, Varadharajan, Vijay.  2016.  Cascading Attacks Against Smart Grid Using Control Command Disaggregation and Services. Proceedings of the 31st Annual ACM Symposium on Applied Computing. :2142–2147.

In this paper, we propose new types of cascading attacks against smart grid that use control command disaggregation and core smart grid services. Although there have been tremendous research efforts in injection attacks against the smart grid, to our knowledge most studies focus on false meter data injection, and false command and false feedback injection attacks have been scarcely investigated. In addition, control command disaggregation has not been addressed from a security point of view, in spite of the fact that it is becoming one of core concepts in the smart grid and hence analysing its security implications is crucial to the smart grid security. Our cascading attacks use false control command, false feedback or false meter data injection, and cascade the effects of such injections throughout the smart grid subsystems and components. Our analysis and evaluation results show that the proposed attacks can cause serious service disruptions in the smart grid. The evaluation has been performed on a widely used smart grid simulation platform.

Wang, Yinan, Zeng, Sicheng, Yang, Qiang, Lin, Zhiyun, Xu, Wenyuan, Yan, Gangfeng.  2016.  A new framework of electrical cyber physical systems. :1334–1339.

This paper establishes a new framework for electrical cyber-physical systems (ECPSs). The communication network is designed by the characteristics of a power grid. The interdependent relationship of communication networks and power grids is described by data-uploading channels and commands-downloading channels. Control strategies (such as load shedding and relay protection) are extended to this new framework for analyzing the performance of ECPSs under several attack scenarios. The fragility of ECPSs under cyber attacks (DoS attack and false data injection attack) and the effectiveness of relay protection policies are verified by experimental results.