Visible to the public Biblio

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2021-09-17
Christie V, Samuel H., Smirnova, Daria, Chopra, Amit K., Singh, Munindar P..  2020.  Protocols Over Things: A Decentralized Programming Model for the Internet of Things. 53:60–68.
Current programming models for developing Internet of Things (IoT) applications are logically centralized and ill-suited for most IoT applications. We contribute Protocols over Things, a decentralized programming model that represents an IoT application via a protocol between the parties involved and provides improved performance over network-level delivery guarantees.
Conference Name: Computer
2021-03-29
Agirre, I..  2020.  Safe and secure software updates on high-performance embedded systems. 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). :68—69.

The next generation of dependable embedded systems feature autonomy and higher levels of interconnection. Autonomy is commonly achieved with the support of artificial intelligence algorithms that pose high computing demands on the hardware platform, reaching a high performance scale. This involves a dramatic increase in software and hardware complexity, fact that together with the novelty of the technology, raises serious concerns regarding system dependability. Traditional approaches for certification require to demonstrate that the system will be acceptably safe to operate before it is deployed into service. The nature of autonomous systems, with potentially infinite scenarios, configurations and unanticipated interactions, makes it increasingly difficult to support such claim at design time. In this context, the extended networking technologies can be exploited to collect post-deployment evidence that serve to oversee whether safety assumptions are preserved during operation and to continuously improve the system through regular software updates. These software updates are not only convenient for critical bug fixing but also necessary for keeping the interconnected system resilient against security threats. However, such approach requires a recondition of the traditional certification practices.

2021-02-01
Papadopoulos, A. V., Esterle, L..  2020.  Situational Trust in Self-aware Collaborating Systems. 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). :91–94.
Trust among humans affects the way we interact with each other. In autonomous systems, this trust is often predefined and hard-coded before the systems are deployed. However, when systems encounter unfolding situations, requiring them to interact with others, a notion of trust will be inevitable. In this paper, we discuss trust as a fundamental measure to enable an autonomous system to decide whether or not to interact with another system, whether biological or artificial. These decisions become increasingly important when continuously integrating with others during runtime.
2020-12-17
Sandoval, S., Thulasiraman, P..  2019.  Cyber Security Assessment of the Robot Operating System 2 for Aerial Networks. 2019 IEEE International Systems Conference (SysCon). :1—8.

The Robot Operating System (ROS) is a widely adopted standard robotic middleware. However, its preliminary design is devoid of any network security features. Military grade unmanned systems must be guarded against network threats. ROS 2 is built upon the Data Distribution Service (DDS) standard and is designed to provide solutions to identified ROS 1 security vulnerabilities by incorporating authentication, encryption, and process profile features, which rely on public key infrastructure. The Department of Defense is looking to use ROS 2 for its military-centric robotics platform. This paper seeks to demonstrate that ROS 2 and its DDS security architecture can serve as a functional platform for use in military grade unmanned systems, particularly in unmanned Naval aerial swarms. In this paper, we focus on the viability of ROS 2 to safeguard communications between swarms and a ground control station (GCS). We test ROS 2's ability to mitigate and withstand certain cyber threats, specifically that of rogue nodes injecting unauthorized data and accessing services that will disable parts of the UAV swarm. We use the Gazebo robotics simulator to target individual UAVs to ascertain the effectiveness of our attack vectors under specific conditions. We demonstrate the effectiveness of ROS 2 in mitigating the chosen attack vectors but observed a measurable operational delay within our simulations.

2020-12-11
Ghose, N., Lazos, L., Rozenblit, J., Breiger, R..  2019.  Multimodal Graph Analysis of Cyber Attacks. 2019 Spring Simulation Conference (SpringSim). :1—12.

The limited information on the cyberattacks available in the unclassified regime, hardens standardizing the analysis. We address the problem of modeling and analyzing cyberattacks using a multimodal graph approach. We formulate the stages, actors, and outcomes of cyberattacks as a multimodal graph. Multimodal graph nodes include cyberattack victims, adversaries, autonomous systems, and the observed cyber events. In multimodal graphs, single-modality graphs are interconnected according to their interaction. We apply community and centrality analysis on the graph to obtain in-depth insights into the attack. In community analysis, we cluster those nodes that exhibit “strong” inter-modal ties. We further use centrality to rank the nodes according to their importance. Classifying nodes according to centrality provides the progression of the attack from the attacker to the targeted nodes. We apply our methods to two popular case studies, namely GhostNet and Putter Panda and demonstrate a clear distinction in the attack stages.

