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Manar Mohaisen

Publications and source records attributed to Manar Mohaisen.

At least 19 recordsLinked to original sources

A Comprehensive Analysis of Evolving Permission Usage in Android Apps: Trends, Threats, and Ecosystem Insights

The proper use of Android app permissions is crucial to the success and security of these apps. Users must agree to permission requests when installing or running their apps. Despite official Android platform documentation on proper permission usage, there are still many cases of permission abuse. This study provides a comprehensive analysis of the Android permission landscape, highlighting trends and patterns in permission requests across various applications from the Google Play Store. By distinguishing between benign and malicious applications, we uncover developers' evolving strategies, with malicious apps increasingly requesting fewer permissions to evade detection, while benign apps request more to enhance functionality. In addition to examining permission trends across years and app features such as advertisements, in-app purchases, content ratings, and app sizes, we leverage association rule mining using the FP-Growth algorithm. This allows us to uncover frequent permission combinations across the entire dataset, specific years, and 16 app genres. The analysis reveals significant differences in permission usage patterns, providing a deeper understanding of co-occurring permissions and their implications for user privacy and app functionality. By categorizing permissions into high-level semantic groups and examining their application across distinct app categories, this study offers a structured approach to analyzing the dynamics within the Android ecosystem. The findings emphasize the importance of continuous monitoring, user education, and regulatory oversight to address permission misuse effectively.

cs.CR

Enhancing Vulnerability Reports with Automated and Augmented Description Summarization

Public vulnerability databases, such as the National Vulnerability Database (NVD), document vulnerabilities and facilitate threat information sharing. However, they often suffer from short descriptions and outdated or insufficient information. In this paper, we introduce Zad, a system designed to enrich NVD vulnerability descriptions by leveraging external resources. Zad consists of two pipelines: one collects and filters supplementary data using two encoders to build a detailed dataset, while the other fine-tunes a pre-trained model on this dataset to generate enriched descriptions. By addressing brevity and improving content quality, Zad produces more comprehensive and cohesive vulnerability descriptions. We evaluate Zad using standard summarization metrics and human assessments, demonstrating its effectiveness in enhancing vulnerability information.

cs.CR

Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations

This paper explores the vulnerability of machine learning models to simple single-feature adversarial attacks in the context of Ethereum fraudulent transaction detection. Through comprehensive experimentation, we investigate the impact of various adversarial attack strategies on model performance metrics. Our findings, highlighting how prone those techniques are to simple attacks, are alarming, and the inconsistency in the attacks' effect on different algorithms promises ways for attack mitigation. We examine the effectiveness of different mitigation strategies, including adversarial training and enhanced feature selection, in enhancing model robustness and show their effectiveness.

cs.CR

Fishing for Phishers: Learning-Based Phishing Detection in Ethereum Transactions

Phishing detection on Ethereum has increasingly leveraged advanced machine learning techniques to identify fraudulent transactions. However, limited attention has been given to understanding the effectiveness of feature selection strategies and the role of graph-based models in enhancing detection accuracy. In this paper, we systematically examine these issues by analyzing and contrasting explicit transactional features and implicit graph-based features, both experimentally and analytically. We explore how different feature sets impact the performance of phishing detection models, particularly in the context of Ethereum's transactional network. Additionally, we address key challenges such as class imbalance and dataset composition and their influence on the robustness and precision of detection methods. Our findings demonstrate the advantages and limitations of each feature type, while also providing a clearer understanding of how feature affect model resilience and generalization in adversarial environments.

cs.CR

Network-based Analysis and Classification of Malware using Behavioral Artifacts Ordering

