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Kessel, Ronald.  2010.  The positive force of deterrence: Estimating the quantitative effects of target shifting. 2010 International WaterSide Security Conference. :1–5.
The installation of a protection system can provide protection by either deterring or stopping an attacker. Both modes of effectiveness-deterring and stopping-are uncertain. Some have guessed that deterrence plays a much bigger role than stopping force. The force of deterrence should therefore be of considerable interest, especially if its effect could be estimated and incorporated into a larger risk analysis and business case for developing and buying new systems, but nowhere has it been estimated quantitatively. The effect of one type of deterrence, namely, influencing an attacker's choice of targets-or target shifting, biasing an attacker away from some targets toward others-is assessed quantitatively here using a game-theoretic approach. It is shown that its positive effects are significant. It features as a force multiplier on the order of magnitude or more, even for low-performance security countermeasures whose effectiveness may be compromised somewhat, of necessity, in order to keep the number of false alarms serviceably low. The analysis furthermore implies that there are certain minimum levels of stopping performance that a protection should provide in order to avoid attracting the choice of attackers (under deterrence). Nothing in the analysis argues for complacency in security. Developers must still design the best affordable systems. The analysis enters into the middle ground of security, between no protection and impossibly perfect protection. It counters the criticisms that some raise about lower-level, affordable, sustainable measures that security providers naturally gravitate toward. Although these measures might in some places be defeated in ways that a non-expert can imagine, the measures are not for that reason irresponsible or to be dismissed. Their effectiveness can be much greater than they first appear.
Liu, Y., Yang, Y., Shi, A., Jigang, P., Haowei, L..  2019.  Intelligent monitoring of indoor surveillance video based on deep learning. 2019 21st International Conference on Advanced Communication Technology (ICACT). :648–653.

With the rapid development of information technology, video surveillance system has become a key part in the security and protection system of modern cities. Especially in prisons, surveillance cameras could be found almost everywhere. However, with the continuous expansion of the surveillance network, surveillance cameras not only bring convenience, but also produce a massive amount of monitoring data, which poses huge challenges to storage, analytics and retrieval. The smart monitoring system equipped with intelligent video analytics technology can monitor as well as pre-alarm abnormal events or behaviours, which is a hot research direction in the field of surveillance. This paper combines deep learning methods, using the state-of-the-art framework for instance segmentation, called Mask R-CNN, to train the fine-tuning network on our datasets, which can efficiently detect objects in a video image while simultaneously generating a high-quality segmentation mask for each instance. The experiment show that our network is simple to train and easy to generalize to other datasets, and the mask average precision is nearly up to 98.5% on our own datasets.

Refaat, S. S., Mohamed, A., Kakosimos, P..  2018.  Self-Healing control strategy; Challenges and opportunities for distribution systems in smart grid. 2018 IEEE 12th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG 2018). :1–6.
Implementation of self-healing control system in smart grid is a persisting challenge. Self-Healing control strategy is the important guarantee to implement the smart grid. In addition, it is the support of achieving the secure operation, improving the reliability and security of distribution grid, and realizing the smart distribution grid. Although self-healing control system concept is presented in smart grid context, but the complexity of distribution network structure recommended to choose advanced control and protection system using a self-healing, this system must be able to heal any disturbance in the distribution system of smart grid to improve efficiency, resiliency, continuity, and reliability of the smart grid. This review focuses mostly on the key technology of self-healing control, gives an insight into the role of self-healing in distribution system advantages, study challenges and opportunities in the prospect of utilities. The main contribution of this paper is demonstrating proposed architecture, control strategy for self-healing control system includes fault detection, fault localization, faulted area isolation, and power restoration in the electrical distribution system.
Chen, L., May, J..  2017.  Theoretical Feasibility of Statistical Assurance of Programmable Systems Based on Simulation Tests. 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). :630–631.

This presents a new model to support empirical failure probability estimation for a software-intensive system. The new element of the approach is that it combines the results of testing using a simulated hardware platform with results from testing on the real platform. This approach addresses a serious practical limitation of a technique known as statistical testing. This limitation will be called the test time expansion problem (or simply the 'time problem'), which is that the amount of testing required to demonstrate useful levels of reliability over a time period T is many orders of magnitude greater than T. The time problem arises whether the aim is to demonstrate ultra-high reliability levels for protection system, or to demonstrate any (desirable) reliability levels for continuous operation ('high demand') systems. Specifically, the theoretical feasibility of a platform simulation approach is considered since, if this is not proven, questions of practical implementation are moot. Subject to the assumptions made in the paper, theoretical feasibility is demonstrated.

Harrison, Michael A., Ruzzo, Walter L., Ullman, Jeffrey D..  1976.  Protection in Operating Systems. Commun. ACM. 19:461–471.

A model of protection mechanisms in computing systems is presented and its appropriateness is argued. The “safety” problem for protection systems under this model is to determine in a given situation whether a subject can acquire a particular right to an object. In restricted cases, it can be shown that this problem is decidable, i.e. there is an algorithm to determine whether a system in a particular configuration is safe. In general, and under surprisingly weak assumptions, it cannot be decided if a situation is safe. Various implications of this fact are discussed.

This article was identified by the SoS Best Scientific Cybersecurity Paper Competition Distinguished Experts as a Science of Security Significant Paper.

The Science of Security Paper Competition was developed to recognize and honor recently published papers that advance the science of cybersecurity. During the development of the competition, members of the Distinguished Experts group suggested that listing papers that made outstanding contributions, empirical or theoretical, to the science of cybersecurity in earlier years would also benefit the research community.