Emulation Attack Research Articles

On optimal sample checkpoint for energy efficient cooperative spectrum sensing

Energy efficient and fast yet reliable spectrum sensing in cognitive radio networks (CRNs) is an important issue and is often met through the involvement of (optimal) multiple sensing nodes in collaboration known as cooperative spectrum sensing (CSS). However, due to severe fading, sometimes transmission of sensing samples over some reporting channels (R-channels) consume much energy but contribute very little on global sensing decision. To address the problem, this work explores the scope of using an optimal checkpoint to stop further transmission of sensing samples over the deeply faded R-channels. First an energy minimization problem under the constraints of detection and false alarm probabilities is developed in an amplify forward relay assisted CSS system in terms of optimal sample checkpoint, the number of essential sensing/relay nodes and relay power gain. The problem is further extended in presence of primary user emulation attack (PUEA). Simulation results show that a performance gain ∼77.17% and ∼71.25% in energy consumption can be achieved for the proposed approach as compared to the existing two works at Pd=0.9 and Pf=0.05.

Defense against primary user emulation attacks from the secondary user throughput perspective

The maximization of Secondary user (SU) throughput has been studied extensively in honest cooperative spectrum sensing (CSS). However, when primary user emulation attacks (PUEAs) are launched, the model of CSS changes. This also necessitates the redesigning of the SU throughput maximisation scheme. In this paper, such redesigning of the SU throughput maximisation scheme under PUEAs has been carried out. Our objective is to suppress the damages caused by the PUEAs on the SU throughput. To serve this purpose, an optimally weighted CSS has been proposed. The optimal weights are obtained by maximising the SU throughput while protecting the primary user (PU) from interference in a network facing the PUEAs. Considering the significance of simplicity and speed in CSS, we apply the Nelder Mead Simplex Algorithm to solve the problem. The experiments carried out endorse the effectiveness of the proposed scheme compared to the existing combination schemes.

Cross Layer Design Based Channel Aware Multipath Routing Towards Primary User Emulation Attack

Cross Layer Design Based Channel Aware Multipath Routing Towards Primary User Emulation Attack

Identification as a deterrent for security enhancement in cognitive radio networks

Cognitive Radio Networks (CRNs) are prone to emerging coexistence security threats such as Primary User Emulation Attack (PUEA). Specifically, a malicious CRN may mimic licensees’ (Primary Users (PUs)) signal characteristics to force another CRN to vacate its channels thinking that PUs have returned. While existing schemes are promising to some extent on detecting PUEAs, they are not able to prevent the attacks. In this article, we propose a PUEA Deterrent (PUED) algorithm that can provide PUEAs' commission details: offender CRNs and attacks’ time and bandwidth. There are many similarities between PUED and Closed-Circuit Television (CCTV) in terms of: deterrence strategy, reason for use, surveillance characteristics, surveillance outcome, and operation site. According to the criminology literature, robust CCTV systems have shown a significant reduction in visible offences (e.g. vehicle theft), reducing crime rates by 80%. Similarly, PUED will contribute the same effectiveness in deterring PUEAs. Furthermore, providing PUEAs’ details will prevent the network’s cognitive engine from considering the attacks as real PUs, consequently avoiding devising unreliable spectrum models for the attacked channels. Extensive simulations show the effectiveness of the PUED algorithm in terms of improving CRNs’ performance.

Protection Against Defecting Attack and Enhanced Channel Allocation for Video Streaming in CRN

Arising issue of spectrum scarcity is resolved by emerging cognitive radio technology. In which, unoccupied portion of licensed spectrum would be granted for unlicensed user in order to upgrade the spectrum utilization. Spectrum sensing is an enabling task for labeling the spectrum holes and away from spectrum congestion in cognitive radio networks. Impact of secondary user’s cooperation developed cooperative spectrum sensing for effective spectrum sensing, many secondary users are to be associated in sensing the idle channels. Adversary secondary users (SU) mimic as primary user in cooperative sensing scheme, called primary user emulation attack (PUEA). If any SU forges the sensing data, that is known as spectrum sensing data falsification attack (SSDF). Rescuing the network against these two attacks is the major issue of cognitive radio networks. To address these challenges, we propose cognitive radio network to ensure security in cooperative spectrum sensing for video streaming application. Sensing based clustering algorithm assembles the cognitive radios into clusters to mitigate cooperative overhead and consumed energy. In order to avert PUEA attacks, we introduce authentication signature ID algorithm which provides authority for licensed user to use spectrum. To diminish SSDF attacks, we exploit Hamming algorithm to abolish forgery node from spectrum sensing decision. Furthermore PRN channel allocation algorithm is employed to precisely deliver the video with high quality and lower delay. For video transmission in cognitive radio network, we need to compress the video frames by block truncation coding-pattern fitting in order to reduce bandwidth consumption. This compression technique offers good video transmission with high compression ratio in cognitive radio network, due to trade-off among quality, bit rate and decoding time. Our proposed framework demonstrates the simulation with improved detection rate of idle channel and reduced the delay for high quality video transmission.

