Visible to the public Biblio

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2017-02-27
Chessa, M., Grossklags, J., Loiseau, P..  2015.  A Game-Theoretic Study on Non-monetary Incentives in Data Analytics Projects with Privacy Implications. 2015 IEEE 28th Computer Security Foundations Symposium. :90–104.

The amount of personal information contributed by individuals to digital repositories such as social network sites has grown substantially. The existence of this data offers unprecedented opportunities for data analytics research in various domains of societal importance including medicine and public policy. The results of these analyses can be considered a public good which benefits data contributors as well as individuals who are not making their data available. At the same time, the release of personal information carries perceived and actual privacy risks to the contributors. Our research addresses this problem area. In our work, we study a game-theoretic model in which individuals take control over participation in data analytics projects in two ways: 1) individuals can contribute data at a self-chosen level of precision, and 2) individuals can decide whether they want to contribute at all (or not). From the analyst's perspective, we investigate to which degree the research analyst has flexibility to set requirements for data precision, so that individuals are still willing to contribute to the project, and the quality of the estimation improves. We study this tradeoffs scenario for populations of homogeneous and heterogeneous individuals, and determine Nash equilibrium that reflect the optimal level of participation and precision of contributions. We further prove that the analyst can substantially increase the accuracy of the analysis by imposing a lower bound on the precision of the data that users can reveal.

Li-xiong, Z., Xiao-lin, X., Jia, L., Lu, Z., Xuan-chen, P., Zhi-yuan, M., Li-hong, Z..  2015.  Malicious URL prediction based on community detection. 2015 International Conference on Cyber Security of Smart Cities, Industrial Control System and Communications (SSIC). :1–7.

Traditional Anti-virus technology is primarily based on static analysis and dynamic monitoring. However, both technologies are heavily depended on application files, which increase the risk of being attacked, wasting of time and network bandwidth. In this study, we propose a new graph-based method, through which we can preliminary detect malicious URL without application file. First, the relationship between URLs can be found through the relationship between people and URLs. Then the association rules can be mined with confidence of each frequent URLs. Secondly, the networks of URLs was built through the association rules. When the networks of URLs were finished, we clustered the date with modularity to detect communities and every community represents different types of URLs. We suppose that a URL has association with one community, then the URL is malicious probably. In our experiments, we successfully captured 82 % of malicious samples, getting a higher capture than using traditional methods.

Wei, Q., Shi, X..  2015.  The optimal contracts in continuous time under Knightian uncertainty. 2015 34th Chinese Control Conference (CCC). :2450–2455.

In this paper, we focus on the principal-agent problems in continuous time when the participants have ambiguity on the output process in the framework of g-expectation. The first best (or, risk-sharing) type is studied. The necessary condition of the optimal contract is derived by means of the optimal control theory. Finally, we present some examples to clarify our results.

Sun, H., Luo, H., Wu, T. Y., Obaidat, M. S..  2015.  A PSNR-Controllable Data Hiding Algorithm Based on LSBs Substitution. 2015 IEEE Global Communications Conference (GLOBECOM). :1–7.

There are more and more systems using mobile devices to perform sensing tasks, but these increase the risk of leakage of personal privacy and data. Data hiding is one of the important ways for information security. Even though many data hiding algorithms have worked on providing more hiding capacity or higher PSNR, there are few algorithms that can control PSNR effectively while ensuring hiding capacity. In this paper, with controllable PSNR based on LSBs substitution- PSNR-Controllable Data Hiding (PCDH), we first propose a novel encoding plan for data hiding. In PCDH, we use the remainder algorithm to calculate the hidden information, and hide the secret information in the last x LSBs of every pixel. Theoretical proof shows that this method can control the variation of stego image from cover image, and control PSNR by adjusting parameters in the remainder calculation. Then, we design the encoding and decoding algorithms with low computation complexity. Experimental results show that PCDH can control the PSNR in a given range while ensuring high hiding capacity. In addition, it can resist well some steganalysis. Compared to other algorithms, PCDH achieves better tradeoff among PSNR, hiding capacity, and computation complexity.

