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2020-07-09
Ashouri, Mohammadreza.  2019.  Detecting Input Sanitization Errors in Scala. 2019 Seventh International Symposium on Computing and Networking Workshops (CANDARW). :313—319.

Scala programming language combines object-oriented and functional programming in one concise, high-level language, and the language supports static types that help to avoid bugs in complex programs. This paper proposes a dynamic taint analyzer called ScalaTaint for Scala applications. The analyzer traces the propagation of malicious inputs from untrusted sources to sensitive sink methods in programs that can be exploited by adversaries. In this work, we evaluated the accuracy of ScalaTaint with a security benchmark suite including 7 projects in Scala. As a result, our analyzer could report 49 vulnerabilities within 753,372 lines of code. Moreover, the result of our performance measurement on ScalaBench shows 67% runtime overhead that demonstrates the usefulness and efficiently of our technique in comparison with similar tools.

Fahrenkrog-Petersen, Stephan A., van der Aa, Han, Weidlich, Matthias.  2019.  PRETSA: Event Log Sanitization for Privacy-aware Process Discovery. 2019 International Conference on Process Mining (ICPM). :1—8.

Event logs that originate from information systems enable comprehensive analysis of business processes, e.g., by process model discovery. However, logs potentially contain sensitive information about individual employees involved in process execution that are only partially hidden by an obfuscation of the event data. In this paper, we therefore address the risk of privacy-disclosure attacks on event logs with pseudonymized employee information. To this end, we introduce PRETSA, a novel algorithm for event log sanitization that provides privacy guarantees in terms of k-anonymity and t-closeness. It thereby avoids disclosure of employee identities, their membership in the event log, and their characterization based on sensitive attributes, such as performance information. Through step-wise transformations of a prefix-tree representation of an event log, we maintain its high utility for discovery of a performance-annotated process model. Experiments with real-world data demonstrate that sanitization with PRETSA yields event logs of higher utility compared to methods that exploit frequency-based filtering, while providing the same privacy guarantees.