2020-12-01
Attia, M., Hossny, M., Nahavandi, S., Dalvand, M., Asadi, H..  2018.  Towards Trusted Autonomous Surgical Robots. 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). :4083—4088.

Throughout the last few decades, a breakthrough took place in the field of autonomous robotics. They have been introduced to perform dangerous, dirty, difficult, and dull tasks, to serve the community. They have been also used to address health-care related tasks, such as enhancing the surgical skills of the surgeons and enabling surgeries in remote areas. This may help to perform operations in remote areas efficiently and in timely manner, with or without human intervention. One of the main advantages is that robots are not affected with human-related problems such as: fatigue or momentary lapses of attention. Thus, they can perform repeated and tedious operations. In this paper, we propose a framework to establish trust in autonomous medical robots based on mutual understanding and transparency in decision making.

2020-11-23
Wang, M., Hussein, A., Rojas, R. F., Shafi, K., Abbass, H. A..  2018.  EEG-Based Neural Correlates of Trust in Human-Autonomy Interaction. 2018 IEEE Symposium Series on Computational Intelligence (SSCI). :350–357.
This paper aims at identifying the neural correlates of human trust in autonomous systems using electroencephalography (EEG) signals. Quantifying the relationship between trust and brain activities allows for real-time assessment of human trust in automation. This line of effort contributes to the design of trusted autonomous systems, and more generally, modeling the interaction in human-autonomy interaction. To study the correlates of trust, we use an investment game in which artificial agents with different levels of trustworthiness are employed. We collected EEG signals from 10 human subjects while they are playing the game; then computed three types of features from these signals considering the signal time-dependency, complexity and power spectrum using an autoregressive model (AR), sample entropy and Fourier analysis, respectively. Results of a mixed model analysis showed significant correlation between human trust and EEG features from certain electrodes. The frontal and the occipital area are identified as the predominant brain areas correlated with trust.
2020-10-05
Kanellopoulos, Aris, Vamvoudakis, Kyriakos G., Gupta, Vijay.  2019.  Decentralized Verification for Dissipativity of Cascade Interconnected Systems. 2019 IEEE 58th Conference on Decision and Control (CDC). :3629—3634.

In this paper, we consider the problem of decentralized verification for large-scale cascade interconnections of linear subsystems such that dissipativity properties of the overall system are guaranteed with minimum knowledge of the dynamics. In order to achieve compositionality, we distribute the verification process among the individual subsystems, which utilize limited information received locally from their immediate neighbors. Furthermore, to obviate the need for full knowledge of the subsystem parameters, each decentralized verification rule employs a model-free learning structure; a reinforcement learning algorithm that allows for online evaluation of the appropriate storage function that can be used to verify dissipativity of the system up to that point. Finally, we show how the interconnection can be extended by adding learning-enabled subsystems while ensuring dissipativity.

2020-09-28
Gawanmeh, Amjad, Alomari, Ahmad.  2018.  Taxonomy Analysis of Security Aspects in Cyber Physical Systems Applications. 2018 IEEE International Conference on Communications Workshops (ICC Workshops). :1–6.
The notion of Cyber Physical Systems is based on using recent computing, communication, and control methods to design and operate intelligent and autonomous systems that can provide using innovative technologies. The existence of several critical applications within the scope of cyber physical systems results in many security and privacy concerns. On the other hand, the distributive nature of these CPS increases security risks. In addition, certain CPS, such as medical ones, generate and process sensitive data regularly, hence, this data must be protected at all levels of generation, processing, and transmission. In this paper, we present a taxonomy based analysis for the state of the art work on security issues in CPS. We identify four types of analysis for security issues in CPS: Modeling, Detection, Prevention, and Response. In addition, we identified six applications of CPS where security is relevant: eHealth and medical, smart grid and power related, vehicular technologies, industrial control and manufacturing, autonomous systems and UAVs, and finally IoT related issues. Then we mapped existing works in the literature into these categories.
2020-07-16
Xiao, Jiaping, Jiang, Jianchun.  2018.  Real-time Security Evaluation for Unmanned Aircraft Systems under Data-driven Attacks*. 2018 13th World Congress on Intelligent Control and Automation (WCICA). :842—847.

