Browsing by Author "Amuru, SaiDhiraj"
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- Distributed Storage Systems with Secure and Exact Repair - New ResultsTandon, Ravi; Amuru, SaiDhiraj; Clancy, Thomas Charles III; Buehrer, R. Michael (IEEE, 2014-02)Distributed storage systems (DSS) in the presence of a passive eavesdropper are considered in this paper. A typical DSS is characterized by 3 parameters (n, k, d) where, a file is stored in a distributed manner across n nodes such that it can be recovered entirely from any k out of n nodes. Whenever a node fails, d ∈ [k, n) nodes participate in the repair process. In this paper, we study the exact repair capabilities of a DSS, where a failed node is replaced with its exact replica. Securing this DSS from a passive eavesdropper capable of wiretapping the repair process of any l < k nodes, is the main focus of this paper. Specifically, we characterize the optimal secure storagevs- exact-repair-bandwidth tradeoff region for the (4, 2, 3) DSS when l = 1 and the (n, n − 1, n − 1) DSS when l = n − 2.
- Intelligent Approaches for Communication DenialAmuru, SaiDhiraj (Virginia Tech, 2015-10-05)Spectrum supremacy is a vital part of security in the modern era. In the past 50 years, a great deal of work has been devoted to designing defenses against attacks from malicious nodes (e.g., anti-jamming), while significantly less work has been devoted to the equally important task of designing effective strategies for denying communication between enemy nodes/radios within an area (e.g., jamming). Such denial techniques are especially useful in military applications and intrusion detection systems where untrusted communication must be stopped. In this dissertation, we study these offensive attack procedures, collectively termed as communication denial. The communication denial strategies studied in this dissertation are not only useful in undermining the communication between enemy nodes, but also help in analyzing the vulnerabilities of existing systems. A majority of the works which address communication denial assume that knowledge about the enemy nodes is available a priori. However, recent advances in communication systems creates the potential for dynamic environmental conditions where it is difficult and most likely not even possible to obtain a priori information regarding the environment and the nodes that are present in it. Therefore, it is necessary to have cognitive capabilities that enable the attacker to learn the environment and prevent enemy nodes from accessing valuable spectrum, thereby denying communication. In this regard, we ask the following question in this dissertation ``Can an intelligent attacker learn and adapt to unknown environments in an electronic warfare-type scenario?" Fundamentally speaking, we explore whether existing machine learning techniques can be used to address such cognitive scenarios and, if not, what are the missing pieces that will enable an attacker to achieve spectrum supremacy by denying an enemy the ability to communicate? The first task in achieving spectrum supremacy is to identify the signal of interest before it can be attacked. Thus, we first address signal identification, specifically modulation classification, in practical wireless environments where the interference is often non-Gaussian. Upon identifying the signal of interest, the next step is to effectively attack the victim signals in order to deny communication. We present a rigorous fundamental analysis regarding the attackers performance, in terms of achieving communication denial, in practical communication settings. Furthermore, we develop intelligent approaches for communication denial that employ novel machine learning techniques to attack the victim either at the physical layer, the MAC layer, or the network layer. We rigorously investigate whether or not these learning techniques enable the attacker to approach the fundamental performance limits achievable when an attacker has complete knowledge of the environment. As a result of our work, we debunk several myths about communication denial strategies that were believed to be true mainly because incorrect system models were previously considered and thus the wrong questions were answered.
- Towards Optimal Secure Distributed Storage Systems with Exact RepairTandon, Ravi; Amuru, SaiDhiraj; Clancy, Thomas Charles III; Buehrer, R. Michael (IEEE, 2016-06)Distributed storage systems in the presence of a wiretapper are considered. A distributed storage system (DSS) is parameterized by three parameters (𝑛, 𝑘, 𝑑), in which a file stored across n distributed nodes, can be recovered from any 𝑘 out of 𝑛 nodes. This is called as the reconstruction property of a DSS. If a node fails, any 𝑑 out of (𝑛-1) nodes help in the repair of the failed node so that the regeneration property of the DSS is preserved. For such a (𝑛, 𝑘, 𝑑)-DSS, two types of wiretapping scenarios are investigated: (a) Type-I (node) adversary which can wiretap the data stored on any 𝑙< 𝑘 nodes; and a more severe (b) Type-II (repair data) adversary which can wiretap the contents of the repair data that is used to repair a set of l failed nodes over time. The focus of this work is on the practically relevant setting of exact repair regeneration in which the repair process must replace a failed node by its exact replica. We make new progress on several non-trivial instances of this problem which prior to this work have been open. The main contribution of this paper is the optimal characterization of the secure storage-vs-exact-repair-bandwidth tradeoff region of a (𝑛, 𝑘, 𝑑)-DSS, with 𝑛 ≤ 4 and any 𝑙 < 𝑘 in the presence of both Type-I and Type-II adversaries. While the problem remains open for a general (𝑛, 𝑘, 𝑑)-DSS with 𝑛 > 4, we present extensions of these results to a (𝑛, 𝑛-1, 𝑛-1)-DSS, in presence of a Type-II adversary that can observe the repair data of any 𝑙 = (𝑛-2) nodes. The key technical contribution of this work is in developing novel information theoretic converse proofs for the Type-II adversarial scenario. From our results, we show that in the presence of Type-II attacks, the only efficient point in the storage-vs-exact-repair-bandwidth tradeoff is the MBR (minimum bandwidth regenerating) point. This is in sharp contrast to the case of a Type-I attack in which the storage-vs-exactrepair-bandwidth tradeoff allows a spectrum of operating points beyond the MBR point.