Biblio

With the fast development of autonomous driving and vehicular communication technologies, intelligent transportation systems that are based on VANET (Vehicular Ad-Hoc Network) have shown great promise. For instance, through V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure) communication, intelligent intersections allow more fine-grained control of vehicle crossings and significantly enhance traffic efficiency. However, the performance and safety of these VANET-based systems could be seriously impaired by communication delays and packet losses, which may be caused by network congestion or by malicious attacks that target communication timing behavior. In this paper, we quantitatively model and analyze some of the timing and security issues in transportation networks with VANET-based intelligent intersections. In particular, we demonstrate how communication delays may affect the performance and safety of a single intersection and of multiple interconnected intersections, and present our delay-tolerant intersection management protocols. We also discuss the issues of such protocols when the vehicles are non-cooperative and how they may be addressed with game theory.

Time-based one-time password (TOTP) systems in use today require storing secrets on both the client and the server. As a result, an attack on the server can expose all second factors for all users in the system. We present T/Key, a time-based one-time password system that requires no secrets on the server. Our work modernizes the classic S/Key system and addresses the challenges in making such a system secure and practical. At the heart of our construction is a new lower bound analyzing the hardness of inverting hash chains composed of independent random functions, which formalizes the security of this widely used primitive. Additionally, we develop a near-optimal algorithm for quickly generating the required elements in a hash chain with little memory on the client. We report on our implementation of T/Key as an Android application. T/Key can be used as a replacement for current TOTP systems, and it remains secure in the event of a server-side compromise. The cost, as with S/Key, is that one-time passwords are longer than the standard six characters used in TOTP.

Cloud Computing represents one of the most significant shifts in information technology and it enables to provide cloud-based security service such as Security-as-a-service (SECaaS). Improving of the cloud computing technologies, the traditional SIEM paradigm is able to shift to cloud-based security services. In this paper, we propose the SIEM architecture that can be deployed to the SECaaS platform which we have been developing for analyzing and recognizing intelligent cyber-threat based on virtualization technologies.

The Internet of Things (IoT) revolution has brought millions of small, low-cost, connected devices into our homes, cities, infrastructure, and more. However, these devices are often plagued by security vulnerabilities that pose threats to user privacy or can threaten the Internet architecture as a whole. Home networks can be particularly vulnerable to these threats as they typically have no network administrator and often contain unpatched or otherwise vulnerable devices. In this paper, we argue that the unique security challenges of home networks require a new network-layer architecture to both protect against external threats and mitigate attacks from compromised devices. We present initial findings based on traffic analysis from a small-scale IoT testbed toward identifying predictable patterns in IoT traffic that may allow construction of a policy-based framework to restrict malicious traffic. Based on our observations, we discuss key features for the design of this architecture to promote future developments in network-layer security in smart home networks.

The trend in computing is towards the use of FPGAs to improve performance at reduced costs. An indication of this is the adoption of FPGAs for data centre and server application acceleration by notable technological giants like Microsoft, Amazon, and Baidu. The continued protection of Intellectual Properties (IPs) on the FPGA has thus become both more important and challenging. To facilitate IP security, FPGA vendors have provided bitstream authentication and encryption. However, advancements in FPGA programming technology have engendered a bitstream manipulation technique like partial bitstream relocation (PBR), which is promising in terms of reducing bitstream storage cost and facilitating adaptability. Meanwhile, encrypted bitstreams are not amenable to PBR. In this paper, we present three methods for performing encrypted PBR with varying overheads of resources and time. These methods ensure that PBR can be applied to bitstreams without losing the protection of IPs.

Increasing interest in cyber-physical systems with integrated computational and physical capabilities that can interact with humans can be identified in research and practice. Since these systems can be classified as safety- and security-critical systems the need for safety and security assurance and certification will grow. Moreover, these systems are typically characterized by fragmentation, interconnectedness, heterogeneity, short release cycles, cross organizational nature and high interference between safety and security requirements. These properties combined with the assurance of compliance to multiple standards, carrying out certification and re-certification, and the lack of an approach to model, document and integrate safety and security requirements represent a major challenge. In order to address this gap we developed a domain agnostic approach to model security and safety requirements in an integrated view to support certification processes during design and run-time phases of cyber-physical systems.