Dou, Huijing, Bian, Tingting.  2015.  An effective information filtering method based on the LTE network. 2015 4th International Conference on Computer Science and Network Technology (ICCSNT). 01:1428–1432.

With the rapid development of the information technology, more and more high-speed networks came out. The 4G LTE network as a recently emerging network has gradually entered the mainstream of the communication network. This paper proposed an effective content-based information filtering based on the 4G LTE high-speed network by combing the content-based filter and traditional simple filter. Firstly, raw information is pre-processed by five-tuple filter. Secondly, we determine the topics and character of the source data by key nearest neighbor text classification after minimum-risk Bayesian classification. Finally, the improved AdaBoost algorithm achieves the four-level content-based information filtering. The experiments reveal that the effective information filtering method can be applied to the network security, big data analysis and other fields. It has high research value and market value.

Na, L., Yunwei, D., Tianwei, C., Chao, W., Yang, G..  2015.  The Legitimacy Detection for Multilevel Hybrid Cloud Algorithm Based Data Access. Reliability and Security - Companion 2015 IEEE International Conference on Software Quality. :169–172.

In this paper a joint algorithm was designed to detect a variety of unauthorized access risks in multilevel hybrid cloud. First of all, the access history is recorded among different virtual machines in multilevel hybrid cloud using the global flow diagram. Then, the global flow graph is taken as auxiliary decision-making basis to design legitimacy detection algorithm based data access and is represented by formal representation, Finally the implement process was specified, and the algorithm can effectively detect operating against regulations such as simple unauthorized level across, beyond indirect unauthorized and other irregularities.

Li, Z., Oechtering, T. J..  2015.  Privacy on hypothesis testing in smart grids. 2015 IEEE Information Theory Workshop - Fall (ITW). :337–341.

In this paper, we study the problem of privacy information leakage in a smart grid. The privacy risk is assumed to be caused by an unauthorized binary hypothesis testing of the consumer's behaviour based on the smart meter readings of energy supplies from the energy provider. Another energy supplies are produced by an alternative energy source. A controller equipped with an energy storage device manages the energy inflows to satisfy the energy demand of the consumer. We study the optimal energy control strategy which minimizes the asymptotic exponential decay rate of the minimum Type II error probability in the unauthorized hypothesis testing to suppress the privacy risk. Our study shows that the cardinality of the energy supplies from the energy provider for the optimal control strategy is no more than two. This result implies a simple objective of the optimal energy control strategy. When additional side information is available for the adversary, the optimal control strategy and privacy risk are compared with the case of leaking smart meter readings to the adversary only.

Latif, Z. A., Mohamad, M. H..  2015.  Mapping of Dengue Outbreak Distribution Using Spatial Statistics and Geographical Information System. 2015 2nd International Conference on Information Science and Security (ICISS). :1–6.

This study presents spatial analysis of Dengue Fever (DF) outbreak using Geographic Information System (GIS) in the state of Selangor, Malaysia. DF is an Aedes mosquito-borne disease. The aim of the study is to map the spread of DF outbreak in Selangor by producing a risk map while the objective is to identify high risk areas of DF by producing a risk map using GIS tools. The data used was DF dengue cases in 2012 obtained from Ministry of Health, Malaysia. The analysis was carried out using Moran's I, Average Nearest Neighbor (ANN), Kernel Density Estimation (KDE) and buffer analysis using GIS. From the Moran's I analysis, the distribution pattern of DF in Selangor clustered. From the ANN analysis, the result shows a dispersed pattern where the ratio is more than 1. The third analysis was based on KDE to locate the hot spot location. The result shows that some districts are classified as high risk areas which are Ampang, Damansara, Kapar, Kajang, Klang, Semenyih, Sungai Buloh and Petaling. The buffer analysis, area ranges between 200m. to 500m. above sea level shows a clustered pattern where the highest frequent cases in the year are at the same location. It was proven that the analysis based on the spatial statistic, spatial interpolation, and buffer analysis can be used as a method in controlling and locating the DF affection with the aid of GIS.

