Secure Partial Repair in Wireless Caching Networks with Broadcast Channels

We study security in partial repair in wireless caching networks where parts of the stored packets in the caching nodes are susceptible to be erased. Let us denote a caching node that has lost parts of its stored packets as a sick caching node and a caching node that has not lost any packet as a healthy caching node. In partial repair, a set of caching nodes (among sick and healthy caching nodes) broadcast information to other sick caching nodes to recover the erased packets. The broadcast information from a caching node is assumed to be received without any error by all other caching nodes. All the sick caching nodes then are able to recover their erased packets, while using the broadcast information and the nonerased packets in their storage as side information. In this setting, if an eavesdropper overhears the broadcast channels, it might obtain some information about the stored file. We thus study secure partial repair in the senses of information-theoretically strong and weak security. In both senses, we investigate the secrecy caching capacity, namely, the maximum amount of information which can be stored in the caching network such that there is no leakage of information during a partial repair process. We then deduce the strong and weak secrecy caching capacities, and also derive the sufficient finite field sizes for achieving the capacities. Finally, we propose optimal secure codes for exact partial repair, in which the recovered packets are exactly the same as erased packets.Comment: To Appear in IEEE Conference on Communication and Network Security (CNS

Secure and Private Cloud Storage Systems with Random Linear Fountain Codes

An information theoretic approach to security and privacy called Secure And Private Information Retrieval (SAPIR) is introduced. SAPIR is applied to distributed data storage systems. In this approach, random combinations of all contents are stored across the network. Our coding approach is based on Random Linear Fountain (RLF) codes. To retrieve a content, a group of servers collaborate with each other to form a Reconstruction Group (RG). SAPIR achieves asymptotic perfect secrecy if at least one of the servers within an RG is not compromised. Further, a Private Information Retrieval (PIR) scheme based on random queries is proposed. The PIR approach ensures the users privately download their desired contents without the servers knowing about the requested contents indices. The proposed scheme is adaptive and can provide privacy against a significant number of colluding servers.Comment: 8 pages, 2 figure

Private Information Retrieval with Side Information and Coding for Security

This dissertation studies privacy and security problems from an information-theoretic point of view. We study the privacy problem via the private information retrieval (PIR) problem with a focus on its interactions with available side information. We study the security problem via the wiretap channel with a focus on the design of practical coding schemes to achieve information-theoretically achievable random-coding based secrecy rates. First, we consider the problem of PIR from $N$ non-colluding and replicated databases when the user is equipped with a cache that holds an uncoded fraction $r$ from each of the $K$ stored messages in the databases. We consider the case where the databases are unaware of the cache content. We investigate $D^*(r)$ the optimal download cost normalized with the message size as a function of $K$, $N$, $r$. For a fixed $K$, $N$, we develop converses and achievability schemes for the $D^*(r)$ curve. The largest additive gap between our achievability and the converse bounds is $\frac{1}{6}$. Our results show that the download cost can be reduced beyond memory-sharing if the databases are unaware of the cached content. Second, we consider the same setting under a more restricted model where the databases know the user cache content partially. The user receives an uncoded fraction $r$ from each of the $K$ stored messages, with the $\frac{r}{N}$ fraction of it coming from the $n$th database. The side information obtained from the $n$th database is known by the $n$th database and is unknown by the remaining databases. We investigate the optimal normalized download cost $D^*(r)$, and develop converses and achievability schemes for $D^*(r)$. The largest additive gap between our achievability and the converse bounds is $\frac{5}{32}$ for this case. We observe that the achievable download cost here is larger than that in the previous case due to the partial knowledge of the databases regarding the cache content. Third, we consider the problem of PIR with private side information (PSI) when the cache content is partially known by the databases. Here, a cache-enabled user of cache-size $M$ possesses side information in the form of full messages that are partially known by the databases. The user wishes to download a desired message privately while keeping the identities of the side information messages that the user did not prefetch from a database private against that database. We characterize the exact capacity of PIR with PSI under partially known PSI condition. We show that the capacity of PIR with partially known PSI is the same as the capacity of PIR with fully unknown PSI. Fourth, we consider PIR with PSI under storage constraints where a cache-enabled user of cache-size $S$ possesses side information in the form $M$ messages that are unknown to the databases, where $M>S$. We address the problem of which uncoded parts of $M$ messages the user should keep in its constrained cache of size $S$ in order to minimize the download cost during PIR subject to PSI. We characterize the exact capacity of this PIR-PSI problem under the storage constraint $S$. We show that a uniform caching scheme which caches equal amounts from all messages achieves the lowest normalized download cost. Fifth, we consider the PIR problem from decentralized uncoded caching databases. Here, the contents of the databases are not fixed a priori, and we design the probability distribution adopted by each database in the decentralized caching phase in order to minimize the expected normalized download cost in the retrieval phase. We characterize the exact capacity of this problem, and show that uniform and random caching results in the lowest normalized download cost. Next, we focus on security of communication by designing practical coding schemes to achieve the information-theoretically achievable random-coding based secrecy rates. By applying two recently developed techniques for polar codes, namely, universal polar coding and polar coding for asymmetric channels, we propose a polar coding scheme to achieve the secrecy capacity of the general wiretap channel. We then apply this coding scheme to achieve the best-known secrecy rates for the multiple access wiretap channel, and the broadcast and interference channels with confidential messages

Enable Reliable and Secure Data Transmission in Resource-Constrained Emerging Networks

The increasing deployment of wireless devices has connected humans and objects all around the world, benefiting our daily life and the entire society in many aspects. Achieving those connectivity motivates the emergence of different types of paradigms, such as cellular networks, large-scale Internet of Things (IoT), cognitive networks, etc. Among these networks, enabling reliable and secure data transmission requires various resources including spectrum, energy, and computational capability. However, these resources are usually limited in many scenarios, especially when the number of devices is considerably large, bringing catastrophic consequences to data transmission. For example, given the fact that most of IoT devices have limited computational abilities and inadequate security protocols, data transmission is vulnerable to various attacks such as eavesdropping and replay attacks, for which traditional security approaches are unable to address. On the other hand, in the cellular network, the ever-increasing data traffic has exacerbated the depletion of spectrum along with the energy consumption. As a result, mobile users experience significant congestion and delays when they request data from the cellular service provider, especially in many crowded areas. In this dissertation, we target on reliable and secure data transmission in resource-constrained emerging networks. The first two works investigate new security challenges in the current heterogeneous IoT environment, and then provide certain countermeasures for reliable data communication. To be specific, we identify a new physical-layer attack, the signal emulation attack, in the heterogeneous environment, such as smart home IoT. To defend against the attack, we propose two defense strategies with the help of a commonly found wireless device. In addition, to enable secure data transmission in large-scale IoT network, e.g., the industrial IoT, we apply the amply-and-forward cooperative communication to increase the secrecy capacity by incentivizing relay IoT devices. Besides security concerns in IoT network, we seek data traffic alleviation approaches to achieve reliable and energy-efficient data transmission for a group of users in the cellular network. The concept of mobile participation is introduced to assist data offloading from the base station to users in the group by leveraging the mobility of users and the social features among a group of users. Following with that, we deploy device-to-device data offloading within the group to achieve the energy efficiency at the user side while adapting to their increasing traffic demands. In the end, we consider a perpendicular topic - dynamic spectrum access (DSA) - to alleviate the spectrum scarcity issue in cognitive radio network, where the spectrum resource is limited to users. Specifically, we focus on the security concerns and further propose two physical-layer schemes to prevent spectrum misuse in DSA in both additive white Gaussian noise and fading environments