Intelligent resource allocation scheme for the cognitive radio network in the presence of primary user emulation attack

An energy-efficient cognitive radio network (CRN) design is one of the primary requirements for the low-battery-driven wireless terminals in the presence of primary user emulation attack. Furthermore, sensing accuracy is also essential for allocating vacant bands to the secondary users (SUs) for data transmission. Hence, this study focuses on designing an energy-efficient double threshold-based CRN. The adversarial effects arising in the presence of the attacker are analysed and are treated as constraints while formulating the energy efficiency (EE) maximisation problem. To develop the formulation, a unique SU selection algorithm to identify most eligible SUs for data transmission is proposed. The EE is then maximised by minimising the total power consumption through novel adaptive resource allocation algorithm. Hence, the authors proposed approaches are based on the suitable selection of SUs and adaptive power allocation under the constraints of maximum throughput, controlled transmission power providing sufficient protection to the primary user, minimum power consumption and minimum false alarm probability. The extensive simulation results demonstrate that the proposed scheme substantially increases EE with lower complexity over the conventional scheme.

On detecting primary user emulation attack using channel impulse response in the cognitive radio network

Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service (DoS) attack, named the ‘primary user emulation attack (PUEA)’, exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response (CIR) between the secondary user (SU) and the signal source is used to determine whether the received signal is transmitted by the primary user (PU) or the primary user emulator (PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.

Design of a novel dynamic trust model for spectrum management in WRANs of TV white space

The cognitive radio (CR) technique is considered as a better and more efficient answer to the predicament brought by the high demands of wireless communication services and the scarcity or low utilization of frequency spectrum resources. The IEEE 802.22 standard has regulated the wireless regional area networks (WRANs) as one example of the CR networks, which is operating in the television white space (TVWS) spectrum. In the centralized WRANs, the secondary user base station (SUBS) allocates the spectrum holes for the customer premise equipment (CPE) on the basis of the spectrum sensing information from the CPEs around. However, since the CPEs are easy compromised under the varying and uncontrollable environment, the WRANs is subjected to the primary user emulation attacks (PUEA) and the spectrum sensing data falsification (SSDF) attacks, which may lead to a wrong global spectrum decision made by SUBS. A novel dynamic trust model for the SUBS spectrum management based on the subjective logic for the centralized WRANs of TVWS is proposed in this paper. The proposed trust model has a positive impact on reducing the influence of users’ vicious behaviors and encourages the CPEs to participate in truthful actions for communications. The analysis shows that the time complexity of the proposed trust model is O(n). Simulations indicate that the proposed trust model can significantly reduce the probability of the errors by the SUBS in the spectrum decision making.

Throughput performance under primary user emulation attack in cognitive radio networks

SummarySpectrum sensing in cognitive radio networks imposes some security threats to the secondary users (SUs) such as primary user emulation attack (PUEA). In the present paper, throughput of an SU is studied for cognitive radio network under PUEA where SU spectrum access is hybrid, ie, either in overlay mode or in underlay mode. A novel analytical expression for throughput of an SU in presence of PUEA is developed. Impact of several parameters such as sensing time, attacker strength, attacker's presence probabilities, maximum allowable SU transmit power, and tolerable interference limit at primary user on the throughput of an SU is investigated. The throughput performance under PUEA and without PUEA is compared.

