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Leong, P., Liming Lu.  2014.  Multiagent Web for the Internet of Things. Information Science and Applications (ICISA), 2014 International Conference on. :1-4.

The Internet of Things (IOT) is a network of networks where massively large numbers of objects or things are interconnected to each other through the network. The Internet of Things brings along many new possibilities of applications to improve human comfort and quality of life. Complex systems such as the Internet of Things are difficult to manage because of the emergent behaviours that arise from the complex interactions between its constituent parts. Our key contribution in the paper is a proposed multiagent web for the Internet of Things. Corresponding data management architecture is also proposed. The multiagent architecture provides autonomic characteristics for IOT making the IOT manageable. In addition, the multiagent web allows for flexible processing on heterogeneous platforms as we leverage off web protocols such as HTTP and language independent data formats such as JSON for communications between agents. The architecture we proposed enables a scalable architecture and infrastructure for a web-scale multiagent Internet of Things.
 

de Oliveira Saraiva, F., Nobuhiro Asada, E..  2014.  Multi-agent systems applied to topological reconfiguration of smart power distribution systems. Neural Networks (IJCNN), 2014 International Joint Conference on. :2812-2819.

One of the various features expected for a smart power distribution system - a smart grid in the power distribution level - is the possibility of the fully automated operation for certain control actions. Although this is very expected, it requires various logic, sensor and actuator technologies in a system which, historically, has a low level of automation. One of the most analyzed problems for the distribution system is the topology reconfiguration. The reconfiguration has been applied to various objectives: minimization of power losses, voltage regulation, load balancing, to name a few. The solution method in most cases is centralized and its application is not in real-time. From the new perspectives of advanced distribution systems, fast and adaptive response of the control actions are required, specially in the presence of alternative generation sources and electrical vehicles. In this context, the multi-agent system, which embeds the necessary control actions and decision making is proposed for the topology reconfiguration aiming the loss reduction. The concept of multi-agent system for distribution system is proposed and two case studies with 11-Bus and 16-Bus system are presented.
 

Amullen, Esther, Lin, Hui, Kalbarczyk, Zbigniew, Keel, Lee.  2016.  Multi-agent System for Detecting False Data Injection Attacks Against the Power Grid. Proceedings of the 2Nd Annual Industrial Control System Security Workshop. :38–44.

A class of cyber-attacks called False Data Injection attacks that target measurement data used for state estimation in the power grid are currently under study by the research community. These attacks modify sensor readings obtained from meters with the aim of misleading the control center into taking ill-advised response action. It has been shown that an attacker with knowledge of the network topology can craft an attack that bypasses existing bad data detection schemes (largely based on residual generation) employed in the power grid. We propose a multi-agent system for detecting false data injection attacks against state estimation. The multi-agent system is composed of software implemented agents created for each substation. The agents facilitate the exchange of information including measurement data and state variables among substations. We demonstrate that the information exchanged among substations, even untrusted, enables agents cooperatively detect disparities between local state variables at the substation and global state variables computed by the state estimator. We show that a false data injection attack that passes bad data detection for the entire system does not pass bad data detection for each agent.

Azaiez, Meriem, Chainbi, Walid.  2016.  A Multi-agent System Architecture for Self-Healing Cloud Infrastructure. Proceedings of the International Conference on Internet of Things and Cloud Computing. :7:1–7:6.

The popularity of Cloud computing has considerably increased during the last years. The increase of Cloud users and their interactions with the Cloud infrastructure raise the risk of resources faults. Such a problem can lead to a bad reputation of the Cloud environment which slows down the evolution of this technology. To address this issue, the dynamic and the complex architecture of the Cloud should be taken into account. Indeed, this architecture requires that resources protection and healing must be transparent and without external intervention. Unlike previous work, we suggest integrating the fundamental aspects of autonomic computing in the Cloud to deal with the self-healing of Cloud resources. Starting from the high degree of match between autonomic computing systems and multiagent systems, we propose to take advantage from the autonomous behaviour of agent technology to create an intelligent Cloud that supports autonomic aspects. Our proposed solution is a multi-agent system which interacts with the Cloud infrastructure to analyze the resources state and execute Checkpoint/Replication strategy or migration technique to solve the problem of failed resources.