Lever, K. E., Kifayat, K., Merabti, M..  2015.  Identifying interdependencies using attack graph generation methods. 2015 11th International Conference on Innovations in Information Technology (IIT). :80–85.

Information and communication technologies have augmented interoperability and rapidly advanced varying industries, with vast complex interconnected networks being formed in areas such as safety-critical systems, which can be further categorised as critical infrastructures. What also must be considered is the paradigm of the Internet of Things which is rapidly gaining prevalence within the field of wireless communications, being incorporated into areas such as e-health and automation for industrial manufacturing. As critical infrastructures and the Internet of Things begin to integrate into much wider networks, their reliance upon communication assets by third parties to ensure collaboration and control of their systems will significantly increase, along with system complexity and the requirement for improved security metrics. We present a critical analysis of the risk assessment methods developed for generating attack graphs. The failings of these existing schemas include the inability to accurately identify the relationships and interdependencies between the risks and the reduction of attack graph size and generation complexity. Many existing methods also fail due to the heavy reliance upon the input, identification of vulnerabilities, and analysis of results by human intervention. Conveying our work, we outline our approach to modelling interdependencies within large heterogeneous collaborative infrastructures, proposing a distributed schema which utilises network modelling and attack graph generation methods, to provide a means for vulnerabilities, exploits and conditions to be represented within a unified model.

Wei, L., Moghadasi, A. H., Sundararajan, A., Sarwat, A. I..  2015.  Defending mechanisms for protecting power systems against intelligent attacks. 2015 10th System of Systems Engineering Conference (SoSE). :12–17.

The power system forms the backbone of a modern society, and its security is of paramount importance to nation's economy. However, the power system is vulnerable to intelligent attacks by attackers who have enough knowledge of how the power system is operated, monitored and controlled. This paper proposes a game theoretic approach to explore and evaluate strategies for the defender to protect the power systems against such intelligent attacks. First, a risk assessment is presented to quantify the physical impacts inflicted by attacks. Based upon the results of the risk assessment, this paper represents the interactions between the attacker and the defender by extending the current zero-sum game model to more generalized game models for diverse assumptions concerning the attacker's motivation. The attacker and defender's equilibrium strategies are attained by solving these game models. In addition, a numerical illustration is demonstrated to warrant the theoretical outcomes.

Geng, J., Ye, D., Luo, P..  2015.  Forecasting severity of software vulnerability using grey model GM(1,1). 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :344–348.

Vulnerabilities usually represents the risk level of software, and it is of high value to forecast vulnerabilities so as to evaluate the security level of software. Current researches mainly focus on predicting the number of vulnerabilities or the occurrence time of vulnerabilities, however, to our best knowledge, there are no other researches focusing on the prediction of vulnerabilities' severity, which we think is an important aspect reflecting vulnerabilities and software security. To compensate for this deficiency, we borrows the grey model GM(1,1) from grey system theory to forecast the severity of vulnerabilities. The experiment is carried on the real data collected from CVE and proves the feasibility of our predicting method.

Santini, R., Foglietta, C., Panzieri, S..  2015.  A graph-based evidence theory for assessing risk. 2015 18th International Conference on Information Fusion (Fusion). :1467–1474.

The increasing exploitation of the internet leads to new uncertainties, due to interdependencies and links between cyber and physical layers. As an example, the integration between telecommunication and physical processes, that happens when the power grid is managed and controlled, yields to epistemic uncertainty. Managing this uncertainty is possible using specific frameworks, usually coming from fuzzy theory such as Evidence Theory. This approach is attractive due to its flexibility in managing uncertainty by means of simple rule-based systems with data coming from heterogeneous sources. In this paper, Evidence Theory is applied in order to evaluate risk. Therefore, the authors propose a frame of discernment with a specific property among the elements based on a graph representation. This relationship leads to a smaller power set (called Reduced Power Set) that can be used as the classical power set, when the most common combination rules, such as Dempster or Smets, are applied. The paper demonstrates how the use of the Reduced Power Set yields to more efficient algorithms for combining evidences and to application of Evidence Theory for assessing risk.

