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Prakash, A., Priyadarshini, R..  2018.  An Intelligent Software defined Network Controller for preventing Distributed Denial of Service Attack. 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT). :585–589.

Software Defined Network (SDN) architecture is a new and novel way of network management mechanism. In SDN, switches do not process the incoming packets like conventional network computing environment. They match for the incoming packets in the forwarding tables and if there is none it will be sent to the controller for processing which is the operating system of the SDN. A Distributed Denial of Service (DDoS) attack is a biggest threat to cyber security in SDN network. The attack will occur at the network layer or the application layer of the compromised systems that are connected to the network. In this paper a machine learning based intelligent method is proposed which can detect the incoming packets as infected or not. The different machine learning algorithms adopted for accomplishing the task are Naive Bayes, K-Nearest neighbor (KNN) and Support vector machine (SVM) to detect the anomalous behavior of the data traffic. These three algorithms are compared according to their performances and KNN is found to be the suitable one over other two. The performance measure is taken here is the detection rate of infected packets.

Polyakov, V. V., Lapin, S. A..  2018.  Architecture of the Honeypot System for Studying Targeted Attacks. 2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE). :202-205.
Among the threats to information systems of state institutions, enterprises and financial organizations of particular importance are those originating from organized criminal groups that specialize in obtaining unauthorized access to the computer information protected by law. Criminal groups often possess a material base including financial, technical, human and other resources that allow to perform targeted attacks on information resources as secretly as possible. The principal features of such targeted attacks are the use of software created or modified specifically for use in illegal purposes with respect to specific organizations. Due to these circumstances, the detection of such attacks is quite difficult, and their prevention is even more complicated. In this regard, the task of identifying and analyzing such threats is very relevant. One effective way to solve it is to implement the Honeypot system, which allows to research the strategy and tactics of the attackers. In the present article, there is proposed the original architecture of the Honeypot system designed to study targeted attacks on information systems of criminogenic objects. The architectural design includes such basic elements as the functional component, the registrar of events occurring in the system and the protector. The key features of the proposed Honeypot system are considered, and the functional purpose of its main components is described. The proposed system can find its application in providing information security of institutions, organizations and enterprises, it can be used in the development of information security systems.
Ioini, N. E., Pahl, C..  2018.  Trustworthy Orchestration of Container Based Edge Computing Using Permissioned Blockchain. 2018 Fifth International Conference on Internet of Things: Systems, Management and Security. :147-154.

The need to process the verity, volume and velocity of data generated by today's Internet of Things (IoT) devices has pushed both academia and the industry to investigate new architectural alternatives to support the new challenges. As a result, Edge Computing (EC) has emerged to address these issues, by placing part of the cloud resources (e.g., computation, storage, logic) closer to the edge of the network, which allows faster and context dependent data analysis and storage. However, as EC infrastructures grow, different providers who do not necessarily trust each other need to collaborate in order serve different IoT devices. In this context, EC infrastructures, IoT devices and the data transiting the network all need to be subject to identity and provenance checks, in order to increase trust and accountability. Each device/data in the network needs to be identified and the provenance of its actions needs to be tracked. In this paper, we propose a blockchain container based architecture that implements the W3C-PROV Data Model, to track identities and provenance of all orchestration decisions of a business network. This architecture provides new forms of interaction between the different stakeholders, which supports trustworthy transactions and leads to a new decentralized interaction model for IoT based applications.

Quaum, M. A., Haider, S. Uddin, Haque, M. M..  2018.  An Improved Asymmetric Key Based Security Architecture for WSN. 2018 International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2). :1-5.

Ubiquitous Healthcare System (U-Healthcare) is a well-known application of wireless sensor networking (WSN). In this system, the sensors take less power for operating the function. As the data transfers between sensor and other stations is sensitive so there needs to provide a security scheme. Due to the low life of sensor nodes in Wireless Sensor Networks (WSN), asymmetric key based security (AKS) architecture is always considered as unsuitable for these types of networks. Several papers have been published in recent past years regarding how to incorporate AKS in WSN, Haque et al's Asymmetric key based Architecture (AKA) is one of them. But later it is found that this system has authentication problem and therefore prone to man-in-the-middle (MITM) attack, furthermore it is not a truly asymmetric based scheme. We address these issues in this paper and proposed a complete asymmetric approach using PEKS-PM (proposed by Pham in [8]) to remove impersonation attack. We also found some other vulnerabilities in the original AKA system and proposed solutions, therefore making it a better and enhanced asymmetric key based architecture.