With rapid advances in the fields of the Internet of Things and autonomous systems, the network security of cyber-physical systems(CPS) becomes more and more important. This paper focuses on the real-time security evaluation for unmanned aircraft systems which are cyber-physical systems relying on information communication and control system to achieve autonomous decision making. Our problem formulation is motivated by scenarios involving autonomous unmanned aerial vehicles(UAVs) working continuously under data-driven attacks when in an open, uncertain, and even hostile environment. Firstly, we investigated the state estimation method in CPS integrated with data-driven attacks model, and then proposed a real-time security scoring algorithm to evaluate the security condition of unmanned aircraft systems under different threat patterns, considering the vulnerability of the systems and consequences brought by data attacks. Our simulation in a UAV illustrated the efficiency and reliability of the algorithm.

2020-06-29
Giri, Nupur, Jaisinghani, Rahul, Kriplani, Rohit, Ramrakhyani, Tarun, Bhatia, Vinay.  2019.  Distributed Denial Of Service(DDoS) Mitigation in Software Defined Network using Blockchain. 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :673–678.
A DDoS attack is a spiteful attempt to disrupt legitimate traffic to a server by overwhelming the target with a flood of requests from geographically dispersed systems. Today attackers prefer DDoS attack methods to disrupt target services as they generate GBs to TBs of random data to flood the target. In existing mitigation strategies, because of lack of resources and not having the flexibility to cope with attacks by themselves, they are not considered to be that effective. So effective DDoS mitigation techniques can be provided using emerging technologies such as blockchain and SDN(Software-Defined Networking). We propose an architecture where a smart contract is deployed in a private blockchain, which facilitates a collaborative DDoS mitigation architecture across multiple network domains. Blockchain application is used as an additional security service. With Blockchain, shared protection is enabled among all hosts. With help of smart contracts, rules are distributed among all hosts. In addition, SDN can effectively enable services and security policies dynamically. This mechanism provides ASes(Autonomous Systems) the possibility to deploy their own DPS(DDoS Prevention Service) and there is no need to transfer control of the network to the third party. This paper focuses on the challenges of protecting a hybridized enterprise from the ravages of rapidly evolving Distributed Denial of Service(DDoS) attack.
2020-02-26
Saad, Muhammad, Anwar, Afsah, Ahmad, Ashar, Alasmary, Hisham, Yuksel, Murat, Mohaisen, Aziz.  2019.  RouteChain: Towards Blockchain-Based Secure and Efficient BGP Routing. 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC). :210–218.

Routing on the Internet is defined among autonomous systems (ASes) based on a weak trust model where it is assumed that ASes are honest. While this trust model strengthens the connectivity among ASes, it results in an attack surface which is exploited by malicious entities to hijacking routing paths. One such attack is known as the BGP prefix hijacking, in which a malicious AS broadcasts IP prefixes that belong to a target AS, thereby hijacking its traffic. In this paper, we proposeRouteChain: a blockchain-based secure BGP routing system that counters BGP hijacking and maintains a consistent view of the Internet routing paths. Towards that, we leverage provenance assurance and tamper-proof properties of blockchains to augment trust among ASes. We group ASes based on their geographical (network) proximity and construct a bihierarchical blockchain model that detects false prefixes prior to their spread over the Internet. We validate strengths of our design by simulations and show its effectiveness by drawing a case study with the Youtube hijacking of 2008. Our proposed scheme is a standalone service that can be incrementally deployed without the need of a central authority.

2019-12-18
Essaid, Meryam, Kim, DaeYong, Maeng, Soo Hoon, Park, Sejin, Ju, Hong Taek.  2019.  A Collaborative DDoS Mitigation Solution Based on Ethereum Smart Contract and RNN-LSTM. 2019 20th Asia-Pacific Network Operations and Management Symposium (APNOMS). :1–6.