The traditional physical power grid is evolving into a cyber-physical Smart Grid (SG) that links the cyber communication and computational elements with the physical control functions to dynamically integrate varied and geographically distributed energy producers/consumers. In the SG, the cyber elements of Wide Area Measurement Systems (WAMS) are deployed to provide the critical monitoring of the state of power transmission and distribution to accomplish real-time control of the grid. Unfortunately, the increasing adoption of such computing/communication cyber-technologies essential to providing the SG operations also opens the risk of the SG being vulnerable to cyberattacks. In particular, attacks such as Denial-of-Service (DoS) and Distributed DoS (DDoS) are of primary concern for WAMS where such attacks can compromise its safety-critical accuracy and responsiveness characteristics. To prevent DoS/DDoS attacks at the transport and application layer from affecting the WAMS operations, we propose a proactive and robust extension of the Multipath-TCP (MPTCP) transportation protocol that mitigates such attacks by using a novel stream hopping MPTCP mechanism, termed as MPTCP-H. The proposed MPTCP-H hides the open port numbers of the connection from an attacker by renewing (over time) the subflows over new port numbers without perturbing the WAMS data traffic. Our results demonstrate MPTCP-H to be both effective and efficient (for reduced latency and congestion), and also applicable to the communication frameworks of other similar Critical Infrastructures.

Traditional Intrusion Detection Systems (IDSes) are generally implemented on vendor proprietary appliances or middleboxes, which usually lack a general programming interface, and their versatility and flexibility are also very poor. Emerging Network Function Virtualization (NFV) technology can virtualize IDSes and elastically scale them to deal with attack traffic variations. However, existing NFV solutions treat a virtualized IDS as a monolithic piece of software, which could lead to inflexibility and significant waste of resources. In this paper, we propose a novel approach to virtualize IDSes as microservices where the virtualized IDSes can be customized on demand, and the underlying microservices could be shared and scaled independently. We also conduct experiments, which demonstrate that virtualizing IDSes as microservices can gain greater flexibility and resource efficiency.

In fiber-optic communication networks, research on data security at lower layers of the protocol stack and in particular at the physical layer by means of information-theoretic concepts is only in the beginning. Nevertheless, it has recently attracted quite some attention as it holds the promise of providing unconditional, perfect security without the need for secret key exchanges. In this paper, we analyze some important constraints that such concepts put on a potential implementation of physical-layer security. We review the fundamentals of physical-layer security on the basis of the commonly used AWGN wiretap channel model. For such channel model we summarize the security metrics which are typically used in information theory and in particular recall that, for secure communication over the AWGN channel, the legitimate receiver needs an SNR advantage over the eavesdropper. Next, we relate the information theoretic metrics to physically measurable quantities in optical communications engineering, namely optical signal-to-noise ratio (OSNR) and bit-error ratio (BER), and translate the information-theoretic wiretap scenario to a simple real-world point-to-point optical transmission link in which part of the light is wiretapped using a bend coupler. We investigate the achievable OSNR advantage under realistic assumptions for fiber loss, tap ratio, and noise budget and find that secure transmission is limited to a distance of a few tens of kilometers in this case. The maximum secure transmission distance decreases with an increasing tap ratio chosen by the eavesdropper. This can be only counteracted by monitoring the link loss towards the legitimate receiver which would force the eavesdropper to choose small tap ratios in order to remain undetected. In an outlook towards further research directions we identify information-theoretic approaches which could potentially allow to realize physical-layer security in more generalized scenarios or over longer distances.

SDN networks rely mainly on a set of software defined modules, running on generic hardware platforms, and managed by a central SDN controller. The tight coupling and lack of isolation between the controller and the underlying host limit the controller resilience against host-based attacks and failures. That controller is a single point of failure and a target for attackers. ``Linux-containers'' is a successful thin virtualization technique that enables encapsulated, host-isolated execution-environments for running applications. In this paper we present PAFR, a controller sandboxing mechanism based on Linux-containers. PAFR enables controller/host isolation, plug-and-play operation, failure-and-attack-resilient execution, and fast recovery. PAFR employs and manages live remote checkpointing and migration between different hosts to evade failures and attacks. Experiments and simulations show that the frequent employment of PAFR's live-migration minimizes the chance of successful attack/failure with limited to no impact on network performance.