Aloui, M., Elbiaze, H., Glitho, R., Yangui, S..  2018.  Analytics as a service architecture for cloud-based CDN: Case of video popularity prediction. 2018 15th IEEE Annual Consumer Communications Networking Conference (CCNC). :1–4.
User Generated Videos (UGV) are the dominating content stored in scattered caches to meet end-user Content Delivery Networks (CDN) requests with quality of service. End-User behaviour leads to a highly variable UGV popularity. This aspect can be exploited to efficiently utilize the limited storage of the caches, and improve the hit ratio of UGVs. In this paper, we propose a new architecture for Data Analytics in Cloud-based CDN to derive UGVs popularity online. This architecture uses RESTful web services to gather CDN logs, store them through generic collections in a NoSQL database, and calculate related popular UGVs in a real time fashion. It uses a dynamic model training and prediction services to provide each CDN with related popular videos to be cached based on the latest trained model. The proposed architecture is implemented with k-means clustering prediction model and the obtained results are 99.8% accurate.
Castiglione, A., Choo, K. Raymond, Nappi, M., Ricciardi, S..  2017.  Context Aware Ubiquitous Biometrics in Edge of Military Things. IEEE Cloud Computing. 4:16–20.

Edge computing can potentially play a crucial role in enabling user authentication and monitoring through context-aware biometrics in military/battlefield applications. For example, in Internet of Military Things (IoMT) or Internet of Battlefield Things (IoBT),an increasing number of ubiquitous sensing and computing devices worn by military personnel and embedded within military equipment (combat suit, instrumented helmets, weapon systems, etc.) are capable of acquiring a variety of static and dynamic biometrics (e.g., face, iris, periocular, fingerprints, heart-rate, gait, gestures, and facial expressions). Such devices may also be capable of collecting operational context data. These data collectively can be used to perform context-adaptive authentication in-the-wild and continuous monitoring of soldier's psychophysical condition in a dedicated edge computing architecture.

Wang, Y., Ren, Z., Zhang, H., Hou, X., Xiao, Y..  2018.  “Combat Cloud-Fog” Network Architecture for Internet of Battlefield Things and Load Balancing Technology. 2018 IEEE International Conference on Smart Internet of Things (SmartIoT). :263–268.

Recently, the armed forces want to bring the Internet of Things technology to improve the effectiveness of military operations in battlefield. So the Internet of Battlefield Things (IoBT) has entered our view. And due to the high processing latency and low reliability of the “combat cloud” network for IoBT in the battlefield environment, in this paper , a novel “combat cloud-fog” network architecture for IoBT is proposed. The novel architecture adds a fog computing layer which consists of edge network equipment close to the users in the “combat-cloud” network to reduce latency and enhance reliability. Meanwhile, since the computing capability of the fog equipment are weak, it is necessary to implement distributed computing in the “combat cloud-fog” architecture. Therefore, the distributed computing load balancing problem of the fog computing layer is researched. Moreover, a distributed generalized diffusion strategy is proposed to decrease latency and enhance the stability and survivability of the “combat cloud-fog” network system. The simulation result indicates that the load balancing strategy based on generalized diffusion algorithm could decrease the task response latency and support the efficient processing of battlefield information effectively, which is suitable for the “combat cloud- fog” network architecture.

Wang, X., Oxholm, G., Zhang, D., Wang, Y..  2017.  Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). :7178–7186.
Transferring artistic styles onto everyday photographs has become an extremely popular task in both academia and industry. Recently, offline training has replaced online iterative optimization, enabling nearly real-time stylization. When those stylization networks are applied directly to high-resolution images, however, the style of localized regions often appears less similar to the desired artistic style. This is because the transfer process fails to capture small, intricate textures and maintain correct texture scales of the artworks. Here we propose a multimodal convolutional neural network that takes into consideration faithful representations of both color and luminance channels, and performs stylization hierarchically with multiple losses of increasing scales. Compared to state-of-the-art networks, our network can also perform style transfer in nearly real-time by performing much more sophisticated training offline. By properly handling style and texture cues at multiple scales using several modalities, we can transfer not just large-scale, obvious style cues but also subtle, exquisite ones. That is, our scheme can generate results that are visually pleasing and more similar to multiple desired artistic styles with color and texture cues at multiple scales.
Li, J., Hua, C..  2017.  RaptorQ code based concurrent transmissions in dual connectivity LTE network. 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP). :1–6.

