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2021-05-13
Bansal, Naman, Agarwal, Chirag, Nguyen, Anh.  2020.  SAM: The Sensitivity of Attribution Methods to Hyperparameters. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). :11–21.
Attribution methods can provide powerful insights into the reasons for a classifier's decision. We argue that a key desideratum of an explanation method is its robustness to input hyperparameters which are often randomly set or empirically tuned. High sensitivity to arbitrary hyperparameter choices does not only impede reproducibility but also questions the correctness of an explanation and impairs the trust of end-users. In this paper, we provide a thorough empirical study on the sensitivity of existing attribution methods. We found an alarming trend that many methods are highly sensitive to changes in their common hyperparameters e.g. even changing a random seed can yield a different explanation! Interestingly, such sensitivity is not reflected in the average explanation accuracy scores over the dataset as commonly reported in the literature. In addition, explanations generated for robust classifiers (i.e. which are trained to be invariant to pixel-wise perturbations) are surprisingly more robust than those generated for regular classifiers.
2020-11-30
Hsu, W., Victora, R. H..  2019.  Micromagnetic Study of Media Noise Plateau in Heat-Assisted Magnetic Recording. IEEE Transactions on Magnetics. 55:1–4.
The relationship between integrated media noise power and linear density in heat-assisted magnetic recording (HAMR) is discussed. A noise plateau for intermediate recording density has been observed in HAMR, similar to that found in perpendicular magnetic recording (PMR). Here, we show, by changing the temperature profile of the heat spot in HAMR, that we can tune the noise plateau regions to different recording densities. The heat spot with sharp temperature gradient favors a plateau at high recording density, while the heat spot with gradual temperature gradient favors a plateau at low recording density. This effect is argued to be a consequence of the competition between transition noise and remanence noise in HAMR.
2020-10-12
Asadi, Nima, Rege, Aunshul, Obradovic, Zoran.  2018.  Analysis of Adversarial Movement Through Characteristics of Graph Topological Ordering. 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). :1–6.
Capturing the patterns in adversarial movement can provide valuable information regarding how the adversaries progress through cyberattacks. This information can be further employed for making comparisons and interpretations of decision making of the adversaries. In this study, we propose a framework based on concepts of social networks to characterize and compare the patterns, variations and shifts in the movements made by an adversarial team during a real-time cybersecurity exercise. We also explore the possibility of movement association with the skill sets using topological sort networks. This research provides preliminary insight on adversarial movement complexity and linearity and decision-making as cyberattacks unfold.
2020-09-04
Sutton, Sara, Bond, Benjamin, Tahiri, Sementa, Rrushi, Julian.  2019.  Countering Malware Via Decoy Processes with Improved Resource Utilization Consistency. 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA). :110—119.
The concept of a decoy process is a new development of defensive deception beyond traditional honeypots. Decoy processes can be exceptionally effective in detecting malware, directly upon contact or by redirecting malware to decoy I/O. A key requirement is that they resemble their real counterparts very closely to withstand adversarial probes by threat actors. To be usable, decoy processes need to consume only a small fraction of the resources consumed by their real counterparts. Our contribution in this paper is twofold. We attack the resource utilization consistency of decoy processes provided by a neural network with a heatmap training mechanism, which we find to be insufficiently trained. We then devise machine learning over control flow graphs that improves the heatmap training mechanism. A neural network retrained by our work shows higher accuracy and defeats our attacks without a significant increase in its own resource utilization.
2020-08-28
Knierim, Pascal, Kiss, Francisco, Schmidt, Albrecht.  2018.  Look Inside: Understanding Thermal Flux Through Augmented Reality. 2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). :170—171.
The transition from high school to university is an exciting time for students including many new challenges. Particularly in the field of science, technology, engineering, and mathematics, the university dropout rate may reach up to 40%. The studies of physics rely on many abstract concepts and quantities that are not directly visible like energy or heat. We developed a mixed reality application for education, which augments the thermal conduction of metal by overlaying a representation of temperature as false-color visualization directly onto the object. This real-time augmentation avoids attention split and overcomes the perception gap by amplifying the human eye. Augmented and Virtual Reality environments allow students to perform experiments that were impossible to conduct for security or financial reasons. With the application, we try to foster a deeper understanding of the learning material and higher engagement during the studies.
2020-04-13
Wadsworth, Anthony, Thanoon, Mohammed I., McCurry, Charles, Sabatto, Saleh Zein.  2019.  Development of IIoT Monitoring and Control Security Scheme for Cyber Physical Systems. 2019 SoutheastCon. :1–5.
Industry 4.0 or the fourth industrial revolution encapsulates future industry development trends to achieve more intelligent manufacturing processes, including reliance on Cyber Physical Systems (CPS). The increase in online access and control given by the incorporation of CPSs introduces a new challenge securing the operations of the CPS in that they are not supported by standard security protocols. This paper describes a process used to effectively protect the operations of an IIoT system by implementing security protocols on the CPS within the IIoT. A series of predefined boundary conditions of the safety critical parameters for which a heating and cooling CPS can safely operate within were established. If the CPS is commended to operate outside of these boundaries, it will disconnect from all external communication network and default to some pre-defined safe-operation mode until the system has been evaluated locally by an administrator and released from the safe-mode. This method was tested and validated by establishing a sample IIoT and CPS testbed setup which monitor and control the temperature of a target environment. An attack was initiated to force the target environment outside of the determined safety-critical parameters. The system responded by disabling all network ports and defaulted to the safe-operation mode established previously.
2019-03-15
Cozzi, M., Galliere, J., Maurine, P..  2018.  Exploiting Phase Information in Thermal Scans for Stealthy Trojan Detection. 2018 21st Euromicro Conference on Digital System Design (DSD). :573-576.