2020-07-06
Hasan, Kamrul, Shetty, Sachin, Hassanzadeh, Amin, Ullah, Sharif.  2019.  Towards Optimal Cyber Defense Remediation in Cyber Physical Systems by Balancing Operational Resilience and Strategic Risk. MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). :1–8.
A prioritized cyber defense remediation plan is critical for effective risk management in cyber-physical systems (CPS). The increased integration of Information Technology (IT)/Operational Technology (OT) in CPS has to lead to the need to identify the critical assets which, when affected, will impact resilience and safety. In this work, we propose a methodology for prioritized cyber risk remediation plan that balances operational resilience and economic loss (safety impacts) in CPS. We present a platform for modeling and analysis of the effect of cyber threats and random system faults on the safety of CPS that could lead to catastrophic damages. We propose to develop a data-driven attack graph and fault graph-based model to characterize the exploitability and impact of threats in CPS. We develop an operational impact assessment to quantify the damages. Finally, we propose the development of a strategic response decision capability that proposes optimal mitigation actions and policies that balances the trade-off between operational resilience (Tactical Risk) and Strategic Risk.
Mason, Andrew, Zhao, Yifan, He, Hongmei, Gompelman, Raymon, Mandava, Srikanth.  2019.  Online Anomaly Detection of Time Series at Scale. 2019 International Conference on Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). :1–8.
Cyber breaches can result in disruption to business operations, reputation damage as well as directly affecting the financial stability of the targeted corporations, with potential impacts on future profits and stock values. Automatic network-stream monitoring becomes necessary for cyber situation awareness, and time-series anomaly detection plays an important role in network stream monitoring. This study surveyed recent research on time-series analysis methods in respect of parametric and non-parametric techniques, and popular machine learning platforms for data analysis on streaming data on both single server and cloud computing environments. We believe it provides a good reference for researchers in both academia and industry to select suitable (time series) data analysis techniques, and computing platforms, dependent on the data scale and real-time requirements.
Brezhniev, Yevhen.  2019.  Multilevel Fuzzy Logic-Based Approach for Critical Energy Infrastructure’s Cyber Resilience Assessment. 2019 10th International Conference on Dependable Systems, Services and Technologies (DESSERT). :213–217.
This paper presents approach for critical energy infrastructure's (CEI) cyber resilience assessment. The CEI is the vital physical system of systems, whose accidents and failures lead to damage of economy, environment, impact on health and lives of people. The analysis of cyber incidents with Ukrainian CEI confirms the importance of the task of increasing its cyber resilience to external hostile influences and keeping of the appropriate level of functionality, safety and reliability. This paper is devoted to development of approach for CEI's cyber resilience assessment considering the important capacities of its systems (adaptivity, restoration, absorbability, preventive) and interdependencies between them. This approach is based on application of multilevel fuzzy logic models (called as logic-linguistic models, LLM) taking into consideration the data available from expert's knowledge. The comparison between risk management and resilience assurance is performed. The new risk-oriented definition of resiliency is suggested.
Sheela, A., Revathi, S., Iqbal, Atif.  2019.  Cyber Risks Assessment For Intelligent And Non-Intelligent Attacks In Power System. 2019 2nd International Conference on Power and Embedded Drive Control (ICPEDC). :40–45.
Smart power grid is a perfect model of Cyber Physical System (CPS) which is an important component for a comfortable life. The major concern of the electrical network is safety and reliable operation. A cyber attacker in the operation of power system would create a major damage to the entire power system structure and affect the continuity of the power supply by adversely changing its parameters. A risk assessment method is presented for evaluating the cyber security assessment of power systems taking into consideration the need for protection systems. The paper considers the impact of bus and transmission line protection systems located in substations on the cyber physical performance of power systems. The proposed method is to simulate the response of power systems to sudden attacks on various power system preset value and parameters. This paper focuses on the cyber attacks which occur in a co-ordinated way so that many power system components will be in risk. The risk can be modelled as the combined probability of power system impact due to attacks and of successful interruption into the system. Stochastic Petri Nets is employed for assessing the risks. The effectiveness of the proposed cyber security risk assessment method is simulated for a IEEE39 bus system.
Xiong, Leilei, Grijalva, Santiago.  2019.  N-1 RTU Cyber-Physical Security Assessment Using State Estimation. 2019 IEEE Power Energy Society General Meeting (PESGM). :1–5.
Real-time supervisory control and data acquisition (SCADA) systems use remote terminal units (RTUs) to monitor and manage the flow of power at electrical substations. As their connectivity to different utility and private networks increases, RTUs are becoming more vulnerable to cyber-attacks. Some attacks seek to access RTUs to directly control power system devices with the intent to shed load or cause equipment damage. Other attacks (such as denial-of-service) target network availability and seek to block, delay, or corrupt communications between the RTU and the control center. In the most severe case, when communications are entirely blocked, the loss of an RTU can cause the power system to become unobservable. It is important to understand how losing an RTU impacts the system state (bus voltage magnitudes and angles). The system state is determined by the state estimator and serves as the input to other critical EMS applications. There is currently no systematic approach for assessing the cyber-physical impact of losing RTUs. This paper proposes a methodology for N-1 RTU cyber-physical security assessment that could benefit power system control and operation. We demonstrate our approach on the IEEE 14-bus system as well as on a synthetic 200-bus system.
Tripathi, Dipty, Maurya, Ashish Kumar, Chaturvedi, Amrita, Tripathi, Anil Kumar.  2019.  A Study of Security Modeling Techniques for Smart Systems. 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon). :87–92.