Dual Connectivity(DC) is one of the key technologies standardized in Release 12 of the 3GPP specifications for the Long Term Evolution (LTE) network. It attempts to increase the per-user throughput by allowing the user equipment (UE) to maintain connections with the MeNB (master eNB) and SeNB (secondary eNB) simultaneously, which are inter-connected via non-ideal backhaul. In this paper, we focus on one of the use cases of DC whereby the downlink U-plane data is split at the MeNB and transmitted to the UE via the associated MeNB and SeNB concurrently. In this case, out-of-order packet delivery problem may occur at the UE due to the delay over the non-ideal backhaul link, as well as the dynamics of channel conditions over the MeNB-UE and SeNB-UE links, which will introduce extra delay for re-ordering the packets. As a solution, we propose to adopt the RaptorQ FEC code to encode the source data at the MeNB, and then the encoded symbols are separately transmitted through the MeNB and SeNB. The out-of-order problem can be effectively eliminated since the UE can decode the original data as long as it receives enough encoded symbols from either the MeNB or SeNB. We present detailed protocol design for the RaptorQ code based concurrent transmission scheme, and simulation results are provided to illustrate the performance of the proposed scheme.

Paharia, B., Bhushan, K..  2018.  Fog Computing as a Defensive Approach Against Distributed Denial of Service (DDoS): A Proposed Architecture. 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–7.
Cloud computing is a long-established technique which deals with storage and processing of information. In cloud computing, any user is liable to pay and demand according to its particular needs. Due to various limitations of cloud computing like higher latency and more bandwidth consumptions for transmitted information, the origination of Fog computing was essential. Fog computing inherits all the advantages of cloud computing, and also brings computing at the network's edge. In addition, security is a very serious concern for cloud computing. In this paper, fog computing is used as a defensive approach from the day-to-day increasing security threats particularly DDoS attacks in cloud computing. Here an architecture has been proposed to obstruct the malicious traffic generated by the DDoS attack from user to the cloud by utilizing the benefits of fog computing. Fog functions as a filtering layer for the traffic generated and is placed between user and cloud. This paper primarily works to improve the overall performance of the network and enhances reduction in the traffic forwarded to the cloud.
Tiwari, V., Chaurasia, B. K..  2017.  Security issues in fog computing using vehicular cloud. 2017 International Conference on Information, Communication, Instrumentation and Control (ICICIC). :1–4.

In the near future, vehicular cloud will help to improve traffic safety and efficiency. Unfortunately, a computing of vehicular cloud and fog cloud faced a set of challenges in security, authentication, privacy, confidentiality and detection of misbehaving vehicles. In addition to, there is a need to recognize false messages from received messages in VANETs during moving on the road. In this work, the security issues and challenges for computing in the vehicular cloud over for computing is studied.

Imine, Y., Kouicem, D. E., Bouabdallah, A., Ahmed, L..  2018.  MASFOG: An Efficient Mutual Authentication Scheme for Fog Computing Architecture. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :608–613.

Fog computing is a new paradigm which extends cloud computing services into the edge of the network. Indeed, it aims to pool edge resources in order to deal with cloud's shortcomings such as latency problems. However, this proposal does not ensure the honesty and the good behavior of edge devices. Thus, security places itself as an important challenge in front of this new proposal. Authentication is the entry point of any security system, which makes it an important security service. Traditional authentication schemes endure latency issues and some of them do not satisfy fog-computing requirements such as mutual authentication between end devices and fog servers. Thus, new authentication protocols need to be implemented. In this paper, we propose a new efficient authentication scheme for fog computing architecture. Our scheme ensures mutual authentication and remedies to fog servers' misbehaviors. Moreover, fog servers need to hold only a couple of information to verify the authenticity of every user in the system. Thus, it provides a low overhead in terms of storage capacity. Finally, we show through experimentation the efficiency of our scheme.