An intelligent resource management scheme for SDF-based cooperative spectrum sensing in the presence of primary user emulation attack

This paper focuses on designing an energy-efficient cognitive radio network (CRN) in the presence of a primary user emulation attacker. The approach requires suitable resource management schemes that help in maximizing energy efficiency (EE) of the secondary network while providing sufficient protection to the primary network. Hence, we propose a secondary users (SUs) selection algorithm for maximizing system throughput while ensuring spectrum sensing accuracy. Then the sensing time is evaluated for obtaining maximum throughput, minimum delay and minimum false alarm probability. Further, the non-linear EE maximization problem associated with the non-convex constraints is solved by our proposed novel iterative resource allocation (NIRA) algorithm to jointly optimize both sensing time and transmission power of the secondary network within which the fractional EE is transferred to convex programming by employing the Dinkelbach method in the outer layer and the constraints are addressed by dual decomposition and Difference of convex (DC) programming method. Simulation results validate the effectiveness of our proposed approaches, and the impact of different system parameters is also studied.

Detection of PUE Attack in CRN with Reduced Error in Location Estimation Using Novel Bat Algorithm

Cognitive Radio Network Technology makes the efficient utilization of scarce spectrum resources by allowing the unlicensed users to opportunistically use the licensed spectrum. Cognitive Radio Network due to its flexible and open nature is vulnerable to a number of security attacks. This paper is mainly concerned with one of the physical layer attack called Primary User Emulation Attack and its detection. This paper solves the problem of PUE attack by localization technique based on TDOA measurements with reduced error in location estimation using a Novel Bat Algorithm (NBA). A number of cooperative secondary users are used for detecting the PUEA by comparing its estimated position with the known position of incumbent. The main goal of NBA is to minimize two fitness functions namely non-linear least square and the maximum likelihood in order to optimize the estimation error. After evaluation, simulation results clearly demonstrates that NBA results in reduced estimation error as compared to Taylor Series Estimation and Particle Swarm Optimization.

Defence against primary user emulation attack using statistical properties of the cognitive radio received power

Cognitive radio (CR) is proposed to solve the spectrum scarcity problem. One of the significant issues which arises recently in CR networks is security threats. Most of the proposed methods to defend against the attacks need the previous knowledge about the system. In this study, the authors use the statistical characteristics of the users to address one of the important kinds of attacks called primary user emulation attack (PUEA). In the proposed scheme, the received power statistics of the CR users is used to detect the PUEA. The results show that their scheme has higher performance in detecting the primary transmission comparing with the previous works.

Robust Collaborative Spectrum Sensing Using PHY-Layer Fingerprints in Mobile Cognitive Radio Networks

Collaborative spectrum sensing has been proposed to significantly improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, a serious attack, called a primary user emulation attack (PUEA), could decrease the performance of collaborative spectrum sensing. In this letter, according to mobile CRNs, we propose a novel robust collaborative spectrum sensing method using physical-layer fingerprints power in a multipath Rayleigh fading channel. Moreover, a fingerprints-power-belief-based noncentral detection algorithm is designed to defend against PUEAs. Simulation results show that our proposed method can rapidly detect the presence of a primary user under PUEAs with good performance.

Maximum Utility Function Approach for Detection of Primary User Emulation Attack in Cognitive Radio Networks

Maximum Utility Function Approach for Detection of Primary User Emulation Attack in Cognitive Radio Networks

Dynamic Spectrum Utilization with Secure Sensing in E-Healthcare System

To enhance the quality of medical care, e-healthcare system becomes a promising system which integrates diverse wireless devices and technologies such as internet of things, wireless body area networks, etc. However, numerous wireless devices and communication requirements will cause the shortage of the wireless spectrum. Cognitive radio is able to exploit spectrum opportunities and increase the communication performance for the e-healthcare system. To access the spectrum safely, the security aspect of spectrum utilization should be carefully addressed. A well-known threat to the spectrum utilization is the primary user emulation attack (PUEA) in which the attackers emulate as the primary users to obtain spectrum opportunities. To defend this threat, in this paper, we propose a triple threshold energy detection (TTED) to identify the PUEA. Based on the TTED, legitimate devices are allowed to access the available channels when the licensed channel is idle or occupied by attackers. To evaluate our proposed access scheme, we derive the achievable throughput while the average transmission time is fixed and exponential distributed, respectively.