The term “smart” has been used in many ways for describing systems and infrastructure such as smart city, smart home, smart grid, smart meter, etc. These systems may lie in the domain of critical security systems where security can be estimated in terms of confidentiality, integrity and some cases may involve availability for protection against the theft or damage of system resources as well as disruption of the system services. Although, in spite of, being a hot topic to enhance the quality of life, there is no concrete definition of what smart system is and what should be the characteristics of it. Thus, there is a need to identify what these systems actually are and how they can be designed securely. This work firstly attempts to describe attributes related to the smartness to define smart systems. Furthermore, we propose a secure smart system development life cycle, where the security is weaved at all the development phase of smart systems according to principles, guidelines, attack patterns, risk, vulnerability, exploits, and defined rules. Finally, the comparative study is performed for evaluation of traditional security modeling techniques for early assessment of threats and risks in smart systems.
Mikhalevich, I. F., Trapeznikov, V. A..  2019.  Critical Infrastructure Security: Alignment of Views. 2019 Systems of Signals Generating and Processing in the Field of on Board Communications. :1–5.
Critical infrastructures of all countries unites common cyberspace. In this space, there are many threats that can disrupt the security of critical infrastructure in one country, but also cause damage in other countries. This is a reality that makes it necessary to agree on intergovernmental national views on the composition of critical infrastructures, an assessment of their security and protection. The article presents an overview of views on critical infrastructures of the United States, the European Union, the United Kingdom, and the Russian Federation, the purpose of which is to develop common positions.
Cerotti, D., Codetta-Raiteri, D., Egidi, L., Franceschinis, G., Portinale, L., Dondossola, G., Terruggia, R..  2019.  Analysis and Detection of Cyber Attack Processes targeting Smart Grids. 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). :1–5.
This paper proposes an approach based on Bayesian Networks to support cyber security analysts in improving the cyber-security posture of the smart grid. We build a system model that exploits real world context information from both Information and Operational Technology environments in the smart grid, and we use it to demonstrate sample predictive and diagnostic analyses. The innovative contribution of this work is in the methodology capability of capturing the many dependencies involved in the assessment of security threats, and of supporting the security analysts in planning defense and detection mechanisms for energy digital infrastructures.
Lakhno, Valeriy, Kasatkin, Dmytro, Blozva, Andriy.  2019.  Modeling Cyber Security of Information Systems Smart City Based on the Theory of Games and Markov Processes. 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S T). :497–501.
The article considers some aspects of modeling information security circuits for information and communication systems used in Smart City. As a basic research paradigm, the postulates of game theory and mathematical dependencies based on Markov processes were used. Thus, it is possible to sufficiently substantively describe the procedure for selecting rational variants of cyber security systems used to protect information technologies in Smart City. At the same time, using the model proposed by us, we can calculate the probability of cyber threats for the Smart City systems, as well as the cybernetic risks of diverse threats. Further, on the basis of the described indicators, rational contour options are chosen to protect the information systems used in Smart City.
Ben, Yongming, Han, Yanni, Cai, Ning, An, Wei, Xu, Zhen.  2019.  An Online System Dependency Graph Anomaly Detection based on Extended Weisfeiler-Lehman Kernel. MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). :1–6.
Modern operating systems are typical multitasking systems: Running multiple tasks at the same time. Therefore, a large number of system calls belonging to different processes are invoked at the same time. By associating these invocations, one can construct the system dependency graph. In rapidly evolving system dependency graphs, how to quickly find outliers is an urgent issue for intrusion detection. Clustering analysis based on graph similarity will help solve this problem. In this paper, an extended Weisfeiler-Lehman(WL) kernel is proposed. Firstly, an embedded vector with indefinite dimensions is constructed based on the original dependency graph. Then, the vector is compressed with Simhash to generate a fingerprint. Finally, anomaly detection based on clustering is carried out according to these fingerprints. Our scheme can achieve prominent detection with high efficiency. For validation, we choose StreamSpot, a relevant prior work, to act as benchmark, and use the same data set as it to carry out evaluations. Experiments show that our scheme can achieve the highest detection precision of 98% while maintaining a perfect recall performance. Moreover, both quantitative and visual comparisons demonstrate the outperforming clustering effect of our scheme than StreamSpot.
Castillo, Anya, Arguello, Bryan, Cruz, Gerardo, Swiler, Laura.  2019.  Cyber-Physical Emulation and Optimization of Worst-Case Cyber Attacks on the Power Grid. 2019 Resilience Week (RWS). 1:14–18.
In this paper we report preliminary results from the novel coupling of cyber-physical emulation and interdiction optimization to better understand the impact of a CrashOverride malware attack on a notional electric system. We conduct cyber experiments where CrashOverride issues commands to remote terminal units (RTUs) that are controlling substations within a power control area. We identify worst-case loss of load outcomes with cyber interdiction optimization; the proposed approach is a bilevel formulation that incorporates RTU mappings to controllable loads, transmission lines, and generators in the upper-level (attacker model), and a DC optimal power flow (DCOPF) in the lower-level (defender model). Overall, our preliminary results indicate that the interdiction optimization can guide the design of experiments instead of performing a “full factorial” approach. Likewise, for systems where there are important dependencies between SCADA/ICS controls and power grid operations, the cyber-physical emulations should drive improved parameterization and surrogate models that are applied in scalable optimization techniques.
Gries, Stefan, Ollesch, Julius, Gruhn, Volker.  2019.  Modeling Semantic Dependencies to Allow Flow Monitoring in Networks with Black-Box Nodes. 2019 IEEE/ACM 5th International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS). :14–17.
Cyber-Physical Systems are distributed, heterogeneous systems that communicate and exchange data over networks. This creates semantic dependencies between the individual components. In the event of an error, it is difficult to identify the source of an occurring error that is spread due to those underlying dependencies. Tools such as the Information Flow Monitor solve this problem, but require compliance with a protocol. Nodes that do not adhere to this protocol prevent errors from being tracked. In this paper, we present a way to bridge these black-box nodes with a dependency model and to still be able to use them in monitoring tools.
2020-07-03
Libicki, Martin.  2019.  For a Baltic Cyberspace Alliance? 2019 11th International Conference on Cyber Conflict (CyCon). 900:1—14.