Wang, Shaoyang, Lv, Tiejun, Zhang, Xuewei.  2019.  Multi-Agent Reinforcement Learning-Based User Pairing in Multi-Carrier NOMA Systems. 2019 IEEE International Conference on Communications Workshops (ICC Workshops). :1–6.
This paper investigates the problem of user pairing in multi-carrier non-orthogonal multiple access (MC-NOMA) systems. Firstly, the hard channel capacity and soft channel capacity are presented. The former depicts the transmission capability of the system that depends on the channel conditions, and the latter refers to the effective throughput of the system that is determined by the actual user demands. Then, two optimization problems to maximize the hard and soft channel capacities are established, respectively. Inspired by the multiagent deep reinforcement learning (MADRL) and convolutional neural network, the user paring network (UP-Net), based on the cooperative game and deep deterministic policy gradient, is designed for solving the optimization problems. Simulation results demonstrate that the performance of the designed UP-Net is comparable to that obtained from the exhaustive search method via the end-to-end low complexity method, which is superior to the common method, and corroborate that the UP-Net focuses more on the actual user demands to improve the soft channel capacity. Additionally and more importantly, the paper makes a useful exploration on the use of MADRL to solve the resource allocation problems in communication systems. Meanwhile, the design method has strong universality and can be easily extended to other issues.
OUIAZZANE, Said, ADDOU, Malika, BARRAMOU, Fatimazahra.  2019.  A Multi-Agent Model for Network Intrusion Detection. 2019 1st International Conference on Smart Systems and Data Science (ICSSD). :1–5.
The objective of this paper is to propose a distributed intrusion detection model based on a multi agent system. Mutli Agent Systems (MAS) are very suitable for intrusion detection systems as they meet the characteristics required by the networks and Big Data issues. The MAS agents cooperate and communicate with each other to ensure the effective detection of network intrusions without the intervention of an expert as used to be in the classical intrusion detection systems relying on signature matching to detect known attacks. The proposed model helped to detect known and unknown attacks within big computer infrastructure by responding to the network requirements in terms of distribution, autonomy, responsiveness and communication. The proposed model is capable of achieving a good and a real time intrusion detection using multi-agents paradigm and Hadoop Distributed File System (HDFS).
Januário, F., Cardoso, A., Gil, P..  2019.  A Multi-Agent Middleware for Resilience Enhancement in Heterogeneous Control Systems. 2019 IEEE International Conference on Industrial Technology (ICIT). :988–993.
Modern computing networks that enable distributed computing are comprised of a wide range of heterogeneous devices with different levels of resources, which are interconnected by different networking technologies and communication protocols. This integration, together with the state of the art technologies, has brought into play new uncertainties, associated with physical world and the cyber space. In heterogeneous networked control systems environments, awareness and resilience are two important properties that these systems should bear and comply with. In this work the problem of resilience enhancement in heterogeneous networked control systems is addressed based on a distributed middleware, which is propped up on a hierarchical multi-agent framework, where each of the constituent agents is devoted to a specific task. The proposed architecture takes into account physical and cyber vulnerabilities and ensures state and context awareness, and a minimum level of acceptable operational performance, in response to physical and cyber disturbances. Experiments on a IPv6-based test-bed proved the relevance and benefits offered by the proposed architecture.
Januário, Fábio, Cardoso, Alberto, Gil, Paulo.  2017.  A Multi-Agent Framework for Resilient Enhancement in Networked Control Systems. Proceedings of the 9th International Conference on Computer and Automation Engineering. :291–295.
Recent advances on the integration of control systems with state of the art information technologies have brought into play new uncertainties, not only associated with the physical world, but also from a cyber-space's perspective. In cyber-physical environments, awareness and resilience are invaluable properties. The paper focuses on the development of an architecture relying on a hierarchical multi-agent framework for resilience enhancement. This framework was evaluated on a test-bed comprising several distributed computational devices and heterogeneous communications. Results from tests prove the relevance of the proposed approach.
Januário, F., Cardoso, A., Gil, P..  2018.  Multi-Agent Framework for Resilience Enhancement over a WSAN. 2018 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). :110–113.
Advances on the integration of wireless sensor and actuator networks, as a whole, have contribute to the greater reconfigurability of systems and lower installation costs with application to supervision of networked control systems. This integration, however, increases some vulnerabilities associated with the physical world and also with the cyber and security world. This trend makes the wireless nodes one of the most vulnerable component of these kind of systems, which can have a major impact on the overall performance of the networked control system. This paper presents an architecture relying on a hierarchical multi-agent system for resilience enhancement, with focus on wireless sensor and actuator networks. The proposed framework was evaluated on an IPv6 test-bed comprising several distributed devices, where performance and communication links health are analyzed. The relevance of the proposed approach is demonstrated by results collected from the test-bed.
Sharma, V..  2017.  Multi-agent based intrusion prevention and mitigation architecture for software defined networks. 2017 International Conference on Information and Communication Technology Convergence (ICTC). :686–692.

