Biblio

Home automation is an intelligent, functional as a unit system that facilitates home processes without unnecessarily complicating the user's life. Devices can be connected, which in turn connect and talk through a centralized control unit, which are accessible via mobile phones. These devices include lights, appliances, security systems, alarms and many other sensors and devices. This paper presents the design and implementation of a Bluetooth based smart home automation system which uses a Peripheral interface controller (PIC) microcontroller (16F1937) as the main processer and the appliances are connected to the peripheral ports of the microcontroller via relays. The circuit in the project was designed in Diptrace software. The PCB layout design was completed. The fully functional smart home prototype was built and demonstrated to functional.

Due to centralized control and programmable capability of the SDN architecture, network administrators can easily manage and control the whole network through the centralized controller. According to the SDN architecture, the SDN controller is vulnerable to distributed denial of service (DDOS) attacks. Thus, a failure of SDN controller is a major leak for security concern. The objectives of paper is therefore to detect the DDOS attacks and classify the normal or attack traffic in SDN network using machine learning algorithms. In this proposed system, polynomial SVM is applied to compare to existing linear SVM by using scapy, which is packet generation tool and RYU SDN controller. According to the experimental result, polynomial SVM achieves 3% better accuracy and 34% lower false alarm rate compared to Linear SVM.

The major challenge of Real Time Protocol is to balance efficiency and fairness over limited bandwidth. MPTCP has proved to be effective for multimedia and real time networks. Ideally, an MPTCP sender should couple the subflows sharing the bottleneck link to provide TCP friendliness. However, existing shared bottleneck detection scheme either utilize end-to-end delay without consideration of multiple bottleneck scenario, or identify subflows on switch at the expense of operation overhead. In this paper, we propose a lightweight yet accurate approach, EMPTCP, to detect shared bottleneck. EMPTCP uses the widely deployed ECN scheme to capture the real congestion state of shared bottleneck, while at the same time can be transparently utilized by various enhanced MPTCP protocols. Through theory analysis, simulation test and real network experiment, we show that EMPTCP achieves higher than 90% accuracy in shared bottleneck detection, thus improving the network efficiency and fairness.

Optical burst switching (OBS) is a candidate switching paradigm for future backbone all-optical networks. However, data burst contention can be a major problem especially as the number of lightpath connections as well as the overall network radius increases. Furthermore, the absence of or limited buffering provision in core nodes, coupled with the standard one-way resources signaling aggravate contention occurrences resulting in some of the contending bursts being discarded as a consequence. Contention avoidance as well as resolution measures can be applied in such networks in order to resolve any contention issues. In that way, the offered quality of service (QoS) as well as the network performance will remain consistent and reliable. In particular, to maintain the cost effectiveness of OBS deployment, restricted intermediate buffering can be implemented to buffer contending bursts that have already traversed much of the network on their way to the intended destination. Hence in this paper we propose and analyze a restricted intermediate Node Buffering-based routing and wavelength assignment scheme (RI-RWA) scheme to address contention occurrences as well as prevent deletion of contending bursts. The scheme primarily prioritizes the selection of primary as well as deflection paths for establishing lightpath connections paths as a function of individual wavelength contention performances. It further facilitates and allows partial intermediate buffering provisioning for any data bursts that encounter contention after having already propagated more than half the network's diameter. We evaluate the scheme's performance by simulation and obtained results show that the scheme indeed does improve on key network performance metrics such as fairness, load balancing as well as throughput.

In multi-tenant datacenters, the hardware may be homogeneous but the traffic often is not. For instance, customers who pay an equal amount of money can get an unequal share of the bottleneck capacity when they do not open the same number of TCP connections. To address this problem, several recent proposals try to manipulate the traffic that TCP sends from the VMs. VCC and AC/DC are two new mechanisms that let the hypervisor control traffic by influencing the TCP receiver window (rwnd). This avoids changing the guest OS, but has limitations (it is not possible to make TCP increase its rate faster than it normally would). Seawall, on the other hand, completely rewrites TCP's congestion control, achieving fairness but requiring significant changes to both the hypervisor and the guest OS. There seems to be a need for a middle ground: a method to control TCP's sending rate without requiring a complete redesign of its congestion control. We introduce a minimally-invasive solution that is flexible enough to cater for needs ranging from weighted fairness in multi-tenant datacenters to potentially offering Internet-wide benefits from reduced interflow competition.