Abubaker, N., Dervishi, L., Ayday, E..  2017.  Privacy-preserving fog computing paradigm. 2017 IEEE Conference on Communications and Network Security (CNS). :502–509.

As an extension of cloud computing, fog computing is proving itself more and more potentially useful nowadays. Fog computing is introduced to overcome the shortcomings of cloud computing paradigm in handling the massive amount of traffic caused by the enormous number of Internet of Things devices being increasingly connected to the Internet on daily basis. Despite its advantages, fog architecture introduces new security and privacy threats that need to be studied and solved as soon as possible. In this work, we explore two privacy issues posed by the fog computing architecture and we define privacy challenges according to them. The first challenge is related to the fog's design purposes of reducing the latency and improving the bandwidth, where the existing privacy-preserving methods violate these design purposed. The other challenge is related to the proximity of fog nodes to the end-users or IoT devices. We discuss the importance of addressing these challenges by putting them in the context of real-life scenarios. Finally, we propose a privacy-preserving fog computing paradigm that solves these challenges and we assess the security and efficiency of our solution.

Khazankin, G. R., Komarov, S., Kovalev, D., Barsegyan, A., Likhachev, A..  2017.  System architecture for deep packet inspection in high-speed networks. 2017 Siberian Symposium on Data Science and Engineering (SSDSE). :27–32.

To solve the problems associated with large data volume real-time processing, heterogeneous systems using various computing devices are increasingly used. The characteristic of solving this class of problems is related to the fact that there are two directions for improving methods of real-time data analysis: the first is the development of algorithms and approaches to analysis, and the second is the development of hardware and software. This article reviews the main approaches to the architecture of a hardware-software solution for traffic capture and deep packet inspection (DPI) in data transmission networks with a bandwidth of 80 Gbit/s and higher. At the moment there are software and hardware tools that allow designing the architecture of capture system and deep packet inspection: 1) Using only the central processing unit (CPU); 2) Using only the graphics processing unit (GPU); 3) Using the central processing unit and graphics processing unit simultaneously (CPU + GPU). In this paper, we consider these key approaches. Also attention is paid to both hardware and software requirements for the architecture of solutions. Pain points and remedies are described.

Alhafidh, B. M. H., Allen, W. H..  2017.  High Level Design of a Home Autonomous System Based on Cyber Physical System Modeling. 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW). :45–52.
The process used to build an autonomous smart home system using Cyber-Physical Systems (CPS) principles has received much attention by researchers and developers. However, there are many challenges during the design and implementation of such a system, such as Portability, Timing, Prediction, and Integrity. This paper presents a novel modeling methodology for a smart home system in the scope of CyberPhysical interface that attempts to overcome these issues. We discuss a high-level design approach that simulates the first three levels of a 5C architecture in CPS layers in a smart home environment. A detailed description of the model design, architecture, and a software implementation via NetLogo simulation have been presented in this paper.
Salah, H., Eltoweissy, M..  2017.  Towards Collaborative Trust Management. 2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC). :198–208.

Current technologies to include cloud computing, social networking, mobile applications and crowd and synthetic intelligence, coupled with the explosion in storage and processing power, are evolving massive-scale marketplaces for a wide variety of resources and services. They are also enabling unprecedented forms and levels of collaborations among human and machine entities. In this new era, trust remains the keystone of success in any relationship between two or more parties. A primary challenge is to establish and manage trust in environments where massive numbers of consumers, providers and brokers are largely autonomous with vastly diverse requirements, capabilities, and trust profiles. Most contemporary trust management solutions are oblivious to diversities in trustors' requirements and contexts, utilize direct or indirect experiences as the only form of trust computations, employ hardcoded trust computations and marginally consider collaboration in trust management. We surmise the need for reference architecture for trust management to guide the development of a wide spectrum of trust management systems. In our previous work, we presented a preliminary reference architecture for trust management which provides customizable and reconfigurable trust management operations to accommodate varying levels of diversity and trust personalization. In this paper, we present a comprehensive taxonomy for trust management and extend our reference architecture to feature collaboration as a first-class object. Our goal is to promote the development of new collaborative trust management systems, where various trust management operations would involve collaborating entities. Using the proposed architecture, we implemented a collaborative personalized trust management system. Simulation results demonstrate the effectiveness and efficiency of our system.

