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Zhou, Yaqiu, Ren, Yongmao, Zhou, Xu, Yang, Wanghong, Qin, Yifang.  2019.  A Scientific Data Traffic Scheduling Algorithm Based on Software-Defined Networking. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :62–67.
Compared to ordinary Internet applications, the transfer of scientific data flows often has higher requirements for network performance. The network security devices and systems often affect the efficiency of scientific data transfer. As a new type of network architecture, Software-defined Networking (SDN) decouples the data plane from the control plane. Its programmability allows users to customize the network transfer path and makes the network more intelligent. The Science DMZ model is a private network for scientific data flow transfer, which can improve performance under the premise of ensuring network security. This paper combines SDN with Science DMZ, designs and implements an SDN-based traffic scheduling algorithm considering the load of link. In addition to distinguishing scientific data flow from common data flow, the algorithm further distinguishes the scientific data flows of different applications and performs different traffic scheduling of scientific data for specific link states. Experiments results proved that the algorithm can effectively improve the transmission performance of scientific data flow.
Rady, Mai, Abdelkader, Tamer, Ismail, Rasha.  2018.  SCIQ-CD: A Secure Scheme to Provide Confidentiality and Integrity of Query results for Cloud Databases. 2018 14th International Computer Engineering Conference (ICENCO). :225–230.
Database outsourcing introduces a new paradigm, called Database as a Service (DBaaS). Database Service Providers (DSPs) have the ability to host outsourced databases and provide efficient facilities for their users. However, the data and the execution of database queries are under the control of the DSP, which is not always a trusted authority. Therefore, our problem is to ensure the outsourced database security. To address this problem, we propose a Secure scheme to provide Confidentiality and Integrity of Query results for Cloud Databases (SCIQ-CD). The performance analysis shows that our proposed scheme is secure and efficient for practical deployment.
Kneib, Marcel, Huth, Christopher.  2018.  Scission: Signal Characteristic-Based Sender Identification and Intrusion Detection in Automotive Networks. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :787–800.
Increased connectivity increases the attack vector. This also applies to connected vehicles in which vulnerabilities not only threaten digital values but also humans and the environment. Typically, attackers try to exploit the Controller Area Network (CAN) bus, which is the most widely used standard for internal vehicle communication. Once an Electronic Control Unit (ECU) connected to the CAN bus is compromised, attackers can manipulate messages at will. The missing sender authentication by design of the CAN bus enables adversarial access to vehicle functions with severe consequences. In order to address this problem, we propose Scission, an Intrusion Detection System (IDS) which uses fingerprints extracted from CAN frames, enabling the identification of sending ECUs. Scission utilizes physical characteristics from analog values of CAN frames to assess whether it was sent by the legitimate ECU. In addition, to detect comprised ECUs, the proposed system is able to recognize attacks from unmonitored and additional devices. We show that Scission is able to identify the sender with an average probability of 99.85%, during the evaluation on two series production cars and a prototype setup. Due to the robust design of the system, the evaluation shows that all false positives were prevented. Compared to previous approaches, we have significantly reduced hardware costs and increased identification rates, which enables a broad application of this technology.
Withers, Alex, Bockelman, Brian, Weitzel, Derek, Brown, Duncan, Gaynor, Jeff, Basney, Jim, Tannenbaum, Todd, Miller, Zach.  2018.  SciTokens: Capability-Based Secure Access to Remote Scientific Data. Proceedings of the Practice and Experience on Advanced Research Computing. :24:1–24:8.
The management of security credentials (e.g., passwords, secret keys) for computational science workflows is a burden for scientists and information security officers. Problems with credentials (e.g., expiration, privilege mismatch) cause workflows to fail to fetch needed input data or store valuable scientific results, distracting scientists from their research by requiring them to diagnose the problems, re-run their computations, and wait longer for their results. In this paper, we introduce SciTokens, open source software to help scientists manage their security credentials more reliably and securely. We describe the SciTokens system architecture, design, and implementation addressing use cases from the Laser Interferometer Gravitational-Wave Observatory (LIGO) Scientific Collaboration and the Large Synoptic Survey Telescope (LSST) projects. We also present our integration with widely-used software that supports distributed scientific computing, including HTCondor, CVMFS, and XrootD. SciTokens uses IETF-standard OAuth tokens for capability-based secure access to remote scientific data. The access tokens convey the specific authorizations needed by the workflows, rather than general-purpose authentication impersonation credentials, to address the risks of scientific workflows running on distributed infrastructure including NSF resources (e.g., LIGO Data Grid, Open Science Grid, XSEDE) and public clouds (e.g., Amazon Web Services, Google Cloud, Microsoft Azure). By improving the interoperability and security of scientific workflows, SciTokens 1) enables use of distributed computing for scientific domains that require greater data protection and 2) enables use of more widely distributed computing resources by reducing the risk of credential abuse on remote systems.
That, D. H. T., Fils, G., Yuan, Z., Malik, T..  2017.  Sciunits: Reusable Research Objects. 2017 IEEE 13th International Conference on e-Science (e-Science). :374–383.

