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Thompson, M., Evans, N., Kisekka, V..  2014.  Multiple OS rotational environment an implemented Moving Target Defense. Resilient Control Systems (ISRCS), 2014 7th International Symposium on. :1-6.

Cyber-attacks continue to pose a major threat to existing critical infrastructure. Although suggestions for defensive strategies abound, Moving Target Defense (MTD) has only recently gained attention as a possible solution for mitigating cyber-attacks. The current work proposes a MTD technique that provides enhanced security through a rotation of multiple operating systems. The MTD solution developed in this research utilizes existing technology to provide a feasible dynamic defense solution that can be deployed easily in a real networking environment. In addition, the system we developed was tested extensively for effectiveness using CORE Impact Pro (CORE), Nmap, and manual penetration tests. The test results showed that platform diversity and rotation offer improved security. In addition, the likelihood of a successful attack decreased proportionally with time between rotations.

Lin, Jerry Chun-Wei, Zhang, Yuyu, Chen, Chun-Hao, Wu, Jimmy Ming-Tai, Chen, Chien-Ming, Hong, Tzung-Pei.  2018.  A Multiple Objective PSO-Based Approach for Data Sanitization. 2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI). :148–151.
In this paper, a multi-objective particle swarm optimization (MOPSO)-based framework is presented to find the multiple solutions rather than a single one. The presented grid-based algorithm is used to assign the probability of the non-dominated solution for next iteration. Based on the designed algorithm, it is unnecessary to pre-define the weights of the side effects for evaluation but the non-dominated solutions can be discovered as an alternative way for data sanitization. Extensive experiments are carried on two datasets to show that the designed grid-based algorithm achieves good performance than the traditional single-objective evolution algorithms.
Takahashi, Hironao, Lakhani, Uzair.  2019.  Multiple Layered Security Analyses Method for Cryptocurrency Exchange Servicers. 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE). :71–73.
Internet is a common method of trading business today. The usage of cryptocurrencies has increased these days and it has become a trend to utilize them. Cryptocurrency exchange servicers provide different smartphone apps that unfortunately may become the target of malicious attacks. This paper focuses on how it achieves highest security and proposes the multiple layered security analyses method for cryptocurrency exchange servicers.
Mashaly, Maggie, El Saied, Ahmed, Alexan, Wassim, Khalifa, Abeer S..  2019.  A Multiple Layer Security Scheme Utilizing Information Matrices. 2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA). :284–289.
This paper proposes a double-layer message security scheme that is implemented in two stages. First, the secret data is encrypted using the AES algorithm with a 256-bit key. Second, least significant bit (LSB) embedding is carried out, by hiding the secret message into an image of an information matrix. A number of performance evaluation metrics are discussed and computed for the proposed scheme. The obtained results are compared to other schemes in literature and show the superiority of the proposed scheme.
Lal Senanayaka, Jagath Sri, Van Khang, Huynh, Robbersmyr, Kjell G..  2018.  Multiple Fault Diagnosis of Electric Powertrains Under Variable Speeds Using Convolutional Neural Networks. 2018 XIII International Conference on Electrical Machines (ICEM). :1900–1905.
Electric powertrains are widely used in automotive and renewable energy industries. Reliable diagnosis for defects in the critical components such as bearings, gears and stator windings, is important to prevent failures and enhance the system reliability and power availability. Most of existing fault diagnosis methods are based on specific characteristic frequencies to single faults at constant speed operations. Once multiple faults occur in the system, such a method may not detect the faults effectively and may give false alarms. Furthermore, variable speed operations render a challenge of analysing nonstationary signals. In this work, a deep learning-based fault diagnosis method is proposed to detect common faults in the electric powertrains. The proposed method is based on pattern recognition using convolutional neural network to detect effectively not only single faults at constant speed but also multiple faults in variable speed operations. The effectiveness of the proposed method is validated via an in-house experimental setup.
Wu, Lan, Su, Sheyan, Wen, Chenglin.  2018.  Multiple Fault Diagnosis Methods Based on Multilevel Multi-Granularity PCA. 2018 International Conference on Control, Automation and Information Sciences (ICCAIS). :566–570.
Principal Component Analysis (PCA) is a basic method of fault diagnosis based on multivariate statistical analysis. It utilizes the linear correlation between multiple process variables to implement process fault diagnosis and has been widely used. Traditional PCA fault diagnosis ignores the impact of faults with different magnitudes on detection accuracy. Based on a variety of data processing methods, this paper proposes a multi-level and multi-granularity principal component analysis method to make the detection results more accurate.
Filaretov, V., Kurganov, S., Gorshkov, K..  2017.  Multiple fault diagnosis in analog circuits using the indirect compensation theorem. 2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). :1–6.

