Ankit Singh Rawat

Collaborative Spectrum Sensing in the Presence of Byzantine Attacks in Cognitive Radio Networks

Cognitive radio (CR) has emerged as a solution to the problem of spectrum scarcity as it exploits transmission opportunities in the under-utilized spectrum bands of primary users. Collaborative (or distributed) spectrum sensing has been shown to have various advantages in terms of spectrum utilization and robustness. The data fusion scheme is a key component of collaborative spectrum sensing. In this paper, we analyze the performance limits of collaborative spectrum sensing under Byzantine Attacks where malicious users send false sensing data to the fusion center leading to increased probability of incorrect sensing results. We show that above a certain fraction of Byzantine attackers in the CR network, data fusion scheme becomes completely incapable and no reputation based fusion scheme can achieve any performance gain. We present optimal attacking strategies for given attacking resources and also analyze the possible counter measures at the fusion center (FC). Based on these analyses, we also propose a novel and easy to implement technique to counter Byzantine attacks in CRNs. In this approach, the FC identifies the attackers and removes them from the data fusion process. Our analysis indicates that the proposed scheme is robust against Byzantine attacks and can successfully remove the Byzantines in a short time span.

Optimal Locally Repairable and Secure Codes for Distributed Storage Systems

This paper aims to go beyond resilience into the study of security and local-repairability for distributed storage systems (DSSs). Security and local-repairability are both important as features of an efficient storage system, and this paper aims to understand the trade-offs between resilience, security, and local-repairability in these systems. In particular, this paper first investigates security in the presence of colluding eavesdroppers, where eavesdroppers are assumed to work together in decoding the stored information. Second, this paper focuses on coding schemes that enable optimal local repairs. It further brings these two concepts together to develop locally repairable coding schemes for DSS that are secure against eavesdroppers. The main results of this paper include: 1) an improved bound on the secrecy capacity for minimum storage regenerating codes; 2) secure coding schemes that achieve the bound for some special cases; 3) a new bound on minimum distance for locally repairable codes; 4) code construction for locally repairable codes that attain the minimum distance bound; and 5) repair-bandwidth-efficient locally repairable codes with and without security constraints.

Optimal locally repairable codes via rank-metric codes

This paper presents a new explicit construction for locally repairable codes (LRCs) for distributed storage systems which possess all-symbol locality and the largest possible minimum distance, or equivalently, can tolerate the maximum number of node failures. This construction, based on maximum rank distance (MRD) Gabidulin codes, provides new optimal vector and scalar LRCs. In addition, the paper also discusses mechanisms by which codes obtained using this construction can be used to construct LRCs with efficient local repair of failed nodes by combination of LRCs with regenerating codes.

Locality and Availability in Distributed Storage

This paper studies the problem of information symbol availability in codes: we refer to a systematic code as code with

Collaborative spectrum sensing in the presence of Byzantine attacks in Cognitive Radio Networks

(r, t)

Locality and availability in distributed storage

-availability if every information (systematic) symbol can be reconstructed from

Countering byzantine attacks in cognitive radio networks

t

Error resilience in distributed storage via rank-metric codes

disjoint groups of other code symbols, each of the sizes at most

Explicit MBR all-symbol locality codes

r

On cooperative local repair in distributed storage

. This paper shows that it is possible to construct codes that can support a scaling number of parallel reads while keeping the rate to be an arbitrarily high constant. It further shows that this is possible with the minimum Hamming distance arbitrarily close to the Singleton bound. This paper also presents a bound demonstrating a tradeoff between rate, minimum Hamming distance, and availability parameters. Our codes match the aforementioned bound, and their constructions rely on certain combinatorial structures. Resolvable designs provide one way to realize these required combinatorial structures. The two constructions presented in this paper require field sizes, which are linear and exponential in the code length, respectively. From a practical standpoint, our codes are relevant for distributed storage applications involving hot data, i.e., the information, which is frequently accessed by multiple processes in parallel.