Science is conducted collaboratively, often requiring knowledge sharing about computational experiments. When experiments include only datasets, they can be shared using Uniform Resource Identifiers (URIs) or Digital Object Identifiers (DOIs). An experiment, however, seldom includes only datasets, but more often includes software, its past execution, provenance, and associated documentation. The Research Object has recently emerged as a comprehensive and systematic method for aggregation and identification of diverse elements of computational experiments. While a necessary method, mere aggregation is not sufficient for the sharing of computational experiments. Other users must be able to easily recompute on these shared research objects. In this paper, we present the sciunit, a reusable research object in which aggregated content is recomputable. We describe a Git-like client that efficiently creates, stores, and repeats sciunits. We show through analysis that sciunits repeat computational experiments with minimal storage and processing overhead. Finally, we provide an overview of sharing and reproducible cyberinfrastructure based on sciunits gaining adoption in the domain of geosciences.

Kumar, S., Johari, R., Singh, L., Gupta, K..  2017.  SCLCT: Secured cross language cipher technique. 2017 International Conference on Computing, Communication and Automation (ICCCA). :545–550.

Cryptography is the fascinating science that deals with constructing and destructing the secret codes. The evolving digitization in this modern era possesses cryptography as one of its backbones to perform the transactions with confidentiality and security wherever the authentication is required. With the modern technology that has evolved, the use of codes has exploded, enriching cryptology and empowering citizens. One of the most important things that encryption provides anyone using any kind of computing device is `privacy'. There is no way to have true privacy with strong security, the method with which we are dealing with is to make the cipher text more robust to be by-passed. In current work, the well known and renowned Caesar cipher and Rail fence cipher techniques are combined with a cross language cipher technique and the detailed comparative analysis amongst them is carried out. The simulations have been carried out on Eclipse Juno version IDE for executions and Java, an open source language has been used to implement these said techniques.

Zaman, Tarannum Shaila, Han, Xue, Yu, Tingting.  2019.  SCMiner: Localizing System-Level Concurrency Faults from Large System Call Traces. 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE). :515—526.

Localizing concurrency faults that occur in production is hard because, (1) detailed field data, such as user input, file content and interleaving schedule, may not be available to developers to reproduce the failure; (2) it is often impractical to assume the availability of multiple failing executions to localize the faults using existing techniques; (3) it is challenging to search for buggy locations in an application given limited runtime data; and, (4) concurrency failures at the system level often involve multiple processes or event handlers (e.g., software signals), which can not be handled by existing tools for diagnosing intra-process(thread-level) failures. To address these problems, we present SCMiner, a practical online bug diagnosis tool to help developers understand how a system-level concurrency fault happens based on the logs collected by the default system audit tools. SCMiner achieves online bug diagnosis to obviate the need for offline bug reproduction. SCMiner does not require code instrumentation on the production system or rely on the assumption of the availability of multiple failing executions. Specifically, after the system call traces are collected, SCMiner uses data mining and statistical anomaly detection techniques to identify the failure-inducing system call sequences. It then maps each abnormal sequence to specific application functions. We have conducted an empirical study on 19 real-world benchmarks. The results show that SCMiner is both effective and efficient at localizing system-level concurrency faults.