In this paper, we study trust-related human factors in supervisory control of swarm robots with varied levels of autonomy (LOA) in a target foraging task. We compare three LOAs: manual, mixed-initiative (MI), and fully autonomous LOA. In the manual LOA, the human operator chooses headings for a flocking swarm, issuing new headings as needed. In the fully autonomous LOA, the swarm is redirected automatically by changing headings using a search algorithm. In the mixed-initiative LOA, if performance declines, control is switched from human to swarm or swarm to human. The result of this work extends the current knowledge on human factors in swarm supervisory control. Specifically, the finding that the relationship between trust and performance improved for passively monitoring operators (i.e., improved situation awareness in higher LOAs) is particularly novel in its contradiction of earlier work. We also discover that operators switch the degree of autonomy when their trust in the swarm system is low. Last, our analysis shows that operator's preference for a lower LOA is confirmed for a new domain of swarm control.

Network security testing devices play important roles in Cyber security. Most of the current network security testing devices are based on proprietary hardware, however, the virtual network security tester needs high network I/O throughput performance. Therefore, the solution of the problem, which provides high-performance network I/O in the virtual scene will be explained in this paper. The method we proposed for virtualized network I/O performance optimization on a general hardware platform is able to achieve the I/O throughput performance of the proprietary hardware. The Single Root I/O Virtualization (SRIOV) of the physical network card is divided into a plurality of virtual network function of VF, furthermore, it can be added to different VF and VM. Extensive experiment illustrated that the virtualization and the physical network card sharing based on hardware are realized, and they can be used by Data Plane Development Kit (DPDK) and SRIOV technology. Consequently, the test instrument applications in virtual machines achieves the rate of 10Gps and meet the I/O requirement.

It is expected that the concept of Internet of everything will be realized in 2020 because of the coming of the 5G wireless communication technology. Internet of Things (IoT) services in various fields require different types of network service features, such as mobility, security, bandwidth, latency, reliability and control strategies. In order to solve the complex requirements and provide customized services, a new network architecture is needed. To change the traditional control mode used in the traditional network architecture, the Software Defined Network (SDN) is proposed. First, SDN divides the network into the Control Plane and Data Plane and then delegates the network management authority to the controller of the control layer. This allows centralized control of connections of a large number of devices. Second, SDN can help realizing the network slicing in the aspect of network layer. With the network slicing technology proposed by 5G, it can cut the 5G network out of multiple virtual networks and each virtual network is to support the needs of diverse users. In this work, we design and develop a network slicing framework. The contributions of this article are two folds. First, through SDN technology, we develop to provide the corresponding end-to-end (E2E) network slicing for IoT applications with different requirements. Second, we develop a dynamic network slice resource scheduling and management method based on SDN to meet the services' requirements with time-varying characteristics. This is usually observed in streaming and services with bursty traffic. A prototyping system is completed. The effectiveness of the system is demonstrated by using an electronic fence application as a use case.

Dynamic network security services have been proposed exploiting the benefits of Software Defined Networking (SDN) and Network Functions Virtualization (NFV) technologies. However, many of these services rely on controller interaction, which presents a performance and scalability challenge, and a threat vector. To overcome the performance issue, stateful data-plane designs have been proposed. Unfortunately, these solutions do not offer protection from attacks that exploit the SDN implementation of network functions such as topology and path update, or services such as the Address Resolution Protocol (ARP). In this work, we propose state-based SDN security protection mechanisms. Our stateful security data plane solution, OFMTL-SEC, is designed to provide protection against attacks on SDN and traditional network services. Specifically, we present a novel data plane protection against configuration-based attacks in SDN and against ARP spoofing. OFMTL-SEC is compared with the state-of-the-art solutions and offers increased security to SDNs with negligible performance impact.