Saravanan, S., Sabari, A., Geetha, M., priyanka, Q..  2015.  Code based community network for identifying low risk community. 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO). :1–6.

The modern day approach in boulevard network centers on efficient factor in safe routing. The safe routing must follow up the low risk cities. The troubles in routing are a perennial one confronting people day in and day out. The common goal of everyone using a boulevard seems to be reaching the desired point through the fastest manner which involves the balancing conundrum of multiple expected and unexpected influencing factors such as time, distance, security and cost. It is universal knowledge that travelling is an almost inherent aspect in everyone's daily routine. With the gigantic and complex road network of a modern city or country, finding a low risk community for traversing the distance is not easy to achieve. This paper follows the code based community for detecting the boulevard network and fuzzy technique for identifying low risk community.

Ismail, Z., Leneutre, J., Bateman, D., Chen, L..  2015.  A Game-Theoretical Model for Security Risk Management of Interdependent ICT and Electrical Infrastructures. 2015 IEEE 16th International Symposium on High Assurance Systems Engineering. :101–109.

The communication infrastructure is a key element for management and control of the power system in the smart grid. The communication infrastructure, which can include equipment using off-the-shelf vulnerable operating systems, has the potential to increase the attack surface of the power system. The interdependency between the communication and the power system renders the management of the overall security risk a challenging task. In this paper, we address this issue by presenting a mathematical model for identifying and hardening the most critical communication equipment used in the power system. Using non-cooperative game theory, we model interactions between an attacker and a defender. We derive the minimum defense resources required and the optimal strategy of the defender that minimizes the risk on the power system. Finally, we evaluate the correctness and the efficiency of our model via a case study.

Gonzalez-Longatt, F., Carmona-Delgado, C., Riquelme, J., Burgos, M., Rueda, J. L..  2015.  Risk-based DC security assessment for future DC-independent system operator. 2015 International Conference on Energy Economics and Environment (ICEEE). :1–8.

The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included.

Rontidis, G., Panaousis, E., Laszka, A., Dagiuklas, T., Malacaria, P., Alpcan, T..  2015.  A game-theoretic approach for minimizing security risks in the Internet-of-Things. 2015 IEEE International Conference on Communication Workshop (ICCW). :2639–2644.

In the Internet-of-Things (IoT), users might share part of their data with different IoT prosumers, which offer applications or services. Within this open environment, the existence of an adversary introduces security risks. These can be related, for instance, to the theft of user data, and they vary depending on the security controls that each IoT prosumer has put in place. To minimize such risks, users might seek an “optimal” set of prosumers. However, assuming the adversary has the same information as the users about the existing security measures, he can then devise which prosumers will be preferable (e.g., with the highest security levels) and attack them more intensively. This paper proposes a decision-support approach that minimizes security risks in the above scenario. We propose a non-cooperative, two-player game entitled Prosumers Selection Game (PSG). The Nash Equilibria of PSG determine subsets of prosumers that optimize users' payoffs. We refer to any game solution as the Nash Prosumers Selection (NPS), which is a vector of probabilities over subsets of prosumers. We show that when using NPS, a user faces the least expected damages. Additionally, we show that according to NPS every prosumer, even the least secure one, is selected with some non-zero probability. We have also performed simulations to compare NPS against two different heuristic selection algorithms. The former is proven to be approximately 38% more effective in terms of security-risk mitigation.

Li, X., He, Z., Zhang, S..  2015.  Robust optimization of risk for power system based on information gap decision theory. 2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT). :200–204.

Risk-control optimization has great significance for security of power system. Usually the probabilistic uncertainties of parameters are considered in the research of risk optimization of power system. However, the method of probabilistic uncertainty description will be insufficient in the case of lack of sample data. Thus non-probabilistic uncertainties of parameters should be considered, and will impose a significant influence on the results of optimization. To solve this problem, a robust optimization operation method of power system risk-control is presented in this paper, considering the non-probabilistic uncertainty of parameters based on information gap decision theory (IGDT). In the method, loads are modeled as the non-probabilistic uncertainty parameters, and the model of robust optimization operation of risk-control is presented. By solving the model, the maximum fluctuation of the pre-specified target can be obtained, and the strategy of this situation can be obtained at the same time. The proposed model is applied to the IEEE-30 system of risk-control by simulation. The results can provide the valuable information for operating department to risk management.