Software Defined Networking (SDN) has proved to be a promising approach for creating next generation software based network ecosystems. It has provided us with a centralized network provision, a holistic management plane and a well-defined level of abstraction. But, at the same time brings forth new security and management challenges. Research in the field of SDN is primarily focused on reconfiguration, forwarding and network management issues. However in recent times the interest has moved to tackling security and maintenance issues. This work is based on providing a means to mitigate security challenges in an SDN environment from a DDoS attack based point of view. This paper introduces a Multi-Agent based intrusion prevention and mitigation architecture for SDN. Thus allowing networks to govern their behavior and take appropriate measures when the network is under attack. The architecture is evaluated against filter based intrusion prevention architectures to measure efficiency and resilience against DDoS attacks and false policy based attacks.

Xiong, X., Yang, L..  2017.  Multi End-Hopping Modeling and Optimization Using Cooperative Game. 2017 4th International Conference on Information Science and Control Engineering (ICISCE). :470–474.

End-hopping is an effective component of Moving Target Defense (MTD) by randomly hopping network configuration of host, which is a game changing technique against cyber-attack and can interrupt cyber kill chain in the early stage. In this paper, a novel end-hopping model, Multi End-hopping (MEH), is proposed to exploit the full potentials of MTD techniques by hosts cooperating with others to share possible configurable space (PCS). And an optimization method based on cooperative game is presented to make hosts form optimal alliances against reconnaissance, scanning and blind probing DoS attack. Those model and method confuse adversaries by establishing alliances of hosts to enlarge their PCS, which thwarts various malicious scanning and mitigates probing DoS attack intensity. Through simulations, we validate the correctness of MEH model and the effectiveness of optimization method. Experiment results show that the proposed model and method increase system stable operational probability while introduces a low overhead in optimization.

Rashid, N. A. M., Zukri, N. H. A., Zulkifli, Z. A., Awang, N., Buja, A. G..  2020.  A Multi Agent-Based Security Protocol for Securing Password Management Application. 2020 10th IEEE International Conference on Control System, Computing and Engineering (ICCSCE). :42—45.
Password-based authentication is the most common authentication method for either online or offline system. Password composition policies become too burdensome and put the user in a state of struggle to remember their password. Thus, most of the user save their password on the browser or even list it down in their personal gadgets. Therefore, a multi agent-based password management application have been developed to helps user in keeping their password safely. However, multi-agent system facing security issues such as man in the middle attack, data modification and eavesdropping. This paper proposed a security protocol for multi agent-based architecture in order to reduce potential threats. The security protocol focuess on the authentication of mobile agents, data transmission and the data local protection. The communication channels are secured using cryptography techniques.
Amani, Sven, Nadi, Sarah, Nguyen, Hoan A., Nguyen, Tien N., Mezini, Mira.  2016.  MUBench: A Benchmark for API-misuse Detectors. Proceedings of the 13th International Conference on Mining Software Repositories. :464–467.

Over the last few years, researchers proposed a multitude of automated bug-detection approaches that mine a class of bugs that we call API misuses. Evaluations on a variety of software products show both the omnipresence of such misuses and the ability of the approaches to detect them. This work presents MuBench, a dataset of 89 API misuses that we collected from 33 real-world projects and a survey. With the dataset we empirically analyze the prevalence of API misuses compared to other types of bugs, finding that they are rare, but almost always cause crashes. Furthermore, we discuss how to use it to benchmark and compare API-misuse detectors.

Chowdhary, Ankur, Alshamrani, Adel, Huang, Dijiang, Liang, Hongbin.  2018.  MTD Analysis and Evaluation Framework in Software Defined Network (MASON). Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization. :43–48.
Security issues in a Software Defined Network (SDN) environment like system vulnerabilities and intrusion attempts can pose a security risk for multi-tenant network managed by SDN. In this research work, Moving target defense (MTD)technique based on shuffle strategy - port hopping has been employed to increase the difficulty for the attacker trying to exploit the cloud network. Our research workMASON, considers the problem of multi-stage attacks in a network managed using SDN. SDN controller can be used to dynamically reconfigure the network and render attacker»s knowledge in multi-stage attacks redundant. We have used a threat score based on vulnerability information and intrusion attempts to identify Virtual Machines (VMs) in systems with high-security risk and implement MTD countermeasures port hopping to assess threat score reduction in a cloud network.
Shahriar, M. R., Sunny, S. M. N. A., Liu, X., Leu, M. C., Hu, L., Nguyen, N..  2018.  MTComm Based Virtualization and Integration of Physical Machine Operations with Digital-Twins in Cyber-Physical Manufacturing Cloud. 2018 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom). :46—51.