Sahu, Abhijeet, Huang, Hao, Davis, Katherine, Zonouz, Saman.  2019.  SCORE: A Security-Oriented Cyber-Physical Optimal Response Engine. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–6.

Automatic optimal response systems are essential for preserving power system resilience and ensuring faster recovery from emergency under cyber compromise. Numerous research works have developed such response engine for cyber and physical system recovery separately. In this paper, we propose a novel cyber-physical decision support system, SCORE, that computes optimal actions considering pure and hybrid cyber-physical states, using Markov Decision Process (MDP). Such an automatic decision making engine can assist power system operators and network administrators to make a faster response to prevent cascading failures and attack escalation respectively. The hybrid nature of the engine makes the reward and state transition model of the MDP unique. Value iteration and policy iteration techniques are used to compute the optimal actions. Tests are performed on three and five substation power systems to recover from attacks that compromise relays to cause transmission line overflow. The paper also analyses the impact of reward and state transition model on computation. Corresponding results verify the efficacy of the proposed engine.

Morales, A., Luna-Garcia, E., Fierrez, J., Ortega-Garcia, J..  2015.  Score normalization for keystroke dynamics biometrics. 2015 International Carnahan Conference on Security Technology (ICCST). :223–228.

This paper analyzes score normalization for keystroke dynamics authentication systems. Previous studies have shown that the performance of behavioral biometric recognition systems (e.g. voice and signature) can be largely improved with score normalization and target-dependent techniques. The main objective of this work is twofold: i) to analyze the effects of different thresholding techniques in 4 different keystroke dynamics recognition systems for real operational scenarios; and ii) to improve the performance of keystroke dynamics on the basis of target-dependent score normalization techniques. The experiments included in this work are worked out over the keystroke pattern of 114 users from two different publicly available databases. The experiments show that there is large room for improvements in keystroke dynamic systems. The results suggest that score normalization techniques can be used to improve the performance of keystroke dynamics systems in more than 20%. These results encourage researchers to explore this research line to further improve the performance of these systems in real operational environments.

Bönsch, Andrea, Trisnadi, Robert, Wendt, Jonathan, Vierjahn, Tom, Kuhlen, Torsten W..  2017.  Score-based Recommendation for Efficiently Selecting Individual Virtual Agents in Multi-agent Systems. Proceedings of the 23rd ACM Symposium on Virtual Reality Software and Technology. :74:1–74:2.
Controlling user-agent-interactions by means of an external operator includes selecting the virtual interaction partners fast and faultlessly. However, especially in immersive scenes with a large number of potential partners, this task is non-trivial. Thus, we present a score-based recommendation system supporting an operator in the selection task. Agents are recommended as potential partners based on two parameters: the user's distance to the agents and the user's gazing direction. An additional graphical user interface (GUI) provides elements for configuring the system and for applying actions to those agents which the operator has confirmed as interaction partners.
Al-Bassam, Mustafa.  2017.  SCPKI: A Smart Contract-Based PKI and Identity System. Proceedings of the ACM Workshop on Blockchain, Cryptocurrencies and Contracts. :35–40.

The Public Key Infrastructure (PKI) in use today on the Internet to secure communications has several drawbacks arising from its centralised and non-transparent design. In the past there has been instances of certificate authorities publishing rogue certificates for targeted attacks, and this has been difficult to immediately detect as certificate authorities are not transparent about the certificates they issue. Furthermore, the centralised selection of trusted certificate authorities by operating system and browser vendors means that it is not practical to untrust certificate authorities that have issued rogue certificates, as this would disrupt the TLS process for many other hosts. SCPKI is an alternative PKI system based on a decentralised and transparent design using a web-of-trust model and a smart contract on the Ethereum blockchain, to make it easily possible for rogue certificates to be detected when they are published. The web-of-trust model is designed such that an entity or authority in the system can verify (or vouch for) fine-grained attributes of another entity's identity (such as company name or domain name), as an alternative to the centralised certificate authority identity verification model.