Abd, S. K., Salih, R. T., Al-Haddad, S. A. R., Hashim, F., Abdullah, A. B. H., Yussof, S..  2015.  Cloud computing security risks with authorization access for secure Multi-Tenancy based on AAAS protocol. TENCON 2015 - 2015 IEEE Region 10 Conference. :1–5.

Many cloud security complexities can be concerned as a result of its open system architecture. One of these complexities is multi-tenancy security issue. This paper discusses and addresses the most common public cloud security complexities focusing on Multi-Tenancy security issue. Multi-tenancy is one of the most important security challenges faced by public cloud services providers. Therefore, this paper presents a secure multi-tenancy architecture using authorization model Based on AAAS protocol. By utilizing cloud infrastructure, access control can be provided to various cloud information and services by our suggested authorization system. Each business can offer several cloud services. These cloud services can cooperate with other services which can be related to the same organization or different one. Moreover, these cooperation agreements are supported by our suggested system.

Zheng, Y., Zheng, S..  2015.  Cyber Security Risk Assessment for Industrial Automation Platform. 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP). :341–344.

Due to the fact that the cyber security risks exist in industrial control system, risk assessment on Industrial Automation Platform (IAP) is discussed in this paper. The cyber security assessment model for IAP is built based on relevant standards at abroad. Fuzzy analytic hierarchy process and fuzzy comprehensive evaluation method based on entropy theory are utilized to evaluate the communication links' risk of IAP software. As a result, the risk weight of communication links which have impacts on platform and the risk level of this platform are given for further study on protective strategy. The assessment result shows that the methods used can evaluate this platform efficiently and practically.

Njenga, K., Ndlovu, S..  2015.  Mobile banking and information security risks: Demand-side predilections of South African lead-users. 2015 Second International Conference on Information Security and Cyber Forensics (InfoSec). :86–92.

South Africa's lead-users predilections to tinker and innovate mobile banking services is driven by various constructs. Advanced technologies have made mobile banking services easy to use, attractive and beneficial. While this is welcome news to many, there are concerns that when lead-users tinker with these services, information security risks are exacerbated. The aim of this article is to present an insightful understanding of the demand-side predilections of South Africa's lead-users in such contexts. We assimilate the theories of Usage Control, (UCON), the Theory of Technology Acceptance Model (TAM), and the Theory of Perceived Risk (TPP) to explain predilections over technology. We demonstrate that constructs derived from these theories can explain the general demand-side predilection to tinker with mobile banking services. A quantitative approach was used to test this. From a sample of South African banking lead-users operating in Gauteng province of South Africa, data was collected and analysed with the help of a software package. We found unexpectedly that, lead-users predilections to tinker with mobile banking services was inhibited by perceived risk. Moreover, male lead-users were more domineering in the tinkering process than female lead-users. The implication for this is discussed and explained in the main body of work.

Mulcahy, J. J., Huang, S..  2015.  An autonomic approach to extend the business value of a legacy order fulfillment system. 2015 Annual IEEE Systems Conference (SysCon) Proceedings. :595–600.

In the modern retailing industry, many enterprise resource planning (ERP) systems are considered legacy software systems that have become too expensive to replace and too costly to re-engineer. Countering the need to maintain and extend the business value of these systems is the need to do so in the simplest, cheapest, and least risky manner available. There are a number of approaches used by software engineers to mitigate the negative impact of evolving a legacy systems, including leveraging service-oriented architecture to automate manual tasks previously performed by humans. A relatively recent approach in software engineering focuses upon implementing self-managing attributes, or “autonomic” behavior in software applications and systems of applications in order to reduce or eliminate the need for human monitoring and intervention. Entire systems can be autonomic or they can be hybrid systems that implement one or more autonomic components to communicate with external systems. In this paper, we describe a commercial development project in which a legacy multi-channel commerce enterprise resource planning system was extended with service-oriented architecture an autonomic control loop design to communicate with an external third-party security screening provider. The goal was to reduce the cost of the human labor necessary to screen an ever-increasing volume of orders and to reduce the potential for human error in the screening process. The solution automated what was previously an inefficient, incomplete, and potentially error-prone manual process by inserting a new autonomic software component into the existing order fulfillment workflow.

