Biblio
The design of attacks for cyber physical systems is critical to assess CPS resilience at design time and run-time, and to generate rich datasets from testbeds for research. Attacks against cyber physical systems distinguish themselves from IT attacks in that the main objective is to harm the physical system. Therefore, both cyber and physical system knowledge are needed to design such attacks. The current practice to generate attacks either focuses on the cyber part of the system using IT cyber security existing body of knowledge, or uses heuristics to inject attacks that could potentially harm the physical process. In this paper, we present a systematic approach to automatically generate integrity attacks from the CPS safety and control specifications, without knowledge of the physical system or its dynamics. The generated attacks violate the system operational and safety requirements, hence present a genuine test for system resilience. We present an algorithm to automate the malware payload development. Several examples are given throughout the paper to illustrate the proposed approach.
This work describes a top down systems security requirements analysis approach for understanding and eliciting security requirements for a notional small unmanned aerial system (SUAS). More specifically, the System-Theoretic Process Analysis approach for Security (STPA-Sec) is used to understand and elicit systems security requirements. The effort employs STPA-Sec on a notional SUAS system case study to detail the development of functional-level security requirements, design-level engineering considerations, and architectural-level security specification criteria early in the system life cycle when the solution trade-space is largest rather than merely examining components and adding protections during system operation or sustainment. These details were elaborated during a semester independent study research effort by two United States Air Force Academy Systems Engineering cadets, guided by their instructor and a series of working group sessions with UAS operators and subject matter experts. This work provides insight into a viable systems security requirements analysis approach which results in traceable security, safety, and resiliency requirements that can be designed-for, built-to, and verified with confidence.
With the latest development of hydroelectric power generation system, the industrial control network system of hydroelectric power generation has undergone the transformation from the dedicated network, using proprietary protocols to an increasingly open network, adopting standard protocols, and increasing integration with hydroelectric power generation system. It generally believed that with the improvement of the smart grid, the future hydroelectric power generation system will rely more on the powerful network system. The general application of standardized communication protocol and intelligent electronic equipment in industrial control network provides a technical guarantee for realizing the intellectualization of hydroelectric power generation system but also brings about the network security problems that cannot be ignored. In order to solve the vulnerability of the system, we analyze and quantitatively evaluate the industrial control network of hydropower generation as a whole, and propose a set of attack and defense strategies. The method of vulnerability assessment with high diversity score proposed by us avoids the indifference of different vulnerability score to the greatest extent. At the same time, we propose an optimal attack and defense decision algorithm, which generates the optimal attack and defense strategy. The work of this paper can distinguish the actual hazards of vulnerable points more effectively.
Currently, security protection in Industrial Control Systems has become a hot topic, and a great number of defense techniques have sprung up. As one of the most effective approaches, area isolation has the exceptional advantages and is widely used to prevent attacks or hazards propagating. However, most existing methods for inter-area communication protection present some limitations, i.e., excessively depending on the analyzing rules, affecting original communication. Additionally, the network architecture and data flow direction can hardly be adjusted after being deployed. To address these problems, a dynamical and customized communication protection technology is proposed in this paper. In detail, a security inter-area communication architecture based on Software Defined Network is designed firstly, where devices or subsystems can be dynamically added into or removed from the communication link. And then, a security inspection method based on information entropy is presented for deep network behaviors analysis. According to the security analysis results, the communications in the network can be adjusted in time. Finally, simulations are constructed, and the results indicate that the proposed approach is sensitive and effective for cyber-attacks detection.
The world is witnessing a remarkable increase in the usage of video surveillance systems. Besides fulfilling an imperative security and safety purpose, it also contributes towards operations monitoring, hazard detection and facility management in industry/smart factory settings. Most existing surveillance techniques use hand-crafted features analyzed using standard machine learning pipelines for action recognition and event detection. A key shortcoming of such techniques is the inability to learn from unlabeled video streams. The entire video stream is unlabeled when the requirement is to detect irregular, unforeseen and abnormal behaviors, anomalies. Recent developments in intelligent high-level video analysis have been successful in identifying individual elements in a video frame. However, the detection of anomalies in an entire video feed requires incremental and unsupervised machine learning. This paper presents a novel approach that incorporates high-level video analysis outcomes with incremental knowledge acquisition and self-learning for autonomous video surveillance. The proposed approach is capable of detecting changes that occur over time and separating irregularities from re-occurrences, without the prerequisite of a labeled dataset. We demonstrate the proposed approach using a benchmark video dataset and the results confirm its validity and usability for autonomous video surveillance.
In this proposed method, the traditional elevators are upgraded in such a way that any alarming situation in the elevator can be detected and then sent to a main center where further action can be taken accordingly. Different emergency situation can be handled by implementing the system. Smart elevator system works by installing different modules inside the elevator such as speed sensors which will detect speed variations occurring above or below a certain threshold of elevator speed. The smart elevator system installed within the elevator sends a message to the emergency response center and sends an automated call as well. The smart system also includes an emotion detection algorithm which will detect emotions of the individual based on their expression in the elevator. The smart system also has a whisper detection system as well to know if someone stuck inside the elevator is alive during any hazardous situation. A broadcast signal is used as a check in the elevator system to evaluate if every part of the system is in stable state. Proposed system can completely replace the current elevator systems and become part of smart homes.
Decreasing the potential for catastrophic consequences poses a significant challenge for high-risk industries. Organizations are under many different pressures, and they are continuously trying to adapt to changing conditions and recover from disturbances and stresses that can arise from both normal operations and unexpected events. Reducing risks in complex systems therefore requires that organizations develop and enhance traits that increase resilience. Resilience provides a holistic approach to safety, emphasizing the creation of organizations and systems that are proactive, interactive, reactive, and adaptive. This approach relies on disciplines such as system safety and emergency management, but also requires that organizations develop indicators and ways of knowing when an emergency is imminent. A resilient organization must be adaptive, using hands-on activities and lessons learned efforts to better prepare it to respond to future disruptions. It is evident from the discussions of each of the traits of resilience, including their limitations, that there are no easy answers to reducing safety risks in complex systems. However, efforts to strengthen resilience may help organizations better address the challenges associated with the ever-increasing complexities of their systems.
Multi-touch attribution, which allows distributing the credit to all related advertisements based on their corresponding contributions, has recently become an important research topic in digital advertising. Traditionally, rule-based attribution models have been used in practice. The drawback of such rule-based models lies in the fact that the rules are not derived form the data but only based on simple intuition. With the ever enhanced capability to tracking advertisement and users' interaction with the advertisement, data-driven multi-touch attribution models, which attempt to infer the contribution from user interaction data, become an important research direction. We here propose a new data-driven attribution model based on survival theory. By adopting a probabilistic framework, one key advantage of the proposed model is that it is able to remove the presentation biases inherit to most of the other attribution models. In addition to model the attribution, the proposed model is also able to predict user's 'conversion' probability. We validate the proposed method with a real-world data set obtained from a operational commercial advertising monitoring company. Experiment results have shown that the proposed method is quite promising in both conversion prediction and attribution.