Infrared thermography has been recognized for its ability to investigate integrated circuits in a non destructive way. Coupled to lock-in correlation it has proven efficient in detecting thermal hot spots. Most of the state of the Art measurement systems are based on amplitude analysis. In this paper we propose to investigate weak thermal hot spots using the phase of infrared signals. We demonstrate that phase analysis is a formidable alternative to amplitude to detect small heat signatures. Finally, we apply our measurement platform and its detection method to the identification of stealthy hardware Trojans.

2018-09-05
Jia, R., Dong, R., Ganesh, P., Sastry, S., Spanos, C..  2017.  Towards a theory of free-lunch privacy in cyber-physical systems. 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton). :902–910.

Emerging cyber-physical systems (CPS) often require collecting end users' data to support data-informed decision making processes. There has been a long-standing argument as to the tradeoff between privacy and data utility. In this paper, we adopt a multiparametric programming approach to rigorously study conditions under which data utility has to be sacrificed to protect privacy and situations where free-lunch privacy can be achieved, i.e., data can be concealed without hurting the optimality of the decision making underlying the CPS. We formalize the concept of free-lunch privacy, and establish various results on its existence, geometry, as well as efficient computation methods. We propose the free-lunch privacy mechanism, which is a pragmatic mechanism that exploits free-lunch privacy if it exists with the constant guarantee of optimal usage of data. We study the resilience of this mechanism against attacks that attempt to infer the parameter of a user's data generating process. We close the paper by a case study on occupancy-adaptive smart home temperature control to demonstrate the efficacy of the mechanism.

2018-02-27
Qiao, Z., Cheng, L., Zhang, S., Yang, L., Guo, C..  2017.  Detection of Composite Insulators Inner Defects Based on Flash Thermography. 2017 1st International Conference on Electrical Materials and Power Equipment (ICEMPE). :359–363.

Usually, the air gap will appear inside the composite insulators and it will lead to serious accident. In order to detect these internal defects in composite insulators operated in the transmission lines, a new non-destructive technique has been proposed. In the study, the mathematical analysis model of the composite insulators inner defects, which is about heat diffusion, has been build. The model helps to analyze the propagation process of heat loss and judge the structure and defects under the surface. Compared with traditional detection methods and other non-destructive techniques, the technique mentioned above has many advantages. In the study, air defects of composite insulators have been made artificially. Firstly, the artificially fabricated samples are tested by flash thermography, and this method shows a good performance to figure out the structure or defects under the surface. Compared the effect of different excitation between flash and hair drier, the artificially samples have a better performance after heating by flash. So the flash excitation is better. After testing by different pollution on the surface, it can be concluded that different pollution don't have much influence on figuring out the structure or defect under the surface, only have some influence on heat diffusion. Then the defective composite insulators from work site are detected and the image of defect is clear. This new active thermography system can be detected quickly, efficiently and accurately, ignoring the influence of different pollution and other environmental restrictions. So it will have a broad prospect of figuring out the defeats and structure in composite insulators even other styles of insulators.