A method for the multiple faults diagnosis in linear analog circuits is presented in this paper. The proposed approach is based upon the concept named by the indirect compensation theorem. This theorem is reducing the procedure of fault diagnosis in the analog circuit to the symbolic analysis process. An extension of the indirect compensation theorem for the linear subcircuit is proposed. The indirect compensation provides equivalent replacement of the n-ports subcircuit by n norators and n fixators of voltages and currents. The proposed multiple faults diagnosis techniques can be used for evaluation of any kind of terminal characteristics of the two-port network. For calculation of the circuit determinant expressions, the Generalized Parameter Extraction Method is implemented. The main advantage of the analysis method is that it is cancellation free. It requires neither matrix nor ordinary graph description of the circuit. The process of symbolic circuit analysis is automated by the freeware computer program Cirsym which can be used online. The experimental results are presented to show the efficiency and reliability of the proposed technique.

Han, Ying, Li, Kun, Ge, Fawei.  2019.  Multiple Fault Diagnosis for Sucker Rod Pumping Systems Based on Matter Element Analysis with F-statistics. 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS). :66–70.
Dynamometer cards can reflect different down-hole working conditions of sucker rod pumping wells. It has great significances to realize multiple fault diagnosis for actual oilfield production. In this paper, the extension theory is used to build a matter-element model to describe the fault diagnosis problem of the sucker rod pumping wells. The correlation function is used to calculate the correlation degree between the diagnostic fault and many standard fault types. The diagnosed sample and many possible fault types are divided into different combinations according to the correlation degree; the F-statistics of each combination is calculated and the “unbiased transformation” is used to find the mean of interval vectors. Larger F-statistics means greater differences within the faults classification; and the minimum F-statistics reflects the real multiple fault types. Case study shows the effectiveness of the proposed method.
Austin, Thomas H., Schmitz, Tommy, Flanagan, Cormac.  2017.  Multiple Facets for Dynamic Information Flow with Exceptions. ACM Trans. Program. Lang. Syst.. 39:10:1–10:56.
JavaScript is the source of many security problems, including cross-site scripting attacks and malicious advertising code. Central to these problems is the fact that code from untrusted sources runs with full privileges. Information flow controls help prevent violations of data confidentiality and integrity. This article explores faceted values, a mechanism for providing information flow security in a dynamic manner that avoids the stuck executions of some prior approaches, such as the no-sensitive-upgrade technique. Faceted values simultaneously simulate multiple executions for different security levels to guarantee termination-insensitive noninterference. We also explore the interaction of faceted values with exceptions, declassification, and clearance.
P. Das, S. C. Kushwaha, M. Chakraborty.  2015.  "Multiple embedding secret key image steganography using LSB substitution and Arnold Transform". 2015 2nd International Conference on Electronics and Communication Systems (ICECS). :845-849.

Cryptography and steganography are the two major fields available for data security. While cryptography is a technique in which the information is scrambled in an unintelligent gibberish fashion during transmission, steganography focuses on concealing the existence of the information. Combining both domains gives a higher level of security in which even if the use of covert channel is revealed, the true information will not be exposed. This paper focuses on concealing multiple secret images in a single 24-bit cover image using LSB substitution based image steganography. Each secret image is encrypted before hiding in the cover image using Arnold Transform. Results reveal that the proposed method successfully secures the high capacity data keeping the visual quality of transmitted image satisfactory.

Sun, Gangcan, Liu, Mengge, Han, Zhuo.  2018.  Multiple Eavesdropper-Based Physical Layer Security in TAS/MRC System With Antenna Correlation. Proceedings of the 8th International Conference on Communication and Network Security. :100–106.

In this paper, we analyze the impact of the antenna correlation on the secrecy of multiple-input multiple-output (MIMO) wiretap channels with multiple eavesdroppers, where transmit antenna selection (TAS) and maximal-ratio combining (MRC) are employed at the transmitter, receiver and eavesdroppers, respectively. For the practical passive eavesdropping, we first develop new and closed general formulas for the secrecy outage probability and the probability of non-zero secrecy capacity to characterize the effect of spatial correlation, and results prove that the enhanced security performance can be achieved when multiple antennas are provided at the transmitter. We then explore how spatial correlation affects the asymptotic secrecy outage probability, and the secrecy diversity order is revealed. Based on these, the results show that when the average SNR of the main channel is relatively low, higher antenna correlation is more perfect to the secrecy. When the average SNR of the main channel is relatively high, higher antenna correlation is more destructive to the secrecy.