Soft Cooperative Spectrum Sensing using Quantization Method in the Presence of Smart PUE Attack

To overcome the frequency spectrum scarcity, cognitive radio (CR) network is proposed where secondary users opportunistically use vacant frequency band. CR intrinsic properties impose threats to these wireless networks. Smart primary user emulation attack (PUEA) is one of these threats where a malicious user performs spectrum sensing and after being aware of radio environment sends fake signals identical to the primary user signals with the desired signal occurrences in both vacant and occupied licensed frequency bands. In this paper, while considering smart PUEA, we propose a soft cooperative spectrum sensing method. In this method, the sensing information values of N secondary users are transmitted to the fusion center (FC) and combined with some coefficients with the aim of minimizing the error probability of primary user detection, under the given constant false alarm probability. We also propose a method for quantization of this sensing information that should be sent to FC. Furthermore, we have worked on the investigation of channel estimation error impact on detection performance. Simulation results show that our method significantly improves the spectrum sensing probability of the error, in comparison with hard combination scheme, AND fusion and OR fusion rules, either considering quantization or in the presence of channel estimation error.

Primary user Emulation Attack Defense in Filter Bank based Cognitive Radio

Background/Objectives: The spectrum scarcity problem arising due to reckless development in wireless communication can be addressed using cognitive radio technology. An important step in cognitive radio technology is spectrum sensing and associated with that is an attack called primary user emulation attack. Methods/Statistical Analysis: A two channel Quadrature Mirror Filter (QMF) bank is employed for a single user spectrum sensing. The energy detection method is used as reference for comparing the performance of the filter bank method in the presence of attackers. Existing approaches like Neyman-Pearson Criterion, Improved Detection Scheme with Double threshold and Location Verification Method for detecting PUE attacks were examined. A new method which combines improved detection scheme and location verification method is proposed for detecting PUE attacks. Findings: The simulation result shows that the filter bank method shows better performance than the energy detection method in the presence of attackers. The probability of detection of PUE attacks using improved detection scheme and location verification method for the filter bank method and energy detection method was analyzed and found out that the filter bank based spectrum sensing method outperforms energy detection method. By incorporating AND rule logic, OR rule logic and Alternate logic approach into the filter bank spectrum sensing technique, the probability of detection of PUE attack was investigated and it is seen that the probability of detection has increased to 0.98 in FB method at SNR = 1 dB when employing an alternate approach. Application/Improvements: The feasibility of deploying the filter bank method integrated with the alternate logic is to be tested using Universal Software Radio Peripheral (USRP) module.

Secure Cognitive Radio Communication for Internet-of-Things: Anti-PUE Attack Based on Graph Theory

Internet of Things (IoT) paradigm with strong impact on future life will be interconnected through Cognitive Radio Networks (CRNs). CRNs with Ubiquitous trait are highly promising to achieve interference-free and on-demand services. CRs are able to sense the spectral environment, to detect unoccupied bands, and to use them for signal transmissions. This opportunity encourages malicious Users to surpass CRs by Primary User Emulation (PUE) attack and use vacant spectrums. This paper proposes an unsupervised algorithm to distinguish CRs from PUs regardless of static and mobile user. Employing K-means and graph theory are coincident in our algorithm to improve detection outcomes. The edge of graph corresponding to the relation between signals is used and the result of comparison the signal properties is exposed to different clusters. The Receiver Operating Characteristic (ROC) and Detection Error Tradeoff (DET) of our proposed algorithm prove our claim.

Adaptive resource allocation scheme for cognitive radio vehicular ad‐hoc network in the presence of primary user emulation attack

Following the characteristics of the cognitive radio (CR) and the exponential increase of the vehicles, it is envisioned to deploy CR in vehicular ad-hoc network (VANET) in near future. Due to the mobility of the vehicles, it is quite challenging to find the vacant band and to reuse it for data transmission purpose without affecting the primary network. Further, the presence of primary user emulation attack (PUEA) in the VANET makes this task more complicated. Hence, an accurate detection technique and proper power allocation to the vehicular secondary users (VSUs) are the two major factors which need to be addressed for reliable data transmission. Hence this study attempts to evaluate the performance metrics of the CR-VANET considering the spatial correlation among the local decisions of the VSUs in the presence of PUEA. The energy efficiency maximisation with adaptive power allocation to the VSUs is achieved by the authors’ proposed scheme based on genetic algorithm under the constraints of interference power to the primary receiver, minimum achievable data rate and maximum transmission power limit. The system performance is investigated in detail through the simulation-based study and analysis.

A Primary User Emulation Attack Countermeasure Strategy and Energy-Efficiency Analysis in Cognitive Radio Networks

A Primary User Emulation Attack Countermeasure Strategy and Energy-Efficiency Analysis in Cognitive Radio Networks