Digital-Twins simulate physical world objects by creating 'as-is' virtual images in a cyberspace. In order to create a well synchronized digital-twin simulator in manufacturing, information and activities of a physical machine need to be virtualized. Many existing digital-twins stream read-only data of machine sensors and do not incorporate operations of manufacturing machines through Internet. In this paper, a new method of virtualization is proposed to integrate machining data and operations into the digital-twins using Internet scale machine tool communication method. A fully functional digital-twin is implemented in CPMC testbed using MTComm and several manufacturing application scenarios are developed to evaluate the proposed method and system. Performance analysis shows that it is capable of providing data-driven visual monitoring of a manufacturing process and performing manufacturing operations through digital twins over the Internet. Results of the experiments also shows that the MTComm based digital twins have an excellent efficiency.

Guoyuan Lin, Danru Wang, Yuyu Bie, Min Lei.  2014.  MTBAC: A mutual trust based access control model in Cloud computing. Communications, China. 11:154-162.

As a new computing mode, cloud computing can provide users with virtualized and scalable web services, which faced with serious security challenges, however. Access control is one of the most important measures to ensure the security of cloud computing. But applying traditional access control model into the Cloud directly could not solve the uncertainty and vulnerability caused by the open conditions of cloud computing. In cloud computing environment, only when the security and reliability of both interaction parties are ensured, data security can be effectively guaranteed during interactions between users and the Cloud. Therefore, building a mutual trust relationship between users and cloud platform is the key to implement new kinds of access control method in cloud computing environment. Combining with Trust Management(TM), a mutual trust based access control (MTBAC) model is proposed in this paper. MTBAC model take both user's behavior trust and cloud services node's credibility into consideration. Trust relationships between users and cloud service nodes are established by mutual trust mechanism. Security problems of access control are solved by implementing MTBAC model into cloud computing environment. Simulation experiments show that MTBAC model can guarantee the interaction between users and cloud service nodes.

Gevargizian, J., Kulkarni, P..  2018.  MSRR: Measurement Framework For Remote Attestation. 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). :748–753.
Measurers are critical to a remote attestation (RA) system to verify the integrity of a remote untrusted host. Run-time measurers in a dynamic RA system sample the dynamic program state of the host to form evidence in order to establish trust by a remote system (appraiser). However, existing run-time measurers are tightly integrated with specific software. Such measurers need to be generated anew for each software, which is a manual process that is both challenging and tedious. In this paper we present a novel approach to decouple application-specific measurement policies from the measurers tasked with performing the actual run-time measurement. We describe MSRR (MeaSeReR), a novel general-purpose measurement framework that is agnostic of the target application. We show how measurement policies written per application can use MSRR, eliminating much time and effort spent on reproducing core measurement functionality. We describe MSRR's robust querying language, which allows the appraiser to accurately specify the what, when, and how to measure. We evaluate MSRR's overhead and demonstrate its functionality.
Zhang, Zhenning, Zhao, Baokang, Feng, Zhenqian, Yu, Wanrong, Wu, Chunqing.  2016.  MSN: A Mobility-enhanced Satellite Network Architecture: Poster. Proceedings of the 22Nd Annual International Conference on Mobile Computing and Networking. :465–466.

The proposed MSN architecture is intended to directly address the challenge of mobility, which refers to the motion of users as well as the dynamics of the satellite constellation. A virtual access point layer consisting of fixed virtual satellite network attachment points is superimposed over the physical topology in order to hide the mobility of satellites from the mobile endpoints. Then the MSN enhances endpoint mobility by a clean separation of identity and logical network location through an identity-to-location resolution service, and taking full advantage of the user's geographical location information. Moreover, a SDN based implementation is presented to further illustrate the proposal.