Khan, JavedAkhtar.  2019.  —Multiple Cluster-Android lock Patterns (MALPs) for Smart Phone Authentication‖. 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC). :619–623.
This paper proposes the implementation of progressive authentication service in smart android mobile phone. In this digital era, massive amount of work can be done in the digital form using the smart devices like smart phone , laptop, Tablets, etc. The number of smartphone users approx. reach to 299.24 million, as per the recent survey report [1] in 2019 this count will reach 2.7 billion and after 3 years, this count will increase up to 442.5 million. This article includes a cluster based progressive smart lock with a dependent combination that is short and more secure in nature. Android provides smart lock facilities with the combination of 9 dot, 6dot, 5dot, 4dot and 1-9 number. By using this mobile phone user will be able to generate pattern lock or number password for authentication. This is a single authentication system, this research paper includes a more secured multiple cluster based pattern match system.
Xia, S., Li, N., Xiaofeng, T., Fang, C..  2018.  Multiple Attributes Based Spoofing Detection Using an Improved Clustering Algorithm in Mobile Edge Network. 2018 1st IEEE International Conference on Hot Information-Centric Networking (HotICN). :242–243.

Information centric network (ICN) based Mobile Edge Computing (MEC) network has drawn growing attentions in recent years. The distributed network architecture brings new security problems, especially the identity security problem. Because of the cloud platform deployed on the edge of the MEC network, multiple channel attributes can be easily obtained and processed. Thus this paper proposes a multiple channel attributes based spoofing detection mechanism. To further reduce the complexity, we also propose an improved clustering algorithm. The simulation results indicate that the proposed spoofing detection method can provide near-optimal performance with extremely low complexity.

Altamimi, Abdulaziz, Clarke, Nathan, Furnell, Steven, Li, Fudong.  2019.  Multi-Platform Authorship Verification. Proceedings of the Third Central European Cybersecurity Conference. :1–7.
At the present time, there has been a rapid increase in the variety and popularity of messaging systems such as social network messaging, text messages, email and Twitter, with users frequently exchanging messages across various platforms. Unfortunately, in amongst the legitimate messages, there is a host of illegitimate and inappropriate content - with cyber stalking, trolling and computerassisted crime all taking place. Therefore, there is a need to identify individuals using messaging systems. Stylometry is the study of linguistic features in a text which consists of verifying an author based on his writing style that consists of checking whether a target text was written or not by a specific individual author. Whilst much research has taken place within authorship verification, studies have focused upon singular platforms, often had limited datasets and restricted methodologies that have meant it is difficult to appreciate the real-world value of the approach. This paper seeks to overcome these limitations through providing an analysis of authorship verification across four common messaging systems. This approach enables a direct comparison of recognition performance and provides a basis for analyzing the feature vectors across platforms to better understand what aspects each capitalize upon in order to achieve good classification. The experiments also include an investigation into the feature vector creation, utilizing population and user-based techniques to compare and contrast performance. The experiment involved 50 participants across four common platforms with a total 13,617; 106,359; 4,539; and 6,540 samples for Twitter, SMS, Facebook, and Email achieving an Equal Error Rate (EER) of 20.16%, 7.97%, 25% and 13.11% respectively.
Miller, Sean T., Busby-Earle, Curtis.  2017.  Multi-Perspective Machine Learning a Classifier Ensemble Method for Intrusion Detection. Proceedings of the 2017 International Conference on Machine Learning and Soft Computing. :7–12.
Today cyber security is one of the most active fields of re- search due to its wide range of impact in business, govern- ment and everyday life. In recent years machine learning methods and algorithms have been quite successful in a num- ber of security areas. In this paper, we explore an approach to classify intrusion called multi-perspective machine learn- ing (MPML). For any given cyber-attack there are multiple methods of detection. Every method of detection is built on one or more network characteristic. These characteristics are then represented by a number of network features. The main idea behind MPML is that, by grouping features that support the same characteristics into feature subsets called perspectives, this will encourage diversity among perspectives (classifiers in the ensemble) and improve the accuracy of prediction. Initial results on the NSL- KDD dataset show at least a 4% improvement over other ensemble methods such as bagging boosting rotation forest and random for- est.
El-Din Abd El-Raouf, Karim Alaa, Bahaa-Eldin, Ayman M., Sobh, Mohamed A..  2019.  Multipath Traffic Engineering for Software Defined Networking. 2019 14th International Conference on Computer Engineering and Systems (ICCES). :132—136.

