The objective of this paper is to optimize the power allocation to maximize the total rate of secondary users (SUs) under the SU total transmit power constraint and primary user (PU) interference temperature constraint, a proportional rate constraint is also used to assure that each SU can achieve fairness. The power allocation problem is not a convex optimization problem, which can be converted to a convex optimization problem without introducing auxiliary variables. To reduce the burden of information exchange and computational complexity, PU interference temperature constraint can be decoupled to an average interference constraint. The Lagrangian duality method is used to solve the optimal transmission power. Numerical results show that the proposed algorithm not only improves the rate fairness of each SU, but also guarantees the quality of service (QoS) of PU.

With the increasing users demands, the data traffic in the network reveal different characteristics in both spatial and temporal dimensions, bringing severe load imbalance problem. This may impact resource utilization, users experience and system energy efficiency, and then need further investigation. In this paper, we propose a distributed load-balancing algorithm considering this spatial-temporal variation in a two-tier heterogeneous network. Instead of illuminating the spatial-temporal influence, we make use of this characteristic while designing the algorithm, and accordingly switch ON/OFF small cell base stations (SBSs) for improving the energy efficiency. A load factor described with load variance is derived, based on which the problem is formulated as a non-linear integer programming that seeks to minimize a load function. Then a suboptimal solution is obtained by an effective heuristic algorithm. Simulation results show that our proposed algorithm balances the traffic load better and significantly reduces the total energy consumption, compared with conventional load-balancing scheme.

Nowadays, 5G puts forward a number of candidate multiple access technologies, among which the non-orthogonal multiple access (NOMA) is attracting more and more attention. Combining cognitive MIMO with NOMA is of great significance to improve the capacity for future mobile communication. Cognitive system includes two kinds of users, which are secondary users (SUs) and primary users (PUs), and the underlay spectrum sharing paradigm needs to consider the interference of the SUs system to the PUs system is below the predetermined threshold. And therefore, in order to reduce interference and improve capacity, we precode firstly at the transmitter. Then SUs were clustered according to the merits of the channel quality and performed power allocation for each cluster. During this process, the mean of the channel matrixs’ trace is used as the dynamic reception weight to enhance the system capacity. Meanwhile, taking the SUs’ quality of service (QoS) and the requirement of successive interference cancelation (SIC) into account. The objective function is NP-hard problem, we need to transform it into system capacity for sub-cluster, and finally using Lagrange function, nonconvex KKT conditions and mathematical induction (MI) to solve the optimal power allocation coefficient, which is between zero and one. The simulation shows that this proposed scheme can improve the capacity obviously compared with the average power allocation.

High imitation of primary user (PU) signal, primary user emulation (PUE) signal is difficulty for discrimination. First, a method based on cross ambiguity function (CAF) is proposed for determining PUE signal. For PUE signal different from PU signal in spatial but same in frequency in one sensing slot, the algorithm with two dimension search is reduced to one dimension search, having no inter-modulation signal influence. Moreover, for defending PUE attack (PUEA), a repeated game between malicious user (MU) and secondary user (SU) is formulated. By introducing credit discipline mechanism, the optimal strategies for both players are investigated. The stability of the strategies is analyzed with replicated dynamic equation, which indicates that the strategies are the final choice no matter what initial strategies they choose. Simulation results demonstrate that the method is effective for discriminating and defending PUEA in terms of lower computation, higher detection probability and greater payoff.

This paper studies the optimal power splitting strategy in a full-duplex wireless powered communication network (WPCN). This wireless powered network contains three nodes, which are the access point (AP), the relay node (R) and the user. We divide the communication process into two phases that each one has the same duration time. The AP transmits the energy to the relay node and the user, and the user transmits the information to the relay node and the AP simultaneously in the first phase. In the second phase, R relays the energy to the user and simultaneously decodes the information and forwards the information signal to the AP. We study how R splits its harvested energy into two parts separately for energy harvesting (EH) and information forwarding, respectively, to maximize the achievable information rate from the user to the AP, when a direct link between AP and the user exists or does not. We get the mathematical results of optimal power splitting factor in two models. Numerical results show that the variation trend of the maximum achievable rate with the distance between the AP and R, and the rate with direct link is not always larger than the rate without direct link.