He, F., Zhang, Y., Liu, H., Zhou, W..  2018.  SCPN-Based Game Model for Security Situational Awareness in the Intenet of Things. 2018 IEEE Conference on Communications and Network Security (CNS). :1-5.
Internet of Things (IoT) is characterized by various of heterogeneous devices that facing numerous threats, which makes modeling security situation of IoT still a certain challenge. This paper defines a Stochastic Colored Petri Net (SCPN) for IoT-based smart environment and then proposes a Game model for security situational awareness. All possible attack paths are computed by the SCPN, and antagonistic behavior of both attackers and defenders are taken into consideration dynamically according to Game Theory (GT). Experiments on two typical attack scenarios in smart home environment demonstrate the effectiveness of the proposed model. The proposed model can form a macroscopic trend curve of the security situation. Analysis of the results shows the capabilities of the proposed model in finding vulnerable devices and potential attack paths, and even facilitating the choice of defense strategy. To the best of our knowledge, this is the first attempt to use Game Theory in the IoT-based SCPN to establish a security situational awareness model for a complex smart environment.
Ashraf, Muhammed Naazer.  2017.  Scratching the Surface of Windows Server 2016 and System Center Configuration Manager Current Branch. Proceedings of the 2017 ACM Annual Conference on SIGUCCS. :73–79.

Lehigh University has set a goal to implement System Center Configuration Manager by the end of 2017. This project is being spearheaded by one of our Senior Computing Consultants who has been researching and trained in the Microsoft Virtualization stack. We will discuss our roadmaps, results from our proof-of-concept environments, and discussions in driving this project.