ASA systems (firewall, IDS, IPS) are probable to become communication bottlenecks in networks with growing network bandwidths. To alleviate this issue, we suggest to use Application-aware mechanism based on Deep Packet Inspection (DPI) to bypass chosen traffic around firewalls. The services of Internet video sharing gained importance and expanded their share of the multimedia market. The Internet video should meet strict service quality (QoS) criteria to make the broadcasting of broadcast television a viable and comparable level of quality. However, since the Internet video relies on packet communication, it is subject to delays, transmission failures, loss of data and bandwidth restrictions that may have a catastrophic effect on the quality of multimedia.

Peng, Qiuyu, Walid, Anwar, Hwang, Jaehyun, Low, Steven H..  2016.  Multipath TCP: Analysis, Design, and Implementation. IEEE/ACM Trans. Netw.. 24:596–609.

Multipath TCP (MP-TCP) has the potential to greatly improve application performance by using multiple paths transparently. We propose a fluid model for a large class of MP-TCP algorithms and identify design criteria that guarantee the existence, uniqueness, and stability of system equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss the implications of these properties on the behavior of existing algorithms and motivate our algorithm Balia (balanced linked adaptation), which generalizes existing algorithms and strikes a good balance among TCP-friendliness, responsiveness, and window oscillation. We have implemented Balia in the Linux kernel. We use our prototype to compare the new algorithm to existing MP-TCP algorithms.

Benjbara, Chaimae, Habbani, Ahmed, Mahdi, Fatna El, Essaid, Bilal.  2017.  Multi-path Routing Protocol in the Smart Digital Environment. Proceedings of the 2017 International Conference on Smart Digital Environment. :14–18.
During the last decade, the smart digital environment has become one of the most scientific challenges that occupy scientists and researchers. This new environment consists basically of smart connected products including three main parts: the physical mechanical/electrical product, the smart part of the product made from embedded software and human machine interface, and finally the connectivity part including antennas and routing protocols insuring the wired/wireless communication with other products, from our side, we are involved in the implementation of the latter part by developing a routing protocol that will meet the increasingly demanding requirements of today's systems (security, bandwidth, network lifetime, ...). Based on the researches carried out in other fields of application such as MANETS, multi-path routing fulfills our expectations. In this article, the MPOLSR protocol was chosen as an example, comparing its standard version and its improvements in order to choose the best solution that can be applied in the smart digital environment.
Seo, Bo-Min, Cho, Ho-Shin.  2016.  A Multipath Diversity Combining in Underwater CDMA System. Proceedings of the 11th ACM International Conference on Underwater Networks & Systems. :40:1–40:2.
In this study, we evaluate a multipath diversity reception in underwater CDMA system by performing a lake experiment. First, we design CDMA transmitter and receiver equipped with a multipath diversity with equal gain combining (EGC) and maximal ratio combining (MRC). Then, an experiment is performed at Lake Kyungcheon, South Korea to show that the diversity combining successfully corrects bit errors caused by multipath fading.
K. Sakai, M. T. Sun, W. S. Ku, J. Wu, T. H. Lai.  2015.  "Multi-path Based Avoidance Routing in Wireless Networks". 2015 IEEE 35th International Conference on Distributed Computing Systems. :706-715.

The speedy advancement in computer hardware has caused data encryption to no longer be a 100% safe solution for secure communications. To battle with adversaries, a countermeasure is to avoid message routing through certain insecure areas, e.g., Malicious countries and nodes. To this end, avoidance routing has been proposed over the past few years. However, the existing avoidance protocols are single-path-based, which means that there must be a safe path such that no adversary is in the proximity of the whole path. This condition is difficult to satisfy. As a result, routing opportunities based on the existing avoidance schemes are limited. To tackle this issue, we propose an avoidance routing framework, namely Multi-Path Avoidance Routing (MPAR). In our approach, a source node first encodes a message into k different pieces, and each piece is sent via k different paths. The destination can assemble the original message easily, while an adversary cannot recover the original message unless she obtains all the pieces. We prove that the coding scheme achieves perfect secrecy against eavesdropping under the condition that an adversary has incomplete information regarding the message. The simulation results validate that the proposed MPAR protocol achieves its design goals.

Chouzenoux, E., Pesquet, J.-C., Florescu, A..  2014.  A multi-parameter optimization approach for complex continuous sparse modelling. Digital Signal Processing (DSP), 2014 19th International Conference on. :817-820.