Kakanakov, N., Shopov, M..  2017.  Adaptive models for security and data protection in IoT with Cloud technologies. 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). :1001–1004.

The paper presents an example Sensor-cloud architecture that integrates security as its native ingredient. It is based on the multi-layer client-server model with separation of physical and virtual instances of sensors, gateways, application servers and data storage. It proposes the application of virtualised sensor nodes as a prerequisite for increasing security, privacy, reliability and data protection. All main concerns in Sensor-Cloud security are addressed: from secure association, authentication and authorization to privacy and data integrity and protection. The main concept is that securing the virtual instances is easier to implement, manage and audit and the only bottleneck is the physical interaction between real sensor and its virtual reflection.

Ye, F., Qian, Y..  2017.  A Security Architecture for Networked Internet of Things Devices. GLOBECOM 2017 - 2017 IEEE Global Communications Conference. :1–6.

The Internet of Things (IoT) increasingly demonstrates its role in smart services, such as smart home, smart grid, smart transportation, etc. However, due to lack of standards among different vendors, existing networked IoT devices (NoTs) can hardly provide enough security. Moreover, it is impractical to apply advanced cryptographic solutions to many NoTs due to limited computing capability and power supply. Inspired by recent advances in IoT demand, in this paper, we develop an IoT security architecture that can protect NoTs in different IoT scenarios. Specifically, the security architecture consists of an auditing module and two network-level security controllers. The auditing module is designed to have a stand-alone intrusion detection system for threat detection in a NoT network cluster. The two network-level security controllers are designed to provide security services from either network resource management or cryptographic schemes regardless of the NoT security capability. We also demonstrate the proposed IoT security architecture with a network based one-hop confidentiality scheme and a cryptography-based secure link mechanism.

Ye, M., Shahrak, M. Z., Wei, S..  2017.  PUFSec: Protecting physical unclonable functions using hardware isolation-based system security techniques. 2017 Asian Hardware Oriented Security and Trust Symposium (AsianHOST). :7–12.

This paper aims to address the security challenges on physical unclonable functions (PUFs) raised by modeling attacks and denial of service (DoS) attacks. We develop a hardware isolation-based secure architecture extension, namely PUFSec, to protect the target PUF from security compromises without modifying the internal PUF design. PUFSec achieves the security protection by physically isolating the PUF hardware and data from the attack surfaces accessible by the adversaries. Furthermore, we deploy strictly enforced security policies within PUFSec, which authenticate the incoming PUF challenges and prevent attackers from collecting sufficient PUF responses to issue modeling attacks or interfering with the PUF workflow to launch DoS attacks. We implement our PUFSec framework on a Xilinx SoC equipped with ARM processor. Our experimental results on the real hardware prove the enhanced security and the low performance and power overhead brought by PUFSec.

Obster, M., Kowalewski, S..  2017.  A live static code analysis architecture for PLC software. 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). :1–4.

Static code analysis is a convenient technique to support the development of software. Without prior test setup, information about a later runtime behavior can be inferred and errors in the code can be found before using a regular compiler. Solutions to apply static code analysis to PLC software following the IEC 61131-3 already exist, but using these separate tools usually creates a gap in the development process. In this paper we introduce an architecture to use static analysis directly in a development environment and give instant feedback to the developer while he is still editing the PLC software.

Bresch, C., Michelet, A., Amato, L., Meyer, T., Hély, D..  2017.  A red team blue team approach towards a secure processor design with hardware shadow stack. 2017 IEEE 2nd International Verification and Security Workshop (IVSW). :57–62.

Software attacks are commonly performed against embedded systems in order to access private data or to run restricted services. In this work, we demonstrate some vulnerabilities of commonly use processor which can be leveraged by hackers to attack a system. The targeted devices are based on open processor architectures OpenRISC and RISC-V. Several software exploits are discussed and demonstrated while a hardware countermeasure is proposed and validated on OpenRISC against Return Oriented Programming attack.