Recently Distributed Denial-of-Service (DDoS) are becoming more and more sophisticated, which makes the existing defence systems not capable of tolerating by themselves against wide-ranging attacks. Thus, collaborative protection mitigation has become a needed alternative to extend defence mechanisms. However, the existing coordinated DDoS mitigation approaches either they require a complex configuration or are highly-priced. Blockchain technology offers a solution that reduces the complexity of signalling DDoS system, as well as a platform where many autonomous systems (Ass) can share hardware resources and defence capabilities for an effective DDoS defence. In this work, we also used a Deep learning DDoS detection system; we identify individual DDoS attack class and also define whether the incoming traffic is legitimate or attack. By classifying the attack traffic flow separately, our proposed mitigation technique could deny only the specific traffic causing the attack, instead of blocking all the traffic coming towards the victim(s).

2019-12-16
Lopes, José, Robb, David A., Ahmad, Muneeb, Liu, Xingkun, Lohan, Katrin, Hastie, Helen.  2019.  Towards a Conversational Agent for Remote Robot-Human Teaming. 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). :548–549.

There are many challenges when it comes to deploying robots remotely including lack of operator situation awareness and decreased trust. Here, we present a conversational agent embodied in a Furhat robot that can help with the deployment of such remote robots by facilitating teaming with varying levels of operator control.

2019-03-06
Aniculaesei, Adina, Grieser, Jörg, Rausch, Andreas, Rehfeldt, Karina, Warnecke, Tim.  2018.  Towards a Holistic Software Systems Engineering Approach for Dependable Autonomous Systems. Proceedings of the 1st International Workshop on Software Engineering for AI in Autonomous Systems. :23-30.

Autonomous systems are gaining momentum in various application domains, such as autonomous vehicles, autonomous transport robotics and self-adaptation in smart homes. Product liability regulations impose high standards on manufacturers of such systems with respect to dependability (safety, security and privacy). Today's conventional engineering methods are not adequate for providing guarantees with respect to dependability requirements in a cost-efficient manner, e.g. road tests in the automotive industry sum up millions of miles before a system can be considered sufficiently safe. System engineers will no longer be able to test and respectively formally verify autonomous systems during development time in order to guarantee the dependability requirements in advance. In this vision paper, we introduce a new holistic software systems engineering approach for autonomous systems, which integrates development time methods as well as operation time techniques. With this approach, we aim to give the users a transparent view of the confidence level of the autonomous system under use with respect to the dependability requirements. We present already obtained results and point out research goals to be addressed in the future.

Peruma, Anthony, Krutz, Daniel E..  2018.  Security: A Critical Quality Attribute in Self-Adaptive Systems. Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems. :188-189.

Self-Adaptive Systems (SAS) are revolutionizing many aspects of our society. From server clusters to autonomous vehicles, SAS are becoming more ubiquitous and essential to our world. Security is frequently a priority for these systems as many SAS conduct mission-critical operations, or work with sensitive information. Fortunately, security is being more recognized as an indispensable aspect of virtually all aspects of computing systems, in all phases of software development. Despite the growing prominence in security, from computing education to vulnerability detection systems, it is just another concern of creating good software. Despite how critical security is, it is a quality attribute like other aspects such as reliability, stability, or adaptability in a SAS.

2018-08-23
Felmlee, D., Lupu, E., McMillan, C., Karafili, E., Bertino, E..  2017.  Decision-making in policy governed human-autonomous systems teams. 2017 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computed, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). :1–6.

Policies govern choices in the behavior of systems. They are applied to human behavior as well as to the behavior of autonomous systems but are defined differently in each case. Generally humans have the ability to interpret the intent behind the policies, to bring about their desired effects, even occasionally violating them when the need arises. In contrast, policies for automated systems fully define the prescribed behavior without ambiguity, conflicts or omissions. The increasing use of AI techniques and machine learning in autonomous systems such as drones promises to blur these boundaries and allows us to conceive in a similar way more flexible policies for the spectrum of human-autonomous systems collaborations. In coalition environments this spectrum extends across the boundaries of authority in pursuit of a common coalition goal and covers collaborations between human and autonomous systems alike. In social sciences, social exchange theory has been applied successfully to explain human behavior in a variety of contexts. It provides a framework linking the expected rewards, costs, satisfaction and commitment to explain and anticipate the choices that individuals make when confronted with various options. We discuss here how it can be used within coalition environments to explain joint decision making and to help formulate policies re-framing the concepts where appropriate. Social exchange theory is particularly attractive within this context as it provides a theory with “measurable” components that can be readily integrated in machine reasoning processes.