The main focus of this work is the estimation of a complex valued signal assumed to have a sparse representation in an uncountable dictionary of signals. The dictionary elements are parameterized by a real-valued vector and the available observations are corrupted with an additive noise. By applying a linearization technique, the original model is recast as a constrained sparse perturbed model. The problem of the computation of the involved multiple parameters is addressed from a nonconvex optimization viewpoint. A cost function is defined including an arbitrary Lipschitz differentiable data fidelity term accounting for the noise statistics, and an ℓ0-like penalty. A proximal algorithm is then employed to solve the resulting nonconvex and nonsmooth minimization problem. Experimental results illustrate the good practical performance of the proposed approach when applied to 2D spectrum analysis.

Sgambelluri, A., Dugeon, O., Sevilla, K., Ubaldi, F., Monti, P., De Dios, O. G., Paolucci, F..  2019.  Multi-Operator Orchestration of Connectivity Services Exploiting Stateful BRPC and BGP-LS in the 5GEx Sandbox. 2019 Optical Fiber Communications Conference and Exhibition (OFC). :1–3.
QoS-based connectivity coordinated by the 5GEx Multi-domain Orchestrator exploiting novel stateful BRPC is demonstrated for the first time over a multi-operator multi-technology transport network within the European 5GEx Sandbox, including Segment Routing and optical domains.
Janakiraman, Nithiyanantham, Nirmal Kumar, Palanisamy.  2014.  Multi-objective Module Partitioning Design for Dynamic and Partial Reconfigurable System-on-chip Using Genetic Algorithm. J. Syst. Archit.. 60:119–139.

This paper proposes a novel architecture for module partitioning problems in the process of dynamic and partial reconfigurable computing in VLSI design automation. This partitioning issue is deemed as Hypergraph replica. This can be treated by a probabilistic algorithm like the Markov chain through the transition probability matrices due to non-deterministic polynomial complete problems. This proposed technique has two levels of implementation methodology. In the first level, the combination of parallel processing of design elements and efficient pipelining techniques are used. The second level is based on the genetic algorithm optimization system architecture. This proposed methodology uses the hardware/software co-design and co-verification techniques. This architecture was verified by implementation within the MOLEN reconfigurable processor and tested on a Xilinx Virtex-5 based development board. This proposed multi-objective module partitioning design was experimentally evaluated using an ISPD’98 circuit partitioning benchmark suite. The efficiency and throughput were compared with that of the hMETIS recursive bisection partitioning approach. The results indicate that the proposed method can improve throughput and efficiency up to 39 times with only a small amount of increased design space. The proposed architecture style is sketched out and concisely discussed in this manuscript, and the existing results are compared and analyzed.

Wang, J., Zhou, Y..  2015.  Multi-objective dynamic unit commitment optimization for energy-saving and emission reduction with wind power. 2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT). :2074–2078.

As a clean energy, wind power is massively utilized in net recent years, which significantly reduced the pollution emission created from unit. This article referred to the concept of energy-saving and emission reducing; built a multiple objective function with represent of the emission of CO2& SO2, the coal-fired from units and the lowest unit fees of commitment; Proposed a algorithm to improving NSGA-D (Non-dominated Sorting Genetic Algorithm-II) for the dynamic characteristics, consider of some constraint conditions such as the shortest operation and fault time and climbing etc.; Optimized and commitment discrete magnitude and Load distribution continuous quantity with the double-optimization strategy; Introduced the fuzzy satisfaction-maximizing method to reaching a decision for Pareto solution and also nested into each dynamic solution; Through simulation for 10 units of wind power, the result show that this method is an effective way to optimize the Multi-objective unit commitment modeling in wind power integrated system with Mixed-integer variable.

Arrieta, Aitor, Wang, Shuai, Arruabarrena, Ainhoa, Markiegi, Urtzi, Sagardui, Goiuria, Etxeberria, Leire.  2018.  Multi-objective Black-box Test Case Selection for Cost-effectively Testing Simulation Models. Proceedings of the Genetic and Evolutionary Computation Conference. :1411–1418.
In many domains, engineers build simulation models (e.g., Simulink) before developing code to simulate the behavior of complex systems (e.g., Cyber-Physical Systems). Those models are commonly heavy to simulate which makes it difficult to execute the entire test suite. Furthermore, it is often difficult to measure white-box coverage of test cases when employing such models. In addition, the historical data related to failures might not be available. This paper proposes a cost-effective approach for test case selection that relies on black-box data related to inputs and outputs of the system. The approach defines in total five effectiveness measures and one cost measure followed by deriving in total 15 objective combinations and integrating them within Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). We empirically evaluated our approach with all these 15 combinations using four case studies by employing mutation testing to assess the fault revealing capability. The results demonstrated that our approach managed to improve Random Search by 26% on average in terms of the Hypervolume quality indicator.