An Autonomous Intrusion Detection System Using an Ensemble of Advanced Learners

An intrusion detection system (IDS) is a vital security component of modern computer networks. With the increasing amount of sensitive services that use computer network-based infrastructures, IDSs need to be more intelligent and autonomous. Aside from autonomy, another important feature for an IDS is its ability to detect zero-day attacks. To address these issues, in this paper, we propose an IDS which reduces the amount of manual interaction and needed expert knowledge and is able to yield acceptable performance under zero-day attacks. Our approach is to use three learning techniques in parallel: gated recurrent unit (GRU), convolutional neural network as deep techniques and random forest as an ensemble technique. These systems are trained in parallel and the results are combined under two logics: majority vote and "OR" logic. We use the NSL-KDD dataset to verify the proficiency of our proposed system. Simulation results show that the system has the potential to operate with a very low technician interaction under the zero-day attacks. We achieved 87:28% accuracy on the NSL-KDD's "KDDTest+" dataset and 76:61% accuracy on the challenging "KDDTest-21" with lower training time and lower needed computational resources.Comment: 5 page

On the Construction of Polar Codes for Achieving the Capacity of Marginal Channels

Achieving security against adversaries with unlimited computational power is of great interest in a communication scenario. Since polar codes are capacity achieving codes with low encoding-decoding complexity and they can approach perfect secrecy rates for binary-input degraded wiretap channels in symmetric settings, they are investigated extensively in the literature recently. In this paper, a polar coding scheme to achieve secrecy capacity in non-symmetric binary input channels is proposed. The proposed scheme satisfies security and reliability conditions. The wiretap channel is assumed to be stochastically degraded with respect to the legitimate channel and message distribution is uniform. The information set is sent over channels that are good for Bob and bad for Eve. Random bits are sent over channels that are good for both Bob and Eve. A frozen vector is chosen randomly and is sent over channels bad for both. We prove that there exists a frozen vector for which the coding scheme satisfies reliability and security conditions and approaches the secrecy capacity. We further empirically show that in the proposed scheme for non-symmetric binary-input discrete memoryless channels, the equivocation rate achieves its upper bound in the whole capacity-equivocation region

Polar Coding for Achieving the Capacity of Marginal Channels in Nonbinary-Input Setting

Achieving information-theoretic security using explicit coding scheme in which unlimited computational power for eavesdropper is assumed, is one of the main topics is security consideration. It is shown that polar codes are capacity achieving codes and have a low complexity in encoding and decoding. It has been proven that polar codes reach to secrecy capacity in the binary-input wiretap channels in symmetric settings for which the wiretapper's channel is degraded with respect to the main channel. The first task of this paper is to propose a coding scheme to achieve secrecy capacity in asymmetric nonbinary-input channels while keeping reliability and security conditions satisfied. Our assumption is that the wiretap channel is stochastically degraded with respect to the main channel and message distribution is unspecified. The main idea is to send information set over good channels for Bob and bad channels for Eve and send random symbols for channels that are good for both. In this scheme the frozen vector is defined over all possible choices using polar codes ensemble concept. We proved that there exists a frozen vector for which the coding scheme satisfies reliability and security conditions. It is further shown that uniform distribution of the message is the necessary condition for achieving secrecy capacity.Comment: Accepted to be published in "51th Conference on Information Sciences and Systems", Baltimore, Marylan

Comparison of Cooperative and Non-Cooperative Game Schemes for SINR-Constrained Power Allocation in Multiple Antenna CDMA Communication Systems

In this paper, we formulate the SINR-constrained power allocation problem in the wideband multiantenna CDMA cellular system as a game. Using the cooperative theory and Nash bargaining model, we compared it to the noncooperative game scheme proposed in (S. Koskie, Z. Gajic, IEEE trans. on Networking, 2005). We define a utility function which considers both power usage and QoS. We show that the resulting operating point using Nash bargaining model is fair and Pareto optimal, however, the Nash equilibrium operating point obtained in the noncooperative game scheme is not in general Pareto optimal. Also, we proposed a centralized power control algorithm based on conjugate gradient algorithm for multiantenna CDMA cellular systems, when the transmitted power and SINR which each user experience is constrained. In addition, we can extend the result to a fair rate optimization in a multiuser multiple antenna regime through a power control problem subject to SINR constraints.This work was supported by Young Researchers Club, No 5, Malek St., Shariati St., Tehran, Iran

Transmit covariance for spatially-correlated multiple-antenna Ricean fading channels with channel distribution side information at transmitter

In this paper, we cast the problem of finding the capacity-achieving transmit covariance of correlated Ricean MIMO fading channels as an equivalent problem as for uncorrelated Ricean MIMO channels. Perfect channel information is assumed to be available at the receiver, while the transmitter only has channel distribution side information. An iterative algorithm based on Newton method to compute the capacity-achieving transmit covariance for the general case of double-ended correlated MIMO channels is proposed in this paper as well. Additionally, we provide a reduced complexity technique to attain a suboptimal transmit covariance. One of the main contributions in this paper is the characterization of the eigenstructure of the suboptimal transmit covariance. Moreover, Sufficient condition is derived for the optimality of this suboptimal solution.This work is supported in part by Iran Telecommunication Research Center (ITRC), PO Box 14155-3961, Tehran 14399,Iran

New Adaptive Method for IQ Imbalance Compensation of Quadrature Modulators in Predistortion Systems

Imperfections in quadrature modulators (QMs), such as inphase and quadrature (IQ) imbalance, can severely impact the performance of power amplifier (PA) linearization systems, in particular in adaptive digital predistorters (PDs). In this paper, we first analyze the effect of IQ imbalance on the performance of a memory orthogonal polynomials predistorter (MOP PD), and then we propose a new adaptive algorithm to estimate and compensate the unknown IQ imbalance in QM. Unlike previous compensation techniques, the proposed method was capable of online IQ imbalance compensation with faster convergence, and no special calibration or training signals were needed. The effectiveness of the proposed IQ imbalance compensator was validated by simulations. The results clearly show the performance of the MOP PD to be enhanced significantly by adding the proposed IQ imbalance compensator