Using runtime execution artifacts to identify malware and its associated family is an established technique in the security domain. Many papers in the literature rely on explicit features derived from network, file system, or registry interaction. While effective, the use of these fine-granularity data points makes these techniques computationally expensive. Moreover, the signatures and heuristics are often circumvented by subsequent malware authors. In this work, we propose Chatter, a system that is concerned only with the order in which high-level system events take place. Individual events are mapped onto an alphabet and execution traces are captured via terse concatenations of those letters. Then, leveraging an analyst labeled corpus of malware, n-gram document classification techniques are applied to produce a classifier predicting malware family. This paper describes that technique and its proof-of-concept evaluation. In its prototype form, only network events are considered and eleven malware families are used. We show the technique achieves 83%-94% accuracy in isolation and makes non-trivial performance improvements when integrated with a baseline classifier of combined order features to reach an accuracy of up to 98.8%.

cs.CR

Downlink macro-diversity precoding-aided spatial modulation

In this paper, a downlink macro-diversity precodingaided spatial modulation (MD-PSM) scheme is proposed, in which two base stations (BSs) communicate simultaneously with a single mobile station (MS). As such, the proposed scheme achieved twice the spectral efficiency of the conventional PSM scheme. To render the demodulation possible, the two signal constellation sets used at the two BSs should be disjoint. Also, since the two BSs use the same spatial dimension, i.e., indices of receive antennas, the Minkowski sum of the two constellation sets should include unrepeated symbols. This is achieved through rotating the constellation set used by the second BS, where the error rate is also minimized. After obtaining the optimal rotation angles for several scenarios, a reduced complexity maximum-likelihood receiver is introduced. For an equal number of transmit and receive antennas of 4 and at a target BER of 10^{-4}, the simulation results show that the proposed MD-PSM scheme outperforms the conventional PSM by about 17.3 dB and 12.4 dB, while achieving the same and double the spectral efficiency, respectively. Also, due to the distributed nature of MDPSM, it is shown that the diversity order of the novel MD-PSM scheme is twice that of the conventional PSM.

cs.IT

Complex Quadrature Spatial Modulation

In this paper, we propose a spatial modulation (SM) scheme referred to as complex quadrature spatial modulation (CQSM). In contrast to quadrature spatial modulation (QSM), CQSM transmits two complex signal constellation symbols on the real and quadrature spatial dimensions at each channel use, increasing the spectral efficiency. To this end, signal symbols transmitted at any given time instant are drawn from two different modulation sets. The first modulation set is any of the conventional QAM/PSK alphabets, while the second is a rotated version of it. The optimal rotation angle is obtained through simulations for several modulation schemes and analytically proven for the case of QPSK, where both results coincide. Simulation results showed that CQSM outperformed QSM and generalized SM (GSM) by approximately 5 and 4.5 dB, respectively, for the same transmission rate. Its performance was similar to that of QSM; however, it achieved higher transmission rates. It was additionally shown numerically and analytically that CQSM outperformed QSM for a relatively large number of transmit antennas.

cs.IT

Fixed-complexity Sphere Encoder for Multi-user MIMO Systems

In this paper, we propose a fixed-complexity sphere encoder (FSE) for multi-user MIMO (MU-MIMO) systems. The proposed FSE accomplishes a scalable tradeoff between performance and complexity. Also, because it has a parallel tree-search structure, the proposed encoder can be easily pipelined, leading to a tremendous reduction in the precoding latency. The complexity of the proposed encoder is also analyzed, and we propose two techniques that reduce it. Simulation and analytical results demonstrate that in a 4 by 4 MU-MIMO system, the proposed FSE requires only 11.5% of the computational complexity needed by the conventional QRD-M encoder (QRDM-E). Also, the encoding throughput of the proposed encoder is 7.5 times that of the QRDM-E with tolerable degradation in the BER performance, while achieving the optimum diversity order.