Searchable Symmetric Encryption (SSE) which enables keyword searches on encrypted data, has drawn a lot of research attention in recent years. However, many SSE schemes do not support privacy-preserving relevance ranking which is a necessary feature for users to quickly locate the needed documents in a large number of retrieved documents. In this paper, we proposed two Privacy-Preserving Relevance Ranking (PPRR) schemes based on RSA encryption and ElGamal encryption. The proposed PPRR schemes preserve rank privacy and reduce storage cost at server side. Furthermore, we integrate PPRR with current multi-keyword SSE algorithm to achieve multi-keyword ranked search on encrypted data. Computation complexity, storage complexity and security of composite schemes are verified with an experiment on real-world dataset.

Today botnets are still one of the most prevalent and devastating attacking platforms that cyber criminals rely on to launch large scale Internet attacks. Botmasters behind the scenes are becoming more agile and discreet, and some new and sophisticated strategies are adopted to recruit bots and schedule their activities to evade detection more effectively. In this paper, we conduct a measurement study of 23 active botnet families to uncover some new botmaster strategies based on an operational dataset collected over a period of seven months. Our analysis shows that different from the common perception that bots are randomly recruited in a best-effort manner, bots recruitment has strong geographical and organizational locality, offering defenses a direction and priority when attempting to shut down these botnets. Furthermore, our study to measure dynamics of botnet activity reveals that botmasters start to deliberately schedule their bots to hibernate and alternate in attacks so that the detection window becomes smaller and smaller.

We present a new class of low-volume application layer DDoS attack–Very Short Intermittent DDoS (VSI-DDoS). Such attack sends intermittent bursts (tens of milliseconds duration) of legitimate HTTP requests to the target website with the goal of degrading the quality of service (QoS) of the system and damaging the long-term business of the service provider. VSI-DDoS attacks can be especially stealthy since they can significantly impair the target system performance while the average usage rate of all the system resources is at a moderate level, making it hard to pinpoint the root-cause of performance degradation. We develop a framework to effectively launch VSI-DDoS attacks, which includes three phases: the profiling phase in which appropriate HTTP requests are selected to launch the attack, the training phase in which a typical Service Level Agreement (e.g., percentile response time <1 s) is used to train the attack parameters, and the attacking phase in which attacking scripts are generated and deployed to distributed bots to launch the actual attack. To evaluate such VSI-DDoS attacks, we conduct extensive experiments using a representative benchmark web application under realistic cloud scaling settings and equipped with some popular state-of-the-art IDS/IPS systems (e.g., Snort), and find that our attacks are able to effectively cause the long-tail latency problem of the benchmark website while escaping the radar of those DDoS defense tools.

Despite security shields to protect user communication with both the radio access network and the core infrastructure, 4G LTE is still susceptible to a number of security threats. The vulnerabilities mainly exist due to its protocol’s inter-layer communication, and the access technologies (2G/3G) inter-radio interaction. We categorize the uncovered vulnerabilities in three dimensions, i.e., authentication, security association and service availability, and verify these vulnerabilities in operational LTE networks. In order to assess practical impact from these security threats, we convert these threats into active attacks, where an adversary can (a) kick the victim device out of the network, (b) hijack the victim’s location, and (c) silently drain the victim’s battery power. Moreover, we have shown that the attacker does not need to communicate with the victim device or reside at the device to launch these attacks (i.e., no Trojan or malware is required). We further propose remedies for the identified attacks.

The emerging Software-Defined Networking (SDN) is being adopted by data centers and cloud service providers to enable flexible control. Meanwhile, the current SDN design brings new vulnerabilities. In this paper, we explore a stealthy data plane based attack that uses a rate of attack packet to disrupt SDN. To achieve this, we propose the LOFT attack that computes the lower bound of attack rate to overflow flow tables based on the inferred network configurations. Particularly, each attack packet always triggers or maintains consumption of one flow rule. LOFT can ensure the attack effect with various network configurations while reducing the possibility of being captured. We demonstrate its feasibility and effectiveness in a real SDN testbed consisting of commercial hardware switches. The experiment results show that LOFT can incur significant network performance degradation and potential network DoS at an attack rate of only tens of Kbps.