2018-05-02
Clifford, J., Garfield, K., Towhidnejad, M., Neighbors, J., Miller, M., Verenich, E., Staskevich, G..  2017.  Multi-layer model of swarm intelligence for resilient autonomous systems. 2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC). :1–4.

Embry-Riddle Aeronautical University (ERAU) is working with the Air Force Research Lab (AFRL) to develop a distributed multi-layer autonomous UAS planning and control technology for gathering intelligence in Anti-Access Area Denial (A2/AD) environments populated by intelligent adaptive adversaries. These resilient autonomous systems are able to navigate through hostile environments while performing Intelligence, Surveillance, and Reconnaissance (ISR) tasks, and minimizing the loss of assets. Our approach incorporates artificial life concepts, with a high-level architecture divided into three biologically inspired layers: cyber-physical, reactive, and deliberative. Each layer has a dynamic level of influence over the behavior of the agent. Algorithms within the layers act on a filtered view of reality, abstracted in the layer immediately below. Each layer takes input from the layer below, provides output to the layer above, and provides direction to the layer below. Fast-reactive control systems in lower layers ensure a stable environment supporting cognitive function on higher layers. The cyber-physical layer represents the central nervous system of the individual, consisting of elements of the vehicle that cannot be changed such as sensors, power plant, and physical configuration. On the reactive layer, the system uses an artificial life paradigm, where each agent interacts with the environment using a set of simple rules regarding wants and needs. Information is communicated explicitly via message passing and implicitly via observation and recognition of behavior. In the deliberative layer, individual agents look outward to the group, deliberating on efficient resource management and cooperation with other agents. Strategies at all layers are developed using machine learning techniques such as Genetic Algorithm (GA) or NN applied to system training that takes place prior to the mission.

2018-02-27
Calo, S., Lupu, E., Bertino, E., Arunkumar, S., Cirincione, G., Rivera, B., Cullen, A..  2017.  Research Challenges in Dynamic Policy-Based Autonomous Security. 2017 IEEE International Conference on Big Data (Big Data). :2970–2973.

Generative policies enable devices to generate their own policies that are validated, consistent and conflict free. This autonomy is required for security policy generation to deal with the large number of smart devices per person that will soon become reality. In this paper, we discuss the research issues that have to be addressed in order for devices involved in security enforcement to automatically generate their security policies - enabling policy-based autonomous security management. We discuss the challenges involved in the task of automatic security policy generation, and outline some approaches based om machine learning that may potentially provide a solution to the same.

2018-02-15
Apostolaki, M., Zohar, A., Vanbever, L..  2017.  Hijacking Bitcoin: Routing Attacks on Cryptocurrencies. 2017 IEEE Symposium on Security and Privacy (SP). :375–392.

As the most successful cryptocurrency to date, Bitcoin constitutes a target of choice for attackers. While many attack vectors have already been uncovered, one important vector has been left out though: attacking the currency via the Internet routing infrastructure itself. Indeed, by manipulating routing advertisements (BGP hijacks) or by naturally intercepting traffic, Autonomous Systems (ASes) can intercept and manipulate a large fraction of Bitcoin traffic. This paper presents the first taxonomy of routing attacks and their impact on Bitcoin, considering both small-scale attacks, targeting individual nodes, and large-scale attacks, targeting the network as a whole. While challenging, we show that two key properties make routing attacks practical: (i) the efficiency of routing manipulation; and (ii) the significant centralization of Bitcoin in terms of mining and routing. Specifically, we find that any network attacker can hijack few (\textbackslashtextless;100) BGP prefixes to isolate 50% of the mining power-even when considering that mining pools are heavily multi-homed. We also show that on-path network attackers can considerably slow down block propagation by interfering with few key Bitcoin messages. We demonstrate the feasibility of each attack against the deployed Bitcoin software. We also quantify their effectiveness on the current Bitcoin topology using data collected from a Bitcoin supernode combined with BGP routing data. The potential damage to Bitcoin is worrying. By isolating parts of the network or delaying block propagation, attackers can cause a significant amount of mining power to be wasted, leading to revenue losses and enabling a wide range of exploits such as double spending. To prevent such effects in practice, we provide both short and long-term countermeasures, some of which can be deployed immediately.

2017-12-12
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.