M, Supriya, Sangeeta, K., Patra, G. K..  2015.  Comparison of AHP based and Fuzzy based mechanisms for ranking Cloud Computing services. 2015 International Conference on Computer, Control, Informatics and its Applications (IC3INA). :175–180.

Cloud Computing has emerged as a paradigm to deliver on demand resources to facilitate the customers with access to their infrastructure and applications as per their requirements on a subscription basis. An exponential increase in the number of cloud services in the past few years provides more options for customers to choose from. To assist customers in selecting a most trustworthy cloud provider, a unified trust evaluation framework is needed. Trust helps in the estimation of competency of a resource provider in completing a task thus enabling users to select the best resources in the heterogeneous cloud infrastructure. Trust estimates obtained using the AHP process exhibit a deviation for parameters that are not in direct proportion to the contributing attributes. Such deviation can be removed using the Fuzzy AHP model. In this paper, a Fuzzy AHP based hierarchical trust model has been proposed to rate the service providers and their various plans for infrastructure as a service.

Orojloo, H., Azgomi, M. A..  2015.  Evaluating the complexity and impacts of attacks on cyber-physical systems. 2015 CSI Symposium on Real-Time and Embedded Systems and Technologies (RTEST). :1–8.

In this paper, a new method for quantitative evaluation of the security of cyber-physical systems (CPSs) is proposed. The proposed method models the different classes of adversarial attacks against CPSs, including cross-domain attacks, i.e., cyber-to-cyber and cyber-to-physical attacks. It also takes the secondary consequences of attacks on CPSs into consideration. The intrusion process of attackers has been modeled using attack graph and the consequence estimation process of the attack has been investigated using process model. The security attributes and the special parameters involved in the security analysis of CPSs, have been identified and considered. The quantitative evaluation has been done using the probability of attacks, time-to-shutdown of the system and security risks. The validation phase of the proposed model is performed as a case study by applying it to a boiling water power plant and estimating the suitable security measures.

Huda, S., Sudarsono, A., Harsono, T..  2015.  Secure data exchange using authenticated Ciphertext-Policy Attributed-Based Encryption. 2015 International Electronics Symposium (IES). :134–139.

Easy sharing files in public network that is intended only for certain people often resulting in the leaking of sharing folders or files and able to be read also by others who are not authorized. Secure data is one of the most challenging issues in data sharing systems. Here, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is a reliable asymmetric encryption mechanism which deals with secure data and used for data encryption. It is not necessary encrypted to one particular user, but recipient is only able to decrypt if and only if the attribute set of his private key match with the specified policy in the ciphertext. In this paper, we propose a secure data exchange using CP-ABE with authentication feature. The data is attribute-based encrypted to satisfy confidentiality feature and authenticated to satisfy data authentication simultaneously.

Zhang, L., Li, B., Zhang, L., Li, D..  2015.  Fuzzy clustering of incomplete data based on missing attribute interval size. 2015 IEEE 9th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :101–104.

Fuzzy c-means algorithm is used to identity clusters of similar objects within a data set, while it is not directly applied to incomplete data. In this paper, we proposed a novel fuzzy c-means algorithm based on missing attribute interval size for the clustering of incomplete data. In the new algorithm, incomplete data set was transformed to interval data set according to the nearest neighbor rule. The missing attribute value was replaced by the corresponding interval median and the interval size was set as the additional property for the incomplete data to control the effect of interval size in clustering. Experiments on standard UCI data set show that our approach outperforms other clustering methods for incomplete data.