cs.IT

Lattice Reduction Aided Precoding for Multiuser MIMO using Seysen's Algorithm

Lenstra-Lenstra-Lovasz (LLL) algorithm, which is one of the lattice reduction (LR) techniques, has been extensively used to obtain better basis of the channel matrix. In this paper, we jointly apply Seysen's lattice reduction algorithm (SA), instead of LLL, with the conventional linear precoding algorithms. Since SA obtains more orthogonal lattice basis compared to that obtained by LLL, lattice reduction aided (LRA) precoding based on SA algorithm outperforms the LRA precoding with LLL. Simulation results demonstrate that a gain of 0.5dB at target BER of 10^-5 is achieved when SA is used instead of LLL for the LR stage.

cs.IT

Improved Achievable Rates for Regularized Tomlinson-Harashima Precoding in Multiuser MIMO Downlink

Tomlinson-Harashima precoding (THP) is considered as a prominent precoding scheme due to its capability to efficiently cancel out the known interference at the transmitter side. Therefore, the information rates achieved by THP are superior to those achieved by conventional linear precoding schemes. In this paper, a new lower bound on the achievable information rate for the regularized THP scheme under additive white Gaussian noise (AWGN) channel with multiuser interference is derived. Analytical results show that the lower bound derived in this paper is tighter than the original lower bound particularly for a low SNR range, while all lower bounds converge to 0.5xlog2(6SNR/πe) as SNR approaches infinity.

cs.IT

On Transmit Antenna Selection for Multiuser MIMO Systems with Dirty Paper Coding

In this paper, we address the transmit antenna selection in multi-user MIMO systems with precoding. The optimum and reduced complexity sub-optimum antenna selection algorithms are introduced. QR-decomposition (QRD) based antenna selection is investigated and the reason behind its sub-optimality is analytically derived. We introduce the conventional QRD-based algorithm and propose an efficient QRD-based transmit antenna scheme (maxR) that is both implementation and performance efficient. Moreover, we derive explicit formulae for the computational complexities of the aforementioned algorithms. Simulation results and analysis demonstrate that the proposed maxR algorithm requires only 1% of the computational efforts required by the optimal algorithm for a degradation of 1dB and 0.1dB in the case of linear zero-forcing and Tomlinson-Harashima precoding schemes, respectively.

cs.IT

Coordinated transmit and receive processing with adaptive multi-stream selection

In this paper, we propose an adaptive coordinated Tx-Rx beamforming scheme for inter-user interference cancellation, when a base station (BS) communicates with multiple users that each has multiple receive antennas. The conventional coordinated Tx-Rx beamforming scheme transmits a fixed number of data streams for each user regardless of the instantaneous channel states, that is, all the users, no matter they are with ill-conditioned or well-conditioned channels, have the same number of data streams. However, in the proposed adaptive coordinated Tx-Rx beamforming scheme, we adaptively select the number of streams per user to solve the inefficient problem of the conventional coordinated Tx-Rx beamforming scheme. As a result, the BER performance is improved. Simulation results show that the proposed algorithm outperforms the conventional co-ordinated Tx-Rx beamforming algorithm by 2.5dB at a target BER of 10^-2

cs.IT

Upper-lower bounded-complexity QRD-M for spatial multiplexing MIMO-OFDM systems

Multiple-input multiple-output (MIMO) technology applied with orthogonal frequency division multiplexing (OFDM) is considered as the ultimate solution to increase channel capacity without any additional spectral resources. At the receiver side, the challenge resides in designing low complexity detection algorithms capable of separating independent streams sent simultaneously from different antennas. In this paper, we introduce an upper-lower bounded-complexity QRD-M algorithm (ULBC QRD-M). In the proposed algorithm we solve the problem of high extreme complexity of the conventional sphere decoding by fixing the upper bound complexity to that of the conventional QRD-M. On the other hand, ULBC QRD-M intelligently cancels all unnecessary hypotheses to achieve very low computational requirements. Analyses and simulation results show that the proposed algorithm achieves the performance of conventional QRD-M with only 26% of the required computations.