Dilshan, D., Piumika, S., Rupasinghe, C., Perera, I., Siriwardena, P..  2020.  MSChain: Blockchain based Decentralized Certificate Transparency for Microservices. 2020 Moratuwa Engineering Research Conference (MERCon). :1–6.
Microservices architecture has become one of the most prominent software architectures in the software development processes due to its features such as scalability, maintainability, resilience, and composability. It allows developing business applications in a decentralized manner by dividing the important business logic into separate independent services. Digital certificates are used to verify the identity of microservices in most cases. However, the certificate authorities (CA) who issue the certificates to microservices cannot be trusted always since they can issue certificates without the consent of the relevant microservice. Nevertheless, existing implementations of certificate transparency are mostly centralized and has the vulnerability of the single point of failure. The distributed ledger technologies such as blockchain can be used to achieve decentralized nature in certificate transparency implementations. A blockchain-based decentralized certificate transparency system specified for microservices architecture is proposed in this paper to ensure secure communication among services. After the implementation and deployment in a cloud service, the system expressed average certificate querying time of 643 milliseconds along with the highly secured service provided.
Nagaratna, M., Sowmya, Y..  2017.  M-sanit: Computing misusability score and effective sanitization of big data using Amazon elastic MapReduce. 2017 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC). :029–035.
The invent of distributed programming frameworks like Hadoop paved way for processing voluminous data known as big data. Due to exponential growth of data, enterprises started to exploit the availability of cloud infrastructure for storing and processing big data. Insider attacks on outsourced data causes leakage of sensitive data. Therefore, it is essential to sanitize data so as to preserve privacy or non-disclosure of sensitive data. Privacy Preserving Data Publishing (PPDP) and Privacy Preserving Data Mining (PPDM) are the areas in which data sanitization plays a vital role in preserving privacy. The existing anonymization techniques for MapReduce programming can be improved to have a misusability measure for determining the level of sanitization to be applied to big data. To overcome this limitation we proposed a framework known as M-Sanit which has mechanisms to exploit misusability score of big data prior to performing sanitization using MapReduce programming paradigm. Our empirical study using the real world cloud eco system such as Amazon Elastic Cloud Compute (EC2) and Amazon Elastic MapReduce (EMR) reveals the effectiveness of misusability score based sanitization of big data prior to publishing or mining it.
Yun Shen, Thonnard, O..  2014.  MR-TRIAGE: Scalable multi-criteria clustering for big data security intelligence applications. Big Data (Big Data), 2014 IEEE International Conference on. :627-635.

Security companies have recently realised that mining massive amounts of security data can help generate actionable intelligence and improve their understanding of Internet attacks. In particular, attack attribution and situational understanding are considered critical aspects to effectively deal with emerging, increasingly sophisticated Internet attacks. This requires highly scalable analysis tools to help analysts classify, correlate and prioritise security events, depending on their likely impact and threat level. However, this security data mining process typically involves a considerable amount of features interacting in a non-obvious way, which makes it inherently complex. To deal with this challenge, we introduce MR-TRIAGE, a set of distributed algorithms built on MapReduce that can perform scalable multi-criteria data clustering on large security data sets and identify complex relationships hidden in massive datasets. The MR-TRIAGE workflow is made of a scalable data summarisation, followed by scalable graph clustering algorithms in which we integrate multi-criteria evaluation techniques. Theoretical computational complexity of the proposed parallel algorithms are discussed and analysed. The experimental results demonstrate that the algorithms can scale well and efficiently process large security datasets on commodity hardware. Our approach can effectively cluster any type of security events (e.g., spam emails, spear-phishing attacks, etc) that are sharing at least some commonalities among a number of predefined features.
 

Holmes, Daniel, Mohror, Kathryn, Grant, Ryan E., Skjellum, Anthony, Schulz, Martin, Bland, Wesley, Squyres, Jeffrey M..  2016.  MPI Sessions: Leveraging Runtime Infrastructure to Increase Scalability of Applications at Exascale. Proceedings of the 23rd European MPI Users' Group Meeting. :121–129.

MPI includes all processes in MPI\_COMM\_WORLD; this is untenable for reasons of scale, resiliency, and overhead. This paper offers a new approach, extending MPI with a new concept called Sessions, which makes two key contributions: a tighter integration with the underlying runtime system; and a scalable route to communication groups. This is a fundamental change in how we organise and address MPI processes that removes well-known scalability barriers by no longer requiring the global communicator MPI\_COMM\_WORLD.

Ramirez, Anthony, Fernandez, Alfredo.  2016.  MP4 Steganography: Analyzing and Detecting TCSteg. Proceedings of the 5th Annual Conference on Research in Information Technology. :2–6.

The MP4 files has become to most used video media file available, and will mostly likely remain at the top for some time to come. This makes MP4 files an interesting candidate for steganography. With its size and structure, it offers a challenge to steganography developers. While some attempts have been made to create a truly covert file, few are as successful as Martin Fiedler's TCSteg. TCSteg allows users to hide a TrueCrypt hidden volume in an MP4 file. The structure of the file makes it difficult to identify that a volume exists. In our analysis of TCSteg, we will show how Fielder's code works and how we may be able to detect the existence of steganography. We will then implement these methods in hope that other steganography analysis can use them to determine if an MP4 file is a carrier file. Finally, we will address the future of MP4 steganography.