In NATO, an attack on one is an attack on all. In recent years, this tenet has been extended to mean that a cyberattack on one is a cyberattack on all. But does what makes sense in the physical world also make sense if extended into cyberspace? And if there is virtue in collective cyberspace defense, is NATO necessarily the right grouping - in a world where, as far as the United States and the United Kingdom are concerned, more of what constitutes cyber defense circulates within the Five Eyes coalition rather than within NATO? To explore these issues, this essay moots the creation of a Baltic-area cyberspace alliance, considers what it would do, assesses its costs and benefits for its members, and concludes by considering whether such an alliance would be also be in the interest of the U.S. Keys to this discussion are (1) the distinction between what constitutes an “attack” in a medium where occupation may result and actions in media where occupation is (currently) meaningless and effects almost always reversible, (2) what collective defense should mean in cyberspace - and where responsibilities may be best discharged within the mix of hardness, pre-emption, and deterrence that constitute defense, (3) the relationship between cyberspace defense and information warfare defense, and (4) the relevance to alliance formation of the fact that while war is dull, dirty, and dangerous, cyber war is none of these three.

Usama, Muhammad, Asim, Muhammad, Qadir, Junaid, Al-Fuqaha, Ala, Imran, Muhammad Ali.  2019.  Adversarial Machine Learning Attack on Modulation Classification. 2019 UK/ China Emerging Technologies (UCET). :1—4.

Modulation classification is an important component of cognitive self-driving networks. Recently many ML-based modulation classification methods have been proposed. We have evaluated the robustness of 9 ML-based modulation classifiers against the powerful Carlini & Wagner (C-W) attack and showed that the current ML-based modulation classifiers do not provide any deterrence against adversarial ML examples. To the best of our knowledge, we are the first to report the results of the application of the C-W attack for creating adversarial examples against various ML models for modulation classification.

Straub, Jeremy.  2019.  Cyber Mutual Assured Destruction as a System of Systems and the Implications for System Design. 2019 14th Annual Conference System of Systems Engineering (SoSE). :137—139.

Mutual assured destruction is a Cold War era principle of deterrence through causing your enemy to fear that you can destroy them to at least the same extent that they can destroy you. It is based on the threat of retaliation and requires systems that can either be triggered after an enemy attack is launched and before the destructive capability is destroyed or systems that can survive an initial attack and be launched in response. During the Cold War, the weapons of mutual assured destructions were nuclear. However, with the incredible reliance on computers for everything from power generation control to banking to agriculture logistics, a cyber attack mutual assured destruction scenario is plausible. This paper presents this concept and considers the deterrent need, to prevent such a crippling attack from ever being launched, from a system of systems perspective.

Giles, Keir, Hartmann, Kim.  2019.  “Silent Battle” Goes Loud: Entering a New Era of State-Avowed Cyber Conflict. 2019 11th International Conference on Cyber Conflict (CyCon). 900:1—13.