A long time ago Industrial Control Systems were in a safe place due to the use of proprietary technology and physical isolation. This situation has changed dramatically and the systems are nowadays often prone to severe attacks executed from remote locations. In many cases, intrusions remain undetected for a long time and this allows the adversary to meticulously prepare an attack and maximize its destructiveness. The ability to detect an attack in its early stages thus has a high potential to significantly reduce its impact. To this end, we propose a holistic, multi-layered, security monitoring and mitigation framework spanning the physical- and cyber domain. The comprehensiveness of the approach demands for scalability measures built-in by design. In this paper we present how scalability is addressed by an architecture that enforces geographically decentralized data reduction approaches that can be dynamically adjusted to the currently perceived context. A specific focus is put on a robust and resilient solution to orchestrate dynamic configuration updates. Experimental results based on a prototype implementation show the feasibility of the approach.

In this paper, we describe an efficient methodology to guide investigators during network forensic analysis. To this end, we introduce the concept of core attack graph, a compact representation of the main routes an attacker can take towards specific network targets. Such compactness allows forensic investigators to focus their efforts on critical nodes that are more likely to be part of attack paths, thus reducing the overall number of nodes (devices, network privileges) that need to be examined. Nevertheless, core graphs also allow investigators to hierarchically explore the graph in order to retrieve different levels of summarised information. We have evaluated our approach over different network topologies varying parameters such as network size, density, and forensic evaluation threshold. Our results demonstrate that we can achieve the same level of accuracy provided by standard logical attack graphs while significantly reducing the exploration rate of the network.

Recently, due to the increase of outsourcing in IC design, it has been reported that malicious third-party vendors often insert hardware Trojans into their ICs. How to detect them is a strong concern in IC design process. The features of hardware-Trojan infected nets (or Trojan nets) in ICs often differ from those of normal nets. To classify all the nets in netlists designed by third-party vendors into Trojan ones and normal ones, we have to extract effective Trojan features from Trojan nets. In this paper, we first propose 51 Trojan features which describe Trojan nets from netlists. Based on the importance values obtained from the random forest classifier, we extract the best set of 11 Trojan features out of the 51 features which can effectively detect Trojan nets, maximizing the F-measures. By using the 11 Trojan features extracted, the machine-learning based hardware Trojan classifier has achieved at most 100% true positive rate as well as 100% true negative rate in several TrustHUB benchmarks and obtained the average F-measure of 74.6%, which realizes the best values among existing machine-learning-based hardware-Trojan detection methods.

Internet-of-Things devices often collect and transmit sensitive information like camera footage, health monitoring data, or whether someone is home. These devices protect data in transit with end-to-end encryption, typically using TLS connections between devices and associated cloud services. But these TLS connections also prevent device owners from observing what their own devices are saying about them. Unlike in traditional Internet applications, where the end user controls one end of a connection (e.g., their web browser) and can observe its communication, Internet-of-Things vendors typically control the software in both the device and the cloud. As a result, owners have no way to audit the behavior of their own devices, leaving them little choice but to hope that these devices are transmitting only what they should. This paper presents TLS–Rotate and Release (TLS-RaR), a system that allows device owners (e.g., consumers, security researchers, and consumer watchdogs) to authorize devices, called auditors, to decrypt and verify recent TLS traffic without compromising future traffic. Unlike prior work, TLS-RaR requires no changes to TLS's wire format or cipher suites, and it allows the device's owner to conduct a surprise inspection of recent traffic, without prior notice to the device that its communications will be audited.

The rapid development of cloud computing has resulted in the emergence of numerous web services on the Internet. Selecting a suitable cloud service is becoming a major problem for users especially non-professionals. Quality of Service (QoS) is considered to be the criterion for judging web services. There are several Collaborative Filtering (CF)-based QoS prediction methods proposed in recent years. QoS values among different users may vary largely due to the network and geographical location. Moreover, QoS data provided by untrusted users will definitely affect the prediction accuracy. However, most existing methods seldom take both facts into consideration. In this paper, we present a trust-aware and location-based approach for web service QoS prediction. A trust value for each user is evaluated before the similarity calculation and the location is taken into account in similar neighbors selecting. A series of experiments are performed based on a realworld QoS dataset including 339 service users and 5,825 services. The experimental analysis shows that the accuracy of our method is much higher than other CF-based methods.

