Are blockchains immune to all malicious attacks?

Background:In recent years,blockchain technology has attracted considerable attention.It records cryptographic transactions in a public ledger that is difficult to alter and compromise because of the distributed consensus.As a result,blockchain is believed to resist fraud and hacking.Results:This work explores the types of fraud and malicious activities that can be prevented by blockchain technology and identifies attacks to which blockchain remains vulnerable.Conclusions:This study recommends appropriate defensive measures and calls for further research into the techniques for fighting malicious activities related to blockchains.

Robust Hybrid Artificial Fish Swarm Simulated Annealing Optimization Algorithm for Secured Free Scale Networks against Malicious Attacks

Due to the recent proliferation of cyber-attacks,highly robust wireless sensor networks(WSN)become a critical issue as they survive node failures.Scale-free WSN is essential because they endure random attacks effectively.But they are susceptible to malicious attacks,which mainly targets particular significant nodes.Therefore,the robustness of the network becomes important for ensuring the network security.This paper presents a Robust Hybrid Artificial Fish Swarm Simulated Annealing Optimization(RHAFS-SA)Algorithm.It is introduced for improving the robust nature of free scale networks over malicious attacks(MA)with no change in degree distribution.The proposed RHAFS-SA is an enhanced version of the Improved Artificial Fish Swarm algorithm(IAFSA)by the simulated annealing(SA)algorithm.The proposed RHAFS-SA algorithm eliminates the IAFSA from unforeseen vibration and speeds up the convergence rate.For experimentation,free scale networks are produced by the Barabási–Albert(BA)model,and real-world networks are employed for testing the outcome on both synthetic-free scale and real-world networks.The experimental results exhibited that the RHAFS-SA model is superior to other models interms of diverse aspects.

Performance of Analysis Cognitive Radio with Cooperative Sensing under Malicious Attacks over Nakagami Faded Channels

The different realistic propagation channels are faced frequently the multipath fading environments. The main goal of this system design (cognitive radio network) is to improve the efficiency of spectrum access on a non-interfering basis. This system achieves high utilization for the limited spectrum in order to fulfill needs for all users’ demands which are considered as a problem in wireless communications due to rapidly increasing in wireless applications and service. This system is exposed to attack due to the vulnerabilities existence in this system. So, the main outcome of this paper is to investigate the performance of the cooperative sensing in cognitive radio networks under malicious attacks over different channel impairments, and to illustrate the most suitable individual probability of detection in real faded channel by using Nakagami model. This paper illustrates the effectiveness of the attacks and fading on the performance of spectrum sensing process.

A Secure Clock Synchronization Scheme for Wireless Sensor Networks Against Malicious Attacks

This paper studies the secure and accurate clock synchronization problem for sensor networks with time-varying delays and malicious attacks.A novel clock synchronization scheme based on the attack detection mechanism,attack