Although the blockchain technology has the potential to transform every industry, the performance level of existing blockchain platforms is too low to realize that vision. From an architectural viewpoint, this unsolved problem is a bottleneck to blockchain adoption in many applications. Our work aims to improve the scalability of blockchain to achieve Visa-like transaction speed. Additionally, we explore and defend against possible security threats and vulnerabilities that could be exploited to obstruct blockchain systems, thereby advancing the practicality of the blockchain technology.
Objectives:
- Improve the scalability of blockchain systems on a wide variety of applications
- Identify vulnerabilities of blockchain systems, including vulnerabilities arising from the underlying distributed infrastructure.
- Identify & mitigate attacks on the efficiency of blockchain systems.
Selected Publications:
- . “Exploring Spatial, Temporal, and Logical Attacks on Bitcoin Network,” in NDSS 2019 (Poster), 2019
- . “Partitioning Attacks on Bitcoin Network: Colliding Space, Time and Logic,” in IEEE ICDCS, 2019
- . “Optimal Transactions Placement for Scalable Blockchain Sharding,” in IEEE ICDCS, 2019
The study of network vulnerability seeks to identify the critical elements with respect to a variety of measures. Generally speaking, a network is robust if external pertubations do not significantly impair its functionality. In this area, we seek to design methods to identify the critical elements. One measure we study is the vulnerability of network clustering to node failure; another is the vulnerability of Quality of Service (QoS) in a communication network to node and link failures.
Objectives:
- Identify critical elements for network infrastructure measurements, such as the degree of network clustering
- Design comprehensive vulnerability measure for communication networks capable of utilizing any QoS metric
Selected Publications:
- . “Network Resilience Assessment via QoS Degradation Metrics: An Algorithmic Approach,” in ACM POMACS & SIGMETRICS, 2019
- . “Exploring Spatial, Temporal, and Logical Attacks on Bitcoin Network,” in NDSS 2019 (Poster), 2019
- . “Partitioning Attacks on Bitcoin Network: Colliding Space, Time and Logic,” in IEEE ICDCS, 2019
s an imperative channel for rapid information propagation, OSNs also have their disruptive effects. One of them is the leakage of information, i.e., information could be spread via OSNs to the users whom we may not willing to share with. Thus the problem of constructing a circle of trust to share the information with as many friends as possible without further spreading it to unwanted users has become a challenging research topic recently. Our work is the first attempt to study the Maximum Circle of Trust problem which seek for a close set of friends such that the chance for information spread out to the unwanted users is the smallest. We propose a Fully Polynomial-Time Approximation Scheme (FPTAS)
Objectives:
- Develop and justify leakage models in online social networks
- Devise scalable and efficient methods to construct circles of trust for smart sharing on the fly, given the unwanted targets
Smart Grid addresses the problem of existing powergrid\’s increasing complexity, growing demand and requirement for greater reliability, through two-way communication and automated residential load control among others. These features also makes the Smart Grid a target for a number of cyber attacks. The load profiles of consumers could be changed through the fabrication of price messages. This attack could lead to cascading failures. Our work is the first attempt to study the effect of such cyber attacks on smart grid, seeking the vulnerable critical nodes. With linearized DC power flow model and cascading failure in power grid models, we also provide solutions to mitigate or reduce the damage due to the cascading failures.
Objectives:
- Find vulnerable nodes where price modification attacks have potential to cause large blackouts
- Find measures to mitigate the cascading failures due to price modification attacks
Selected Publications:
- . “Price Modification Attack and Protection Scheme in Smart Grid,” in IEEE Transactions on Smart Grid, 2016
- . “Rate Alteration Attacks in Smart Grid,” in Proceedings of the IEEE Int Conference on Computer Communications (INFOCOM), 2015
- . “Cascading Critical Nodes Detection with Load Redistribution in Complex Systems,” in Proceedings of the 8th Annual International Conference on Combinatorial Optimization and Applications (COCOA), 2014
The ever-growing deployment of machine learning models in industrial and health contexts raises critical privacy and security concerns. These models are built on personal data (e.g. clinical records, images, and user profiles). Our work on this subject focuses on extending ideas in differential privacy to deep neural networks to secure these models in contexts with sensitive data.
Objectives:
- Identify privacy vulnerabilities in existing machine learning systems, particularly those that may leak sensitive information to third parties.
- Develop provably-robust privacy-preserving machine learning systems.