The unprecedented transparency shown by the Netherlands intelligence services in exposing Russian GRU officers in October 2018 is indicative of a number of new trends in state handling of cyber conflict. US public indictments of foreign state intelligence officials, and the UK's deliberate provision of information allowing the global media to “dox” GRU officers implicated in the Salisbury poison attack in early 2018, set a precedent for revealing information that previously would have been confidential. This is a major departure from previous practice where the details of state-sponsored cyber attacks would only be discovered through lengthy investigative journalism (as with Stuxnet) or through the efforts of cybersecurity corporations (as with Red October). This paper uses case studies to illustrate the nature of this departure and consider its impact, including potentially substantial implications for state handling of cyber conflict. The paper examines these implications, including: · The effect of transparency on perception of conflict. Greater public knowledge of attacks will lead to greater public acceptance that countermeasures should be taken. This may extend to public preparedness to accept that a state of declared or undeclared war exists with a cyber aggressor. · The resulting effect on legality. This adds a new element to the long-running debates on the legality of cyber attacks or counter-attacks, by affecting the point at which a state of conflict is politically and socially, even if not legally, judged to exist. · The further resulting effect on permissions and authorities to conduct cyber attacks, in the form of adjustment to the glaring imbalance between the means and methods available to aggressors (especially those who believe themselves already to be in conflict) and defenders. Greater openness has already intensified public and political questioning of the restraint shown by NATO and EU nations in responding to Russian actions; this trend will continue. · Consequences for deterrence, both specifically within cyber conflict and also more broadly deterring hostile actions. In sum, the paper brings together the direct and immediate policy implications, for a range of nations and for NATO, of the new apparent policy of transparency.

Lisova, Elena, El Hachem, Jamal, Causevic, Aida.  2019.  Investigating Attack Propagation in a SoS via a Service Decomposition. 2019 IEEE World Congress on Services (SERVICES). 2642-939X:9—14.
A term systems of systems (SoS) refers to a setup in which a number of independent systems collaborate to create a value that each of them is unable to achieve independently. Complexity of a SoS structure is higher compared to its constitute systems that brings challenges in analyzing its critical properties such as security. An SoS can be seen as a set of connected systems or services that needs to be adequately protected. Communication between such systems or services can be considered as a service itself, and it is the paramount for establishment of a SoS as it enables connections, dependencies, and a cooperation. Given that reliable and predictable communication contributes directly to a correct functioning of an SoS, communication as a service is one of the main assets to consider. Protecting it from malicious adversaries should be one of the highest priorities within SoS design and operation. This study aims to investigate the attack propagation problem in terms of service-guarantees through the decomposition into sub-services enriched with preconditions and postconditions at the service levels. Such analysis is required as a prerequisite for an efficient SoS risk assessment at the design stage of the SoS development life cycle to protect it from possibly high impact attacks capable of affecting safety of systems and humans using the system.
Pan, Jonathan.  2019.  Physical Integrity Attack Detection of Surveillance Camera with Deep Learning based Video Frame Interpolation. 2019 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS). :79—85.
Surveillance cameras, which is a form of Cyber Physical System, are deployed extensively to provide visual surveillance monitoring of activities of interest or anomalies. However, these cameras are at risks of physical security attacks against their physical attributes or configuration like tampering of their recording coverage, camera positions or recording configurations like focus and zoom factors. Such adversarial alteration of physical configuration could also be invoked through cyber security attacks against the camera's software vulnerabilities to administratively change the camera's physical configuration settings. When such Cyber Physical attacks occur, they affect the integrity of the targeted cameras that would in turn render these cameras ineffective in fulfilling the intended security functions. There is a significant measure of research work in detection mechanisms of cyber-attacks against these Cyber Physical devices, however it is understudied area with such mechanisms against integrity attacks on physical configuration. This research proposes the use of the novel use of deep learning algorithms to detect such physical attacks originating from cyber or physical spaces. Additionally, we proposed the novel use of deep learning-based video frame interpolation for such detection that has comparatively better performance to other anomaly detectors in spatiotemporal environments.
Abbasi, Milad Haji, Majidi, Babak, Eshghi, Moahmmad, Abbasi, Ebrahim Haji.  2019.  Deep Visual Privacy Preserving for Internet of Robotic Things. 2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI). :292—296.
In the past few years, visual information collection and transmission is increased significantly for various applications. Smart vehicles, service robotic platforms and surveillance cameras for the smart city applications are collecting a large amount of visual data. The preservation of the privacy of people presented in this data is an important factor in storage, processing, sharing and transmission of visual data across the Internet of Robotic Things (IoRT). In this paper, a novel anonymisation method for information security and privacy preservation in visual data in sharing layer of the Web of Robotic Things (WoRT) is proposed. The proposed framework uses deep neural network based semantic segmentation to preserve the privacy in video data base of the access level of the applications and users. The data is anonymised to the applications with lower level access but the applications with higher legal access level can analyze and annotated the complete data. The experimental results show that the proposed method while giving the required access to the authorities for legal applications of smart city surveillance, is capable of preserving the privacy of the people presented in the data.
Adari, Suman Kalyan, Garcia, Washington, Butler, Kevin.  2019.  Adversarial Video Captioning. 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). :24—27.
In recent years, developments in the field of computer vision have allowed deep learning-based techniques to surpass human-level performance. However, these advances have also culminated in the advent of adversarial machine learning techniques, capable of launching targeted image captioning attacks that easily fool deep learning models. Although attacks in the image domain are well studied, little work has been done in the video domain. In this paper, we show it is possible to extend prior attacks in the image domain to the video captioning task, without heavily affecting the video's playback quality. We demonstrate our attack against a state-of-the-art video captioning model, by extending a prior image captioning attack known as Show and Fool. To the best of our knowledge, this is the first successful method for targeted attacks against a video captioning model, which is able to inject 'subliminal' perturbations into the video stream, and force the model to output a chosen caption with up to 0.981 cosine similarity, achieving near-perfect similarity to chosen target captions.
Soper, Braden C..  2019.  A Cyber-Nuclear Deterrence Game. 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). :470—479.

