Visible to the public Biblio

Filters: Author is Shetty, S.  [Clear All Filters]
2019-03-25
Hasan, K., Shetty, S., Hassanzadeh, A., Salem, M. B., Chen, J..  2018.  Self-Healing Cyber Resilient Framework for Software Defined Networking-Enabled Energy Delivery System. 2018 IEEE Conference on Control Technology and Applications (CCTA). :1692–1697.
Software defined networking (SDN) is a networking paradigm to provide automated network management at run time through network orchestration and virtualization. SDN can also enhance system resilience through recovery from failures and maintaining critical operations during cyber attacks. SDN's self-healing mechanisms can be leveraged to realized autonomous attack containment, which dynamically modifies access control rules based on configurable trust levels. In this paper, we present an approach to aid in selection of security countermeasures dynamically in an SDN enabled Energy Delivery System (EDS) and achieving tradeoff between providing security and QoS. We present the modeling of security cost based on end-to-end packet delay and throughput. We propose a non-dominated sorting based multi-objective optimization framework which can be implemented within an SDN controller to address the joint problem of optimizing between security and QoS parameters by alleviating time complexity at O(M N2), where M is the number of objective functions and N is the number of population for each generation respectively. We present simulation results which illustrate how data availability and data integrity can be achieved while maintaining QoS constraints.
2018-05-24
Tosh, D. K., Shetty, S., Liang, X., Kamhoua, C. A., Kwiat, K. A., Njilla, L..  2017.  Security Implications of Blockchain Cloud with Analysis of Block Withholding Attack. 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). :458–467.

The blockchain technology has emerged as an attractive solution to address performance and security issues in distributed systems. Blockchain's public and distributed peer-to-peer ledger capability benefits cloud computing services which require functions such as, assured data provenance, auditing, management of digital assets, and distributed consensus. Blockchain's underlying consensus mechanism allows to build a tamper-proof environment, where transactions on any digital assets are verified by set of authentic participants or miners. With use of strong cryptographic methods, blocks of transactions are chained together to enable immutability on the records. However, achieving consensus demands computational power from the miners in exchange of handsome reward. Therefore, greedy miners always try to exploit the system by augmenting their mining power. In this paper, we first discuss blockchain's capability in providing assured data provenance in cloud and present vulnerabilities in blockchain cloud. We model the block withholding (BWH) attack in a blockchain cloud considering distinct pool reward mechanisms. BWH attack provides rogue miner ample resources in the blockchain cloud for disrupting honest miners' mining efforts, which was verified through simulations.

2018-03-19
Kamdem, G., Kamhoua, C., Lu, Y., Shetty, S., Njilla, L..  2017.  A Markov Game Theoritic Approach for Power Grid Security. 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW). :139–144.

The extensive use of information and communication technologies in power grid systems make them vulnerable to cyber-attacks. One class of cyber-attack is advanced persistent threats where highly skilled attackers can steal user authentication information's and then move laterally in the network, from host to host in a hidden manner, until they reach an attractive target. Once the presence of the attacker has been detected in the network, appropriate actions should be taken quickly to prevent the attacker going deeper. This paper presents a game theoretic approach to optimize the defense against an invader attempting to use a set of known vulnerabilities to reach critical nodes in the network. First, the network is modeled as a vulnerability multi-graph where the nodes represent physical hosts and edges the vulnerabilities that the attacker can exploit to move laterally from one host to another. Secondly, a two-player zero-sum Markov game is built where the states of the game represent the nodes of the vulnerability multi-graph graph and transitions correspond to the edge vulnerabilities that the attacker can exploit. The solution of the game gives the optimal strategy to disconnect vulnerable services and thus slow down the attack.

2018-02-14
Zhao, J., Shetty, S., Pan, J. W..  2017.  Feature-based transfer learning for network security. MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM). :17–22.

New and unseen network attacks pose a great threat to the signature-based detection systems. Consequently, machine learning-based approaches are designed to detect attacks, which rely on features extracted from network data. The problem is caused by different distribution of features in the training and testing datasets, which affects the performance of the learned models. Moreover, generating labeled datasets is very time-consuming and expensive, which undercuts the effectiveness of supervised learning approaches. In this paper, we propose using transfer learning to detect previously unseen attacks. The main idea is to learn the optimized representation to be invariant to the changes of attack behaviors from labeled training sets and non-labeled testing sets, which contain different types of attacks and feed the representation to a supervised classifier. To the best of our knowledge, this is the first effort to use a feature-based transfer learning technique to detect unseen variants of network attacks. Furthermore, this technique can be used with any common base classifier. We evaluated the technique on publicly available datasets, and the results demonstrate the effectiveness of transfer learning to detect new network attacks.

2018-02-02
Ghosh, U., Chatterjee, P., Tosh, D., Shetty, S., Xiong, K., Kamhoua, C..  2017.  An SDN Based Framework for Guaranteeing Security and Performance in Information-Centric Cloud Networks. 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). :749–752.

Cloud data centers are critical infrastructures to deliver cloud services. Although security and performance of cloud data centers have been well studied in the past, their networking aspects are overlooked. Current network infrastructures in cloud data centers limit the ability of cloud provider to offer guaranteed cloud network resources to users. In order to ensure security and performance requirements as defined in the service level agreement (SLA) between cloud user and provider, cloud providers need the ability to provision network resources dynamically and on the fly. The main challenge for cloud provider in utilizing network resource can be addressed by provisioning virtual networks that support information centric services by separating the control plane from the cloud infrastructure. In this paper, we propose an sdn based information centric cloud framework to provision network resources in order to support elastic demands of cloud applications depending on SLA requirements. The framework decouples the control plane and data plane wherein the conceptually centralized control plane controls and manages the fully distributed data plane. It computes the path to ensure security and performance of the network. We report initial experiment on average round-trip delay between consumers and producers.

2018-01-10
Chen, W., Hong, L., Shetty, S., Lo, D., Cooper, R..  2016.  Cross-Layered Security Approach with Compromised Nodes Detection in Cooperative Sensor Networks. 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). :499–508.

Cooperative MIMO communication is a promising technology which enables realistic solution for improving communication performance with MIMO technique in wireless networks that are composed of size and cost constrained devices. However, the security problems inherent to cooperative communication also arise. Cryptography can ensure the confidentiality in the communication and routing between authorized participants, but it usually cannot prevent the attacks from compromised nodes which may corrupt communications by sending garbled signals. In this paper, we propose a cross-layered approach to enhance the security in query-based cooperative MIMO sensor networks. The approach combines efficient cryptographic technique implemented in upper layer with a novel information theory based compromised nodes detection algorithm in physical layer. In the detection algorithm, a cluster of K cooperative nodes are used to identify up to K - 1 active compromised nodes. When the compromised nodes are detected, the key revocation is performed to isolate the compromised nodes and reconfigure the cooperative MIMO sensor network. During this process, beamforming is used to avoid the information leaking. The proposed security scheme can be easily modified and applied to cognitive radio networks. Simulation results show that the proposed algorithm for compromised nodes detection is effective and efficient, and the accuracy of received information is significantly improved.

2017-12-28
Liang, X., Zhao, J., Shetty, S., Li, D..  2017.  Towards data assurance and resilience in IoT using blockchain. MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM). :261–266.

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.