Selected Publications:
- . “Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness,” in IJCAI, 2019
Supervisory Control And Data Acquisition (SCADA) system remotely monitors and controls remote stations from a central SCADA center through coded signals over communication (or control) network. The addition of control network to better manage and gather system data comes with its own set of vulnerabilities including false data injection and fabricated system data which leads to bad state estimation. Among security enhancements such as advanced encryption and authentication, deep packet inspection (DPI) is used to detect malicious packets. However, DPI introduces delay in the poacket transmission in highly time critical IEC 61850 messages. Our work focus on the placement of the DPIs in the control network in order to maximize the amount of scanned packets.
Objectives:
- To optimally place the DPIs in the control network without violating the time delay constraint
- Investigate other ways to detect malicious packets in SCADA network
Selected Publications:
- . “Auditing on Smart-Grid with Dynamic Traffic Flows: An Algorithmic Approach,” in IEEE Transactions on Smart Grid, 2019
- . “Optimal Inspection Points for Malicious Attack Detection in Smart Grids,” in Proceedings of the 20th Int Computing and Combinatorics Conference (COCOON), 2014
The socialbot attack model is a spiritual successor to the Sybil attack model that addresses several of its flaws. Where the Sybil model makes strong assumptions about the number and organization of the attackers, the socialbot model relaxes those. A socialbot is simply a bot that pretends to be a human on a social network. Therefore, a socialbot attack could consist of only a single attacker or an army of loosely-coordinated assailants.
Objectives:
- Devise theoretically optimal socialbot attacks, and study their limitations and how to exploit them for defense.
- Examine the impact of user behaviors on socialbot attacks, and study how attackers may exploit or suffer from these behaviors.
Selected Publications:
- . “Adaptive Crawling with Multiple Bots: A Matroid Intersection Approach,” in Proceedings of INFOCOM, 2018
- . “An Approximately Optimal Bot for Non-Submodular Social Reconnaissance,” in Proceedings of HyperText, 2018
- . “Adaptive Reconnaissance Attacks with Near-Optimal Parallel Batching,” in Proceedings of ICDCS, 2017
The wide spread of misinformation in online social networks has become a main threat to our society. Generally, people tend to believe what their friends are saying. Leveraging the social relationships to contain or block the misinformation appears to be a promising strategy.
Objectives:
- Detect misinformation in online social networks in the early stage of spread
- Design effective measure to evaluate the nodes contribution of diffuse the true information in the presence of misinformation
- Identify the most important nodes in the spread of true information so as to block the misinformation
Selected Publications:
- . “Detecting Misinformation in Online Social Networks Before It Is Too Late,” in The 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016), 2016
- . “Analysis of Misinformation Containment in Online Social Networks,” in Elsevier Computer Networks-Towards a Science of Cyber Security (COMNETS), vol. 57, no. 10, pp. 2133–2146, 2013
The social computing will integrate and enhance many digital systems over the next decade and the smart grid is no exception. Smart grid efficiency depends on utility customers having knowledge about demand response programs and being actively engaged in energy management. And this is exactly where social network comes into the picture and can really have an impact. Social computing can also expand the adoption and adaptation of smart grid technologies through the peer to peer communication in local communities through social network. It also could change large scale behavior through crowdshifting basing on the theory “people decide how to behave based on what they see others doing, especially if those others seem similar to themselves”.
Objectives:
- Study and analyze the inter dependency between social network and smart grid
- Explore possible vulnerabilities and corresponding protection measures in the socially enabled smart grid
Selected Publications:
- . “Catastrophic Cascading Failures in Power Networks,” in Theoretical Computer Science, 2015
The study of interdependent networks from the perspective of vulnerability seeks to identify the critical elements with respect to a variety of measures. An interdependent system is robust if external perturbations do not significantly impair the functionality of the system. In this area, we seek to design methods to identify the critical elements. One measure we study in general interdependent networks is the vulnerability of network clustering to node failure. We also study measures in practical scenarios, one scenario is in a Smart Grid system, how the interdependent communication and power networks impact one another’s functionality — a failure in one of these networks may cascade to the other. Another scenario is in mobile social networks underlay a D2D network, where misinformation in the social network may cascade and cause users stop using D2D, thus impact the throughput of the D2D network.
Objectives:
- Characterize robustness using a variety of measures of functionality
- Study interdependency effects relevant to vulnerability, such as cascading failure
- Identify critical elements in the functionality of interdependent systems
Selected Publications:
- . “Detecting Critical Nodes in Interdependent Power Networks for Vulnerability Assessment,” in IEEE Transactions on Smart Grid (ToSG), 2013