We present a formal OpenFlow-based network programming language (OF) including various flow rules, which can not only describe the behaviors of an individual switch, but also support to model a network of switches connected in the point-to-point topology. Besides, a topology-oriented operational semantics of the proposed language is explored to specify how the packet is processed and delivered in the OpenFlow-based networks. Based on the formal framework, we also propose an approach to detect potential security threats caused by the conflict of dynamic flow rules imposed by dynamic OpenFlow applications.

Proof-of-Work (PoW) is a popular protocol used in Blockchain systems to resolve double-spending problems. However, if an attacker has access to calculation hash power greater than half of the total hash power, this attacker can create a double-spending attack or 51% attack. The cost of creating a 51% attack is surprisingly low if hash power is abundantly available. That posts a great threat to lots of PoW blockchains. We propose a technique to combine history weighted information of miners with the total calculation difficulty to alleviate the 51% attack problem. Analysis indicates that with the new technique, the cost of a traditional attack is increased by two orders of magnitude.

Responding to network security incidents requires interference with ongoing attacks to restore the security of services running on production systems. This approach prevents damage, but drastically impedes the collection of threat intelligence and the analysis of vulnerabilities, exploits, and attack strategies. We propose the live confinement of suspicious microservices into a sandbox network that allows to monitor and analyze ongoing attacks under quarantine and that retains an image of the vulnerable and open production network. A successful sandboxing requires that it happens completely transparent to and cannot be detected by an attacker. Therefore, we introduce a novel metric to measure the Quality of Deception (QoD) and use it to evaluate three proposed network deception mechanisms. Our evaluation results indicate that in our evaluation scenario in best case, an optimal QoD is achieved. In worst case, only a small downtime of approx. 3s per microservice (MS) occurs and thus a momentary drop in QoD to 70.26% before it converges back to optimum as the quarantined services are restored.

With the gradual progress of cloud computing, big data, network virtualization and other network technology. The traditional network architecture can no longer support this huge business. At this time, the clean slate team defined a new network architecture, SDN (Software Defined Network). It has brought about tremendous changes in the development of today's networks. The controller sends the flow table down to the switch, and the data flow is forwarded through matching flow table items. However, the current flow table resources of the SDN switch are very limited. Therefore, this paper studies the technology of the latest SDN Flow table optimization at home and abroad, proposes an efficient optimization scheme of Flow table item on the betweenness centrality through the main road selection algorithm, and realizes related applications by setting up experimental topology. Experiments show that this scheme can greatly reduce the number of flow table items of switches, especially the more hosts there are in the topology, the more obvious the experimental effect is. And the experiment proves that the optimization success rate is over 80%.

Modern Internet of Things networks are often proprietary, although based on open standards, or are built on the basis of conventional Wi-Fi network, which does not allow the use of energy-saving modes and limits the range of solutions used. The paper is devoted to the study and comparison of two solutions based on Wi-Fi and Bluetooth with the functions of a self-organizing network and switching between transmission channels. The power consumption in relation to specific actions and volumes of transmitted data is investigated; a conclusion is drawn on the conditions for the application of a particular technology.

Modern operating systems for personal computers (including Linux, MAC, and Windows) provide user-level APIs for an application to access the I/O paths of another application. This design facilitates information sharing between applications, enabling applications such as screenshots. However, it also enables user-level malware to log a user's keystrokes or scrape a user's screen output. In this work, we explore a design called SwitchMan to protect a user's I/O paths against user-level malware attacks. SwitchMan assigns each user with two accounts: a regular one for normal operations and a protected one for inputting and outputting sensitive data. Each user account runs under a separate virtual terminal. Malware running under a user's regular account cannot access sensitive input/output under a user's protected account. At the heart of SwitchMan lies a secure protocol that enables automatic account switching when an application requires sensitive input/output from a user. Our performance evaluation shows that SwitchMan adds acceptable performance overhead. Our security and usability analysis suggests that SwitchMan achieves a better tradeoff between security and usability than existing solutions.