Successful deployment of Low power and Lossy Networks (LLNs) requires self-organising, self-configuring, security, and mobility support. However, these characteristics can be exploited to perform security attacks against the Routing Protocol for Low-Power and Lossy Networks (RPL). In this paper, we address the lack of strong identity and security mechanisms in RPL. We first demonstrate by simulation the impact of Sybil-Mobile attack, namely SybM, on RPL with respect to control overhead, packet delivery and energy consumption. Then, we introduce a new Intrusion Detection System (IDS) scheme for RPL, named Trust-based IDS (T-IDS). T-IDS is a distributed, cooperative and hierarchical trust-based IDS, which can detect novel intrusions by comparing network behavior deviations. In T-IDS, each node is considered as monitoring node and collaborates with his peers to detect intrusions and report them to a 6LoWPAN Border Router (6BR). In our solution, we introduced a new timer and minor extensions to RPL messages format to deal with mobility, identity and multicast issues. In addition, each node is equipped with a Trusted Platform Module co-processor to handle identification and off-load security related computation and storage.

It is hard to set up an end-to-end connection between source and destination in Opportunistic Networks, due to dynamic network topology and the lack of infrastructure. Instead, the store-carry-forward mechanism is used to achieve communication. Namely, communication in Opportunistic Networks relies on the cooperation among nodes. Correspondingly, Opportunistic Networks have some issues like long delays, packet loss and so on, which lead to many challenges in Opportunistic Networks. However, malicious nodes do not follow the routing rules, or refuse to cooperate with benign nodes. Some misbehaviors like black-hole attack, gray-hole attack may arbitrarily bloat their delivery competency to intercept and drop data. Selfishness in Opportunistic Networks will also drop some data from other nodes. These misbehaviors will seriously affect network performance like the delivery success ratio. In this paper, we design a Trust-based Routing Protocol (TRP), combined with various utility algorithms, to more comprehensively evaluate the competency of a candidate node and effectively reduce negative effects by malicious nodes. In simulation, we compare TRP with other protocols, and shows that our protocol is effective for misbehaviors.

We propose an approach to enforce security in disruption- and delay-tolerant networks (DTNs) where long delays, high packet drop rates, unavailability of central trusted entity etc. make traditional approaches unfeasible. We use trust model based on subjective logic to continuously evaluate trustworthiness of security credentials issued in distributed manner by network participants to deal with absence of centralised trusted authorities.

Client-side JavaScript has become ubiquitous in web applications to improve user experience and reduce server load. However, since clients are untrusted, servers cannot rely on the confidentiality or integrity of client-side JavaScript code and the data that it operates on. For example, client-side input validation must be repeated at server side, and confidential business logic cannot be offloaded. In this paper, we present TrustJS, a framework that enables trustworthy execution of security-sensitive JavaScript inside commodity browsers. TrustJS leverages trusted hardware support provided by Intel SGX to protect the client-side execution of JavaScript, enabling a flexible partitioning of web application code. We present the design of TrustJS and provide initial evaluation results, showing that trustworthy JavaScript offloading can further improve user experience and conserve more server resources.

Numerous event-based probing methods exist for cloud computing environments allowing a hypervisor to gain insight into guest activities. Such event-based probing has been shown to be useful for detecting attacks, system hangs through watchdogs, and for inserting exploit detectors before a system can be patched, among others. Here, we illustrate how to use such probing for trustworthy logging and highlight some of the challenges that existing event-based probing mechanisms do not address. Challenges include ensuring a probe inserted at given address is trustworthy despite the lack of attestation available for probes that have been inserted dynamically. We show how probes can be inserted to ensure proper logging of every invocation of a probed instruction. When combined with attested boot of the hypervisor and guest machines, we can ensure the output stream of monitored events is trustworthy. Using these techniques we build a trustworthy log of certain guest-system-call events. The log powers a cloud-tuned Intrusion Detection System (IDS). New event types are identified that must be added to existing probing systems to ensure attempts to circumvent probes within the guest appear in the log. We highlight the overhead penalties paid by guests to increase guarantees of log completeness when faced with attacks on the guest kernel. Promising results (less that 10% for guests) are shown when a guest relaxes the trade-off between log completeness and overhead. Our demonstrative IDS detects common attack scenarios with simple policies built using our guest behavior recording system.

