Biblio

The notion of commitment is widely studied as a high-level abstraction for modeling multiagent interaction.  An important challenge is supporting flexible decentralized enactments of commitment specifications.  In this paper, we combine recent advances on specifying commitments and information protocols.  Specifically, we contribute Tosca, a technique for automatically synthesizing information protocols from commitment specifications. Our main result is that the synthesized protocols support commitment alignment, which is the idea that agents must make compatible inferences about their commitments despite decentralization.

The semiconductor industry is fully globalized and integrated circuits (ICs) are commonly defined, designed and fabricated in different premises across the world. This reduces production costs, but also exposes ICs to supply chain attacks, where insiders introduce malicious circuitry into the final products. Additionally, despite extensive post-fabrication testing, it is not uncommon for ICs with subtle fabrication errors to make it into production systems. While many systems may be able to tolerate a few byzantine components, this is not the case for cryptographic hardware, storing and computing on confidential data. For this reason, many error and backdoor detection techniques have been proposed over the years. So far all attempts have been either quickly circumvented, or come with unrealistically high manufacturing costs and complexity. This paper proposes Myst, a practical high-assurance architecture, that uses commercial off-the-shelf (COTS) hardware, and provides strong security guarantees, even in the presence of multiple malicious or faulty components. The key idea is to combine protective-redundancy with modern threshold cryptographic techniques to build a system tolerant to hardware trojans and errors. To evaluate our design, we build a Hardware Security Module that provides the highest level of assurance possible with COTS components. Specifically, we employ more than a hundred COTS secure cryptocoprocessors, verified to FIPS140-2 Level 4 tamper-resistance standards, and use them to realize high-confidentiality random number generation, key derivation, public key decryption and signing. Our experiments show a reasonable computational overhead (less than 1% for both Decryption and Signing) and an exponential increase in backdoor-tolerance as more ICs are added.

Due to the user-interface limitations of wearable devices, voice-based interfaces are becoming more common; speaker recognition may then address the authentication requirements of wearable applications. Wearable devices have small form factor, limited energy budget and limited computational capacity. In this paper, we examine the challenge of computing speaker recognition on small wearable platforms, and specifically, reducing resource use (energy use, response time) by trimming the input through careful feature selections. For our experiments, we analyze four different feature-selection algorithms and three different feature sets for speaker identification and speaker verification. Our results show that Principal Component Analysis (PCA) with frequency-domain features had the highest accuracy, Pearson Correlation (PC) with time-domain features had the lowest energy use, and recursive feature elimination (RFE) with frequency-domain features had the least latency. Our results can guide developers to choose feature sets and configurations for speaker-authentication algorithms on wearable platforms.

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 growth in cloud-based services tailored for users means more and more personal data is being exploited, and with this comes the need to better handle user privacy. Software technologies concentrating on privacy preservation typically present a one-size fits all solution. However, users have different viewpoints of what privacy means to them and therefore, configurable and dynamic privacy preserving solutions have the potential to create useful and tailored services without breaching any user's privacy. In this paper, we present a model of user-centered privacy that can be used to analyse a service's behaviour against user preferences, such that a user can be informed of the privacy implications of that service and what fine-grained actions they can take to maintain their privacy. We show through study that the user-based privacy model can: i) provide customizable privacy aligned with user needs; and ii) identify potential privacy breaches.

Software security is an important aspect of ensuring software quality. The goal of this study is to help developers evaluate software security using traceable patterns and software metrics during development. The concept of traceable patterns is similar to design patterns but they can be automatically recognized and extracted from source code. If these patterns can better predict vulnerable code compared to traditional software metrics, they can be used in developing a vulnerability prediction model to classify code as vulnerable or not. By analyzing and comparing the performance of traceable patterns with metrics, we propose a vulnerability prediction model. This study explores the performance of some code patterns in vulnerability prediction and compares them with traditional software metrics. We use the findings to build an effective vulnerability prediction model. We evaluate security vulnerabilities reported for Apache Tomcat, Apache CXF and three stand-alone Java web applications. We use machine learning and statistical techniques for predicting vulnerabilities using traceable patterns and metrics as features. We found that patterns have a lower false negative rate and higher recall in detecting vulnerable code than the traditional software metrics.

Security in smartphones has become one of the major concerns, with prolific growth in its usage scenario. Many applications are available for Android users to protect their applications and data. But all these security applications are not easily accessible for persons with disabilities. For persons with color blindness, authentication mechanisms pose user interface related issues. Color blind users find the inaccessible and complex design in the interface difficult to access and interpret mobile locks. This paper focuses on a novel method for providing color and touch sensitivity based dot pattern lock. This Model automatically replaces the existing display style of a pattern lock with a new user preferred color combination. In addition Pressure Gradient Input (PGI) has been incorporated to enhance authentication strength. The feedback collected from users shows that this accessible security application is easy to use without any major access barrier.

Software-defined networking (SDN) overcomes many limitations of traditional networking architectures because of its programmable and flexible nature. Security applications,for instance, can dynamically reprogram a network to respond to ongoing threats in real time. However, the same flexibility also creates risk, since it can be used against the network. Current SDN architectures potentially allow adversaries to disrupt one or more SDN system components and to hide their actions in doing so. That makes assurance and reasoning about past network
events more difficult, if not impossible. In this paper, we argue that an SDN architecture must incorporate various notions of accountability for achieving systemwide cyber resiliency goals.
We analyze accountability based on a conceptual framework, and we identify how that analysis fits in with the SDN architecture’s entities and processes. We further consider a case study in which accountability is necessary for SDN network applications, and we discuss the limits of current approaches.