Gugelmann, D., Sommer, D., Lenders, V., Happe, M., Vanbever, L..  2018.  Screen watermarking for data theft investigation and attribution. 2018 10th International Conference on Cyber Conflict (CyCon). :391–408.
Organizations not only need to defend their IT systems against external cyber attackers, but also from malicious insiders, that is, agents who have infiltrated an organization or malicious members stealing information for their own profit. In particular, malicious insiders can leak a document by simply opening it and taking pictures of the document displayed on the computer screen with a digital camera. Using a digital camera allows a perpetrator to easily avoid a log trail that results from using traditional communication channels, such as sending the document via email. This makes it difficult to identify and prove the identity of the perpetrator. Even a policy prohibiting the use of any device containing a camera cannot eliminate this threat since tiny cameras can be hidden almost everywhere. To address this leakage vector, we propose a novel screen watermarking technique that embeds hidden information on computer screens displaying text documents. The watermark is imperceptible during regular use, but can be extracted from pictures of documents shown on the screen, which allows an organization to reconstruct the place and time of the data leak from recovered leaked pictures. Our approach takes advantage of the fact that the human eye is less sensitive to small luminance changes than digital cameras. We devise a symbol shape that is invisible to the human eye, but still robust to the image artifacts introduced when taking pictures. We complement this symbol shape with an error correction coding scheme that can handle very high bit error rates and retrieve watermarks from cropped and compressed pictures. We show in an experimental user study that our screen watermarks are not perceivable by humans and analyze the robustness of our watermarks against image modifications.
Stokes, J. W., Agrawal, R., McDonald, G., Hausknecht, M..  2019.  ScriptNet: Neural Static Analysis for Malicious JavaScript Detection. MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). :1–8.
Malicious scripts are an important computer infection threat vector for computer users. For internet-scale processing, static analysis offers substantial computing efficiencies. We propose the ScriptNet system for neural malicious JavaScript detection which is based on static analysis. We also propose a novel deep learning model, Pre-Informant Learning (PIL), which processes Javascript files as byte sequences. Lower layers capture the sequential nature of these byte sequences while higher layers classify the resulting embedding as malicious or benign. Unlike previously proposed solutions, our model variants are trained in an end-to-end fashion allowing discriminative training even for the sequential processing layers. Evaluating this model on a large corpus of 212,408 JavaScript files indicates that the best performing PIL model offers a 98.10% true positive rate (TPR) for the first 60K byte subsequences and 81.66% for the full-length files, at a false positive rate (FPR) of 0.50%. Both models significantly outperform several baseline models. The best performing PIL model can successfully detect 92.02% of unknown malware samples in a hindsight experiment where the true labels of the malicious JavaScript files were not known when the model was trained.
Park, Jungmin, Cho, Seongjoon, Lim, Taejin, Bhunia, Swarup, Tehranipoor, Mark.  2019.  SCR-QRNG: Side-Channel Resistant Design using Quantum Random Number Generator. 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). :1–8.
Random number generators play a pivotal role in generating security primitives, e.g., encryption keys, nonces, initial vectors, and random masking for side-channel countermeasures. A quantum entropy source based on radioactive isotope decay can be exploited to generate random numbers with sufficient entropy. If a deterministic random bit generator (DRBG) is combined for post-processing, throughput of the quantum random number generator (QRNG) can be improved. However, general DRBGs are susceptible to side-channel attacks. In this paper, we propose a framework called SCR-QRNG framework, which offers Side-Channel Resistant primitives using QRNG. The QRNG provides sources of randomness for modulating the clock frequency of a DRBG to obfuscate side-channel leakages, and to generate unbiased random numbers for security primitives. The QRNG has robustness against power side-channel attacks and is in compliance with NIST SP 800-22/90B and BSI AIS 31. We fabricate a quantum entropy chip, and implement a PCB module for a random frequency clock generator and a side-channel resistant QRNG on an FPGA.
Liu, Yi, Dong, Mianxiong, Ota, Kaoru, Wu, Jun, Li, Jianhua, Chen, Hao.  2019.  SCTD: Smart Reasoning Based Content Threat Defense in Semantics Knowledge Enhanced ICN. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.
Information-centric networking (ICN) is a novel networking architecture with subscription-based naming mechanism and efficient caching, which has abundant semantic features. However, existing defense studies in ICN fails to isolate or block efficiently novel content threats including malicious penetration and semantic obfuscation for the lack of researches considering ICN semantic features. More importantly, to detect potential threats, existing security works in ICN fail to use semantic reasoning to construct security knowledge-based defense mechanism. Thus ICN needs a smart and content-based defense mechanism. Current works are not able to block content threats implicated in semantics. Additionally, based on traditional computing resources, they are incompatible with ICN protocols. In this paper, we propose smart reasoning based content threat defense for semantics knowledge enhanced ICN. A fog computing based defense mechanism with content semantic awareness is designed to build ICN edge defense system. In addition, smart reasoning algorithms is proposed to detect implicit knowledge and semantic relations in packet names and contents with context communication content and knowledge graph. On top of inference knowledge, the mechanism can perceive threats from ICN interests. Simulations demonstrate the validity and efficiency of the proposed mechanism.
Ma Licui, Li Meihong, Li Lun, Du Ye, Zhang Dawei.  2014.  A SDKEY-Based Secure Storage and Transmission Approach for Android Phone. Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2014 International Conference on. :1-6.

To resolve the more and more serious problems of sensitive data leakage from Android systems, a kind of method of data protection on encryption storage and encryption transmission is presented in this paper by adopting secure computation environment of SDKEY device. Firstly, a dual-authentication scheme for login using SDKEY and PIN is designed. It is used for login on system boot and lock screen. Secondly, an approach on SDKEY-based transparent encryption storage for different kinds of data files is presented, and a more fine-grained encryption scheme for different file types is proposed. Finally, a method of encryption transmission between Android phones is presented, and two kinds of key exchange mechanisms are designed for next encryption and decryption operation in the following. One is a zero-key exchange and another is a public key exchange. In this paper, a prototype system based on the above solution has been developed, and its security and performance are both analyzed and verified from several aspects.