This paper describes an experiment carried out to demonstrate robustness and trustworthiness of an orchestrated two-layer network test-bed (PROnet). A Robotic Operating System Industrial (ROS-I) distributed application makes use of end-to-end flow services offered by PROnet. The PROnet Orchestrator is used to provision reliable end-to-end Ethernet flows to support the ROS-I application required data exchange. For maximum reliability, the Orchestrator provisions network resource redundancy at both layers, i.e., Ethernet and optical. Experimental results show that the robotic application is not interrupted by a fiber outage.

The advancement in technology has changed how people work and what software and hardware people use. From conventional personal computer to GPU, hardware technology and capability have dramatically improved so does the operating systems that come along. Unfortunately, current industry practice to compare OS is performed with single perspective. It is either benchmark the hardware level performance or performs penetration testing to check the security features of an OS. This rigid method of benchmarking does not really reflect the true performance of an OS as the performance analysis is not comprehensive and conclusive. To illustrate this deficiency, the study performed hardware level and operational level benchmarking on Windows XP, Windows 7 and Windows 8 and the results indicate that there are instances where Windows XP excels over its newer counterparts. Overall, the research shows Windows 8 is a superior OS in comparison to its predecessors running on the same hardware. Furthermore, the findings also show that the automated benchmarking tools are proved less efficient benchmark systems that run on Windows XP and older OS as they do not support DirectX 11 and other advanced features that the hardware supports. There lies the need to have a unified benchmarking approach to compare other aspects of OS such as user oriented tasks and security parameters to provide a complete comparison. Therefore, this paper is proposing a unified approach for Operating System (OS) comparisons with the help of a Windows OS case study. This unified approach includes comparison of OS from three aspects which are; hardware level, operational level performance and security tests.

Distributed Denial of Service (DDoS) attacks are a popular and inexpensive form of cyber attacks. Application layer DDoS attacks utilize legitimate application layer requests to overwhelm a web server. These attacks are a major threat to Internet applications and web services. The main goal of these attacks is to make the services unavailable to legitimate users by overwhelming the resources on a web server. They look valid in connection and protocol characteristics, which makes them difficult to detect. In this paper, we propose a detection method for the application layer DDoS attacks, which is based on user behavior anomaly detection. We extract instances of user behaviors requesting resources from HTTP web server logs. We apply the Principle Component Analysis (PCA) subspace anomaly detection method for the detection of anomalous behavior instances. Web server logs from a web server hosting a student resource portal were collected as experimental data. We also generated nine different HTTP DDoS attacks through penetration testing. Our performance results on the collected data show that using PCAsubspace anomaly detection on user behavior data can detect application layer DDoS attacks, even if they are trying to mimic a normal user's behavior at some level.

Friendly jamming is a physical layer security technique that utilizes extra available nodes to jam any eavesdroppers. This paper considers the use of additional available nodes as friendly jammers in order to improve the security performance of a route through a wireless area network. One of the unresolved technical challenges is the combining of security metrics with typical service quality metrics. In this context, this paper considers the problem of routing through a D2D network while jointly minimizing the secrecy outage probability (SOP) and connection outage probability (COP), using friendly jamming to improve the SOP of each link. The jamming powers are determined to place nulls at friendly receivers while maximizing the power to eavesdroppers. Then the route metrics are derived, and the problem is framed as a convex optimization problem. We also consider that not all network users equally value SOP and COP, and so introduce an auxiliary variable to tune the optimization between the two metrics.

Due to the increasing complexity of design process, outsourcing, and use of third-party blocks, it becomes harder and harder to prevent Trojan insertion and other malicious design modifications. In this paper, we propose to deploy security invariant as carried proof to prevent and detect Trojans and malicious attacks and to ensure the security of hardware design. Non-interference with down-grading policy is checked for confidentiality. Contrary to existing approaches by type checking, we develop a method to model-check a simple safety property on a composed machine. Down-grading is handled in a better way in model-checking and the effectiveness of our approach is demonstrated on various Verilog benchmarks.