In the privacy protection method based on user collaboration, all participants and collaborators must share the maximum anonymity value set in the anonymous group. No user can get better quality of service by reducing the anonymity requirement. In this paper, a privacy protection algorithm random-QBE, which divides query information into blocks and exchanges randomly, is proposed. Through this method, personalized anonymity, query diversity and location anonymity in user cooperative privacy protection can be realized. And through multi-hop communication between collaborative users, this method can also satisfy the randomness of anonymous location, so that the location of the applicant is no longer located in the center of the anonymous group, which further increases the ability of privacy protection. Experiments show that the algorithm can complete the processing in a relatively short time and is suitable for deployment in real environment to protect user's location privacy.

In this paper, we design NETHCF, a line-rate in-network system for filtering spoofed traffic. NETHCF leverages the opportunity provided by programmable switches to design a novel defense against spoofed IP traffic, and it is highly efficient and adaptive. One key challenge stems from the restrictions of the computational model and memory resources of programmable switches. We address this by decomposing the HCF system into two complementary components-one component for the data plane and another for the control plane. We also aggregate the IP-to-Hop-Count (IP2HC) mapping table for efficient memory usage, and design adaptive mechanisms to handle end-to-end routing changes, IP popularity changes, and network activity dynamics. We have built a prototype on a hardware Tofino switch, and our evaluation demonstrates that NETHCF can achieve line-rate and adaptive traffic filtering with low overheads.

Virtual network function provides tenant with flexible and scalable end-to-end service chaining in the cloud computing and data center environments. However, comparing with traditional hardware network devices, the uncertainty caused by software and virtualization of Network Function Virtualization expands the attack surface, making the network node vulnerable to a certain types of attacks. The existing approaches for solving the problem of reliability are able to reduce the impact of failure of physical devices, but pay little attention to the attack scenario, which could be persistent and covert. In this paper, a heterogeneous backup strategy is brought up, enhancing the intrusion tolerance of NFV SFC by dynamically switching the VNF executor. The validity of the method is verified by simulation and game theory analysis.

The supervisory control and data acquisition (SCADA) network in a smart grid requires to be reliable and efficient to transmit real-time data to the controller. Introducing SDN into a SCADA network helps in deploying novel grid control operations, as well as, their management. As the overall network cannot be transformed to have only SDN-enabled devices overnight because of budget constraints, a systematic deployment methodology is needed. In this work, we present a framework, named SDNSynth, that can design a hybrid network consisting of both legacy forwarding devices and programmable SDN-enabled switches. The design satisfies the resiliency requirements of the SCADA network, which are specified with respect to a set of identified threat vectors. The deployment plan primarily includes the best placements of the SDN-enabled switches. The plan may include one or more links to be installed newly. We model and implement the SDNSynth framework that includes the satisfaction of several requirements and constraints involved in resilient operation of the SCADA. It uses satisfiability modulo theories (SMT) for encoding the synthesis model and solving it. We demonstrate SDNSynth on a case study and evaluate its performance on different synthetic SCADA systems.

The disclosure of an important yet sensitive link may cause serious privacy crisis between two users of a social graph. Only deleting the sensitive link referred to as a target link which is often the attacked target of adversaries is not enough, because the adversarial link prediction can deeply forecast the existence of the missing target link. Thus, to defend some specific adversarial link prediction, a budget limited number of other non-target links should be optimally removed. We first propose a path-based dissimilarity function as the optimizing objective and prove that the greedy link deletion to preserve target link privacy referred to as the GLD2Privacy which has monotonicity and submodularity properties can achieve a near optimal solution. However, emulating all length limited paths between any pair of nodes for GLD2Privacy mechanism is impossible in large scale social graphs. Secondly, we propose a Walk2Privacy mechanism that uses self-avoiding random walk which can efficiently run in large scale graphs to sample the paths of given lengths between the two ends of any missing target link, and based on the sampled paths we select the alternative non-target links being deleted for privacy purpose. Finally, we compose experiments to demonstrate that the Walk2Privacy algorithm can remarkably reduce the time consumption and achieve a very near solution that is achieved by the GLD2Privacy.