Ghosh, U., Chatterjee, P., Tosh, D., Shetty, S., Xiong, K., Kamhoua, C..  2017.  An SDN Based Framework for Guaranteeing Security and Performance in Information-Centric Cloud Networks. 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). :749–752.

Cloud data centers are critical infrastructures to deliver cloud services. Although security and performance of cloud data centers have been well studied in the past, their networking aspects are overlooked. Current network infrastructures in cloud data centers limit the ability of cloud provider to offer guaranteed cloud network resources to users. In order to ensure security and performance requirements as defined in the service level agreement (SLA) between cloud user and provider, cloud providers need the ability to provision network resources dynamically and on the fly. The main challenge for cloud provider in utilizing network resource can be addressed by provisioning virtual networks that support information centric services by separating the control plane from the cloud infrastructure. In this paper, we propose an sdn based information centric cloud framework to provision network resources in order to support elastic demands of cloud applications depending on SLA requirements. The framework decouples the control plane and data plane wherein the conceptually centralized control plane controls and manages the fully distributed data plane. It computes the path to ensure security and performance of the network. We report initial experiment on average round-trip delay between consumers and producers.

Chowdhary, Ankur, Pisharody, Sandeep, Huang, Dijiang.  2016.  SDN Based Scalable MTD Solution in Cloud Network. Proceedings of the 2016 ACM Workshop on Moving Target Defense. :27–36.

Software-Defined Networking (SDN) has emerged as a framework for centralized command and control in cloud data centric environments. SDN separates data and control plane, which provides network administrator better visibility and policy enforcement capability compared to traditional networks. The SDN controller can assess reachability information of all the hosts in a network. There are many critical assets in a network which can be compromised by a malicious attacker through a multistage attack. Thus we make use of centralized controller to assess the security state of the entire network and pro-actively perform attack analysis and countermeasure selection. This approach is also known as Moving Target Defense (MTD). We use the SDN controller to assess the attack scenarios through scalable Attack Graphs (AG) and select necessary countermeasures to perform network reconfiguration to counter network attacks. Moreover, our framework has a comprehensive conflict detection and resolution module that ensures that no two flow rules in a distributed SDN-based cloud environment have conflicts at any layer; thereby assuring consistent conflict-free policy implementation and preventing information leakage.

Alcorn, J., Melton, S., Chow, C. E..  2017.  SDN data path confidence analysis. 2017 IEEE Conference on Dependable and Secure Computing. :209–216.

The unauthorized access or theft of sensitive, personal information is becoming a weekly news item. The illegal dissemination of proprietary information to media outlets or competitors costs industry untold millions in remediation costs and losses every year. The 2013 data breach at Target, Inc. that impacted 70 million customers is estimated to cost upwards of 1 billion dollars. Stolen information is also being used to damage political figures and adversely influence foreign and domestic policy. In this paper, we offer some techniques for better understanding the health and security of our networks. This understanding will help professionals to identify network behavior, anomalies and other latent, systematic issues in their networks. Software-Defined Networks (SDN) enable the collection of network operation and configuration metrics that are not readily available, if available at all, in traditional networks. SDN also enables the development of software protocols and tools that increases visibility into the network. By accumulating and analyzing a time series data repository (TSDR) of SDN and traditional metrics along with data gathered from our tools we can establish behavior and security patterns for SDN and SDN hybrid networks. Our research helps provide a framework for a range of techniques for administrators and automated system protection services that give insight into the health and security of the network. To narrow the scope of our research, this paper focuses on a subset of those techniques as they apply to the confidence analysis of a specific network path at the time of use or inspection. This confidence analysis allows users, administrators and autonomous systems to decide whether a network path is secure enough for sending their sensitive information. Our testing shows that malicious activity can be identified quickly as a single metric indicator and consistently within a multi-factor indicator analysis. Our research includes the implementation of - hese techniques in a network path confidence analysis service, called Confidence Assessment as a Service. Using our behavior and security patterns, this service evaluates a specific network path and provides a confidence score for that path before, during and after the transmission of sensitive data. Our research and tools give administrators and autonomous systems a much better understanding of the internal operation and configuration of their networks. Our framework will also provide other services that will focus on detecting latent, systemic network problems. By providing a better understanding of network configuration and operation our research enables a more secure and dependable network and helps prevent the theft of information by malicious actors.