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.

To reshape energy systems towards renewable energy resources, decision makers need to decide today on how to make the transition. Energy scenarios are widely used to guide decision making in this context. While considerable effort has been put into developing energy scenarios, researchers have pointed out three requirements for energy scenarios that are not fulfilled satisfactorily yet: The development and evaluation of energy scenarios should (1) incorporate the concept of sustainability, (2) provide decision support in a transparent way and (3) be replicable for other researchers. To meet these requirements, we combine different methodological approaches: story-and-simulation (SAS) scenarios, multi-criteria decision-making (MCDM), information modeling and co-simulation. We show in this paper how the combination of these methods can lead to an integrated approach for sustainability evaluation of energy scenarios with automated information exchange. Our approach consists of a sustainability evaluation process (SEP) and an information model for modeling dependencies. The objectives are to guide decisions towards sustainable development of the energy sector and to make the scenario and decision support processes more transparent for both decision makers and researchers.

There has been increasing interest in adopting BlockChain (BC), that underpins the crypto-currency Bitcoin, in Internet of Things (IoT) for security and privacy. However, BCs are computationally expensive and involve high bandwidth overhead and delays, which are not suitable for most IoT devices. This paper proposes a lightweight BC-based architecture for IoT that virtually eliminates the overheads of classic BC, while maintaining most of its security and privacy benefits. IoT devices benefit from a private immutable ledger, that acts similar to BC but is managed centrally, to optimize energy consumption. High resource devices create an overlay network to implement a publicly accessible distributed BC that ensures end-to-end security and privacy. The proposed architecture uses distributed trust to reduce the block validation processing time. We explore our approach in a smart home setting as a representative case study for broader IoT applications. Qualitative evaluation of the architecture under common threat models highlights its effectiveness in providing security and privacy for IoT applications. Simulations demonstrate that our method decreases packet and processing overhead significantly compared to the BC implementation used in Bitcoin.

Many modern defenses rely on address space layout randomization (ASLR) to efficiently hide security-sensitive metadata in the address space. Absent implementation flaws, an attacker can only bypass such defenses by repeatedly probing the address space for mapped (security-sensitive) regions, incurring a noisy application crash on any wrong guess. Recent work shows that modern applications contain idioms that allow the construction of crash-resistant code primitives, allowing an attacker to efficiently probe the address space without causing any visible crash. In this paper, we classify different crash-resistant primitives and show that this problem is much more prominent than previously assumed. More specifically, we show that rather than relying on labor-intensive source code inspection to find a few "hidden" application-specific primitives, an attacker can find such primitives semi-automatically, on many classes of real-world programs, at the binary level. To support our claims, we develop methods to locate such primitives in real-world binaries. We successfully identified 29 new potential primitives and constructed proof-of-concept exploits for four of them.

Establishing and operating an Information Security Management System (ISMS) to protect information values and information systems is in itself a challenge for larger enterprises and small and medium sized businesses alike. A high level of automation is required to reduce operational efforts to an acceptable level when implementing an ISMS. In this paper we present the ADAMANT framework to increase automation in information security management as a whole by establishing a continuous risk-driven and context-aware ISMS that not only automates security controls but considers all highly interconnected information security management tasks. We further illustrate how ADAMANT is suited to establish an ISO 27001 compliant ISMS for small and medium-sized enterprises and how not only the monitoring of security controls but a majority of ISMS related activities can be supported through automated process execution and workflow enactment.

Building the Internet of Things requires deploying a huge number of objects with full or limited connectivity to the Internet. Given that these objects are exposed to attackers and generally not secured-by-design, it is essential to be able to update them, to patch their vulnerabilities and to prevent hackers from enrolling them into botnets. Ideally, the update infrastructure should implement the CIA triad properties, i.e., confidentiality, integrity and availability. In this work, we investigate how the use of a blockchain infrastructure can meet these requirements, with a focus on availability. In addition, we propose a peer-to-peer mechanism, to spread updates between objects that have limited access to the Internet. Finally, we give an overview of our ongoing prototype implementation.

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.

Data assurance and resilience are crucial security issues in cloud-based IoT applications. With the widespread adoption of drones in IoT scenarios such as warfare, agriculture and delivery, effective solutions to protect data integrity and communications between drones and the control system have been in urgent demand to prevent potential vulnerabilities that may cause heavy losses. To secure drone communication during data collection and transmission, as well as preserve the integrity of collected data, we propose a distributed solution by utilizing blockchain technology along with the traditional cloud server. Instead of registering the drone itself to the blockchain, we anchor the hashed data records collected from drones to the blockchain network and generate a blockchain receipt for each data record stored in the cloud, reducing the burden of moving drones with the limit of battery and process capability while gaining enhanced security guarantee of the data. This paper presents the idea of securing drone data collection and communication in combination with a public blockchain for provisioning data integrity and cloud auditing. The evaluation shows that our system is a reliable and distributed system for drone data assurance and resilience with acceptable overhead and scalability for a large number of drones.

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.

In this demo, we address the problem of detecting anomalies on the Internet backbone in near real-time. Many of today's incidents may only become visible from inspecting multiple data sources and by considering multiple vantage points simultaneously. We present a setup based on the distributed forensic platform VAST that was extended to import various data streams from passive measurements and incident reporting at multiple locations, and perform an effective correlation analysis shortly after the data becomes exposed to our queries.

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.