Nashaat, M., Ali, K., Miller, J..  2017.  Detecting Security Vulnerabilities in Object-Oriented PHP Programs. 2017 IEEE 17th International Working Conference on Source Code Analysis and Manipulation (SCAM). :159–164.

PHP is one of the most popular web development tools in use today. A major concern though is the improper and insecure uses of the language by application developers, motivating the development of various static analyses that detect security vulnerabilities in PHP programs. However, many of these approaches do not handle recent, important PHP features such as object orientation, which greatly limits the use of such approaches in practice. In this paper, we present OOPIXY, a security analysis tool that extends the PHP security analyzer PIXY to support reasoning about object-oriented features in PHP applications. Our empirical evaluation shows that OOPIXY detects 88% of security vulnerabilities found in micro benchmarks. When used on real-world PHP applications, OOPIXY detects security vulnerabilities that could not be detected using state-of-the-art tools, retaining a high level of precision. We have contacted the maintainers of those applications, and two applications' development teams verified the correctness of our findings. They are currently working on fixing the bugs that lead to those vulnerabilities.

An, S., Zhao, Z., Zhou, H..  2017.  Research on an Agent-Based Intelligent Social Tagging Recommendation System. 2017 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). 1:43–46.

With the repaid growth of social tagging users, it becomes very important for social tagging systems how the required resources are recommended to users rapidly and accurately. Firstly, the architecture of an agent-based intelligent social tagging system is constructed using agent technology. Secondly, the design and implementation of user interest mining, personalized recommendation and common preference group recommendation are presented. Finally, a self-adaptive recommendation strategy for social tagging and its implementation are proposed based on the analysis to the shortcoming of the personalized recommendation strategy and the common preference group recommendation strategy. The self-adaptive recommendation strategy achieves equilibrium selection between efficiency and accuracy, so that it solves the contradiction between efficiency and accuracy in the personalized recommendation model and the common preference recommendation model.

Kwon, Y., Kim, H. K., Koumadi, K. M., Lim, Y. H., Lim, J. I..  2017.  Automated Vulnerability Analysis Technique for Smart Grid Infrastructure. 2017 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT). :1–5.

A smart grid is a fully automated power electricity network, which operates, protects and controls all its physical environments of power electricity infrastructure being able to supply energy in an efficient and reliable way. As the importance of cyber-physical system (CPS) security is growing, various vulnerability analysis methodologies for general systems have been suggested, whereas there has been few practical research targeting the smart grid infrastructure. In this paper, we highlight the significance of security vulnerability analysis in the smart grid environment. Then we introduce various automated vulnerability analysis techniques from executable files. In our approach, we propose a novel binary-based vulnerability discovery method for AMI and EV charging system to automatically extract security-related features from the embedded software. Finally, we present the test result of vulnerability discovery applied for AMI and EV charging system in Korean smart grid environment.

Dridi, M., Rubini, S., Lallali, M., Florez, M. J. S., Singhoff, F., Diguet, J. P..  2017.  DAS: An Efficient NoC Router for Mixed-Criticality Real-Time Systems. 2017 IEEE International Conference on Computer Design (ICCD). :229–232.

Mixed-Criticality Systems (MCS) are real-time systems characterized by two or more distinct levels of criticality. In MCS, it is imperative that high-critical flows meet their deadlines while low critical flows can tolerate some delays. Sharing resources between flows in Network-On-Chip (NoC) can lead to different unpredictable latencies and subsequently complicate the implementation of MCS in many-core architectures. This paper proposes a new virtual channel router designed for MCS deployed over NoCs. The first objective of this router is to reduce the worst-case communication latency of high-critical flows. The second aim is to improve the network use rate and reduce the communication latency for low-critical flows. The proposed router, called DAS (Double Arbiter and Switching router), jointly uses Wormhole and Store And Forward techniques for low and high-critical flows respectively. Simulations with a cycle-accurate SystemC NoC simulator show that, with a 15% network use rate, the communication delay of high-critical flows is reduced by 80% while communication delay of low-critical flow is increased by 18% compared to usual solutions based on routers with multiple virtual channels.