Karmakar, Kallol Krishna, Varadharajan, Vijay, Nepal, Surya, Tupakula, Uday.  2019.  SDN Enabled Secure IoT Architecture. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :581–585.
The Internet of Things (IoT) is increasingly being used in applications ranging from precision agriculture to critical national infrastructure by deploying a large number of resource-constrained devices in hostile environments. These devices are being exploited to launch attacks in cyber systems. As a result, security has become a significant concern in the design of IoT based applications. In this paper, we present a security architecture for IoT networks by leveraging the underlying features supported by Software Defined Networks (SDN). Our security architecture restricts network access to authenticated IoT devices. We use fine granular policies to secure the flows in the IoT network infrastructure and provide a lightweight protocol to authenticate IoT devices. Such an integrated security approach involving authentication of IoT devices and enabling authorized flows can help to protect IoT networks from malicious IoT devices and attacks.
Karmakar, Kallol Krishna, Varadharajan, Vijay, Nepal, Surya, Tupakula, Uday.  2019.  SDN Enabled Secure IoT Architecture. {2019 IFIP/IEEE} Symposium on Integrated Network and Service Management (IM).

The Internet of Things (IoT) is increasingly being used in applications ranging from precision agriculture to critical national infrastructure by deploying a large number of resource-constrained devices in hostile environments. These devices are being exploited to launch attacks in cyber systems. As a result, security has become a significant concern in the design of IoT based applications. In this paper, we present a security architecture for IoT networks by leveraging the underlying features supported by Software Defined Networks (SDN). Our security architecture restricts network access to authenticated IoT devices. We use fine granular policies to secure the flows in the IoT network infrastructure and provide a lightweight protocol to authenticate IoT devices. Such an integrated security approach involving authentication of IoT devices and enabling authorized flows can help to protect IoT networks from malicious IoT devices and attacks.

Nikolich, Anita.  2016.  SDN Research Challenges and Opportunities. Proceedings of the Sixth ACM Conference on Data and Application Security and Privacy. :254–254.

The National Science Foundation has made investments in Software Defined Networking (SDN) and Network Function Virtualization (NFV) for many years, in both the research and infrastructure areas. SDN and NFV enable systems to become more open to transformative research, with implications for revolutionary new applications and services. Additionally, the emerging concept of Software-Defined Exchanges will enable large-scale interconnection of Software Defined infrastructures, owned and operated by many different organizations, to provide logically isolated 'on demand' global scale infrastructure on an end-to-end basis, with enhanced flexibility and security for new applications. This talk will examine past NSF investments and successes in SDN/NFV, identify new research opportunities available to the community and present challenges that need to be overcome to make SDN/NFV a reality in operational cyberinfrastructure.

Guodong, T., Xi, Q., Chaowen, C..  2017.  A SDN security control forwarding mechanism based on cipher identification. 2017 IEEE 9th International Conference on Communication Software and Networks (ICCSN). :1419–1425.

SDN is a new network architecture for control and data forwarding logic separation, able to provide a high degree of openness and programmability, with many advantages not available by traditional networks. But there are still some problems unsolved, for example, it is easy to cause the controller to be attacked due to the lack of verifying the source of the packet, and the limited range of match fields cannot meet the requirement of the precise control of network services etc. Aiming at the above problems, this paper proposes a SDN network security control forwarding mechanism based on cipher identification, when packets flow into and out of the network, the forwarding device must verify their source to ensure the user's non-repudiation and the authenticity of packets. Besides administrators control the data forwarding based on cipher identification, able to form network management and control capabilities based on human, material, business flow, and provide a new method and means for the future of Internet security.