cs.IT

Parallel QR decomposition in LTE-A systems

The QR Decomposition (QRD) of communication channel matrices is a fundamental prerequisite to several detection schemes in Multiple-Input Multiple-Output (MIMO) communication systems. Herein, the main feature of the QRD is to transform the non-causal system into a causal system, where consequently efficient detection algorithms based on the Successive Interference Cancellation (SIC) or Sphere Decoder (SD) become possible. Also, QRD can be used as a light but efficient antenna selection scheme. In this paper, we address the study of the QRD methods and compare their efficiency in terms of computational complexity and error rate performance. Moreover, a particular attention is paid to the parallelism of the QRD algorithms since it reduces the latency of the matrix factorization.

cs.OH

Maximum-likelihood co-channel interference cancellation with power control for cellular OFDM networks

In cellular Orthogonal Frequency Division Multiplexing (OFDM) networks, Co-Channel Interference (CCI) leads to severe degradation in the BER performance. To solve this problem, Maximum-Likelihood Estimation (MLE) CCI cancellation scheme has been proposed in the literature. MLE CCI cancellation scheme generates weighted replicas of the transmitted signals and selects replica with the smallest Euclidean distance from the received signal. When the received power of the desired and interference signals are nearly the same, the BER performance is degraded. In this paper, we propose an improved MLE CCI canceler with closed-loop Power Control (PC) scheme capable of detecting and combating against the equal received power situation at the Mobile Station (MS) receiver by using the newly introduced parameter Power Ratio (PR). At cell edge where Signal to Interferer Ratio (SIR) is considered to have average value between -5 and 10 dB, computer simulations show that the proposed closed-loop PC scheme has a gain of 7 dB at 28 km/h and about 2 dB at 120 km/h.

cs.IT

On the achievable improvement by the linear minimum mean square error detector

Linear minimum mean square error (MMSE) detector has been shown to alleviate the noise amplification problem, resulting in the conventional zero-forcing (ZF) detector. In this paper, we analyze the performance improvement by the MMSE detector in terms of the condition number of its filtering matrix, and in terms of the post-precessing signal to noise ratio (SNR) improvement. To this end, we derive explicit formulas for the condition numbers of the filtering matrices and the post-processing SNRs. Analytical and simulation results demonstrate that the improvement achieved by the MMSE detector over the ZF detector is not only dependent on the noise variance and the condition number of the channel matrix, but also on how close the smallest singular values are to the noise variance.

cs.IT

Fixed-complexity vector perturbation with Block diagonalization for MU-MIMO systems

Block diagonalization (BD) is an attractive technique that transforms the multi-user multiple-input multiple-output (MU-MIMO) channel into parallel single-user MIMO (SU-MIMO) channels with zero inter-user interference (IUI). In this paper, we combine the BD technique with two deterministic vector perturbation (VP) algorithms that reduce the transmit power in MU-MIMO systems with linear precoding. These techniques are the fixed-complexity sphere encoder (FSE) and the QR-decomposition with M-algorithm encoder (QRDM-E). In contrast to the conventional BD VP technique, which is based on the sphere encoder (SE), the proposed techniques have fixed complexity and a tradeoff between performance and complexity can be achieved by controlling the size of the set of candidates for the perturbation vector. Simulation results and analysis demonstrate the properness of the proposed techniques for the next generation mobile communications systems which are latency and computational complexity limited. In MU-MIMO system with 4 users each equipped with 2 receive antennas, simulation results show that the proposed BD-FSE and BD-QRDM-E outperforms the conventional BD-THP (Tomlinson Harashima precoding) by 5.5 and 7.4dB, respectively, at a target BER of 10^{-4}.

cs.IT

Radio Transmission Performance of EPCglobal Gen-2 RFID System

In this paper, we analyze the performance of the encoding and the modulation processes in the downlink and uplink of the EPCglobal Gen2 system through the analysis and simulation. Furthermore, the synchronization issues on time and frequency domain and the preamble architecture are evaluated. Through the simulation in the uplink, we find that the detection probability of FM0 and Miller coding approaches 1 at 13dB Eb/N0.

cs.OH