The reliability of nuclear command, control and communications has long been identified as a critical component of the strategic stability among nuclear states. Advances in offensive cyber weaponry have the potential to negatively impact this reliability, threatening strategic stability. In this paper we present a game theoretic model of preemptive cyber attacks against nuclear command, control and communications. The model is a modification of the classic two-player game of Chicken, a standard game theoretic model for nuclear brinksmanship. We fully characterize equilibria in both the complete information game and two distinct two-sided incomplete information games. We show that when both players have advanced cyber capabilities conflict is more likely in equilibrium, regardless of information structure. On the other hand, when at most one player has advanced cyber capabilities, strategic stability depends on the information structure. Under complete information, asymmetric cyber capabilities have a stabilizing effect in which the player with strong cyber has the resolve to stand firm in equilibrium. Under incomplete information, asymmetric cyber capabilities can have both stabilizing and destabilizing effects depending on prior beliefs over opponent cyber capabilities.

2020-06-29
Tran, Thang M., Nguyen, Khanh-Van.  2019.  Fast Detection and Mitigation to DDoS Web Attack Based on Access Frequency. 2019 IEEE-RIVF International Conference on Computing and Communication Technologies (RIVF). :1–6.

We have been investigating methods for establishing an effective, immediate defense mechanism against the DDoS attacks on Web applications via hacker botnets, in which this defense mechanism can be immediately active without preparation time, e.g. for training data, usually asked for in existing proposals. In this study, we propose a new mechanism, including new data structures and algorithms, that allow the detection and filtering of large amounts of attack packets (Web request) based on monitoring and capturing the suspect groups of source IPs that can be sending packets at similar patterns, i.e. with very high and similar frequencies. The proposed algorithm places great emphasis on reducing storage space and processing time so it is promising to be effective in real-time attack response.

2020-06-26
Wang, Manxi, Liu, Bingjie, Xu, Haitao.  2019.  Resource Allocation for Threat Defense in Cyber-security IoT system. 2019 28th Wireless and Optical Communications Conference (WOCC). :1—3.
In this paper, we design a model for resource allocation in IoT system considering the cyber security, to achieve optimal resource allocation when defend the attack and threat. The resource allocation problem is constructed as a dynamic game, where the threat level is the state and the defend cost is the objective function. Open loop solution and feedback solutions are both given to the defender as the optimal control variables under different solutions situations. The optimal allocated resource and the optimal threat level for the defender is simulated through the numerical simulations.