Distributed Denial of Service(DDoS) attacks have become most important network security threat as the number of devices are connected to internet increases exponentially and reaching an attack volume approximately very high compared to other attacks. To make the network safe and flexible a new networking infrastructure such as Software Defined Networking (SDN) has come into effect, which relies on centralized controller and decoupling of control and data plane. However due to it's centralized controller it is prone to DDoS attacks, as it makes the decision of forwarding of packets based on rules installed in switch by OpenFlow protocol. Out of all different DDoS attacks, UDP (User Datagram Protocol) flooding constitute the most in recent years. In this paper, we have proposed an entropy based DDoS detection and rate limiting based mitigation for efficient service delivery. We have evaluated using Mininet as emulator and Ryu as controller by taking switch as OpenVswitch and obtained better result in terms of bandwidth utilization and hit ratio which consume network resources to make denial of service.

SDN is new networking concept which has revolutionized the network architecture in recent years. It decouples control plane from data plane. Architectural change provides re-programmability and centralized control management of the network. At the same time it also increases the complexity of underlying physical infrastructure of the network. Unfortunately, the centralized control of the network introduces new vulnerabilities and attacks. Attackers can exploit the limitation of centralized control by DDoS attack on control plane. The entire network can be compromised by DDoS attack. Based on packet entropy, a solution for mitigation of DDoS attack provided in the proposed scheme.

Honeypots have become an important tool for capturing attacks. Hybrid honeypots, including the front end and the back end, are widely used in research because of the scalability of the front end and the high interactivity of the back end. However, traditional hybrid honeypots have some problems that the flow control is difficult and topology simulation is not realistic. This paper proposes a new architecture based on SDN applied to the hybrid honeypot system for network topology simulation and attack traffic migration. Our system uses the good expansibility and controllability of the SDN controller to simulate a large and realistic network to attract attackers and redirect high-level attacks to a high-interaction honeypot for attack capture and further analysis. It improves the deficiencies in the network spoofing technology and flow control technology in the traditional honeynet. Finally, we set up the experimental environment on the mininet and verified the mechanism. The test results show that the system is more intelligent and the traffic migration is more stealthy.

Wireless Networks-on-Chips (NoCs) have emerged as a panacea to the non-scalable multi-hop data transmission paths in traditional wired NoC architectures. Using low-power transceivers in NoC switches, novel Wireless NoC (WiNoC) architectures have been shown to achieve higher energy efficiency with improved peak bandwidth and reduced on-chip data transfer latency. However, using wireless interconnects for data transfer within a chip makes the on-chip communications vulnerable to various security threats from either external attackers or internal hardware Trojans (HTs). In this work, we propose a mechanism to make the wireless communication in a WiNoC secure against persistent jamming based Denial-of-Service attacks from both external and internal attackers. Persistent jamming attacks on the on-chip wireless medium will cause interference in data transfer over the duration of the attack resulting in errors in contiguous bits, known as burst errors. Therefore, we use a burst error correction code to monitor the rate of burst errors received over the wireless medium and deploy a Machine Learning (ML) classifier to detect the persistent jamming attack and distinguish it from random burst errors. In the event of jamming attack, alternate routing strategies are proposed to avoid the DoS attack over the wireless medium, so that a secure data transfer can be sustained even in the presence of jamming. We evaluate the proposed technique on a secure WiNoC in the presence of DoS attacks. It has been observed that with the proposed defense mechanisms, WiNoC can outperform a wired NoC even in presence of attacks in terms of performance and security. On an average, 99.87% attack detection was achieved with the chosen ML Classifiers. A bandwidth degradation of \textbackslashtextless;3% is experienced in the event of internal attack, while the wireless interconnects are disabled in the presence of an external attacker.

Network Function Virtualization (NFV) is a recent concept where virtualization enables the shift from network functions (e.g., routers, switches, load-balancers, proxies) on specialized hardware appliances to software images running on all-purpose, high-volume servers. The resource allocation problem in the NFV environment has received considerable attention in the past years. However, little attention was paid to the security aspects of the problem in spite of the increasing number of vulnerabilities faced by cloud-based applications. Securing the services is an urgent need to completely benefit from the advantages offered by NFV. In this paper, we show how a network service request, composed of a set of service function chains (SFC) should be modified and enriched to take into consideration the security requirements of the supported service. We examine the well-known security best practices and propose a two-step algorithm that extends the initial SFC requests to a more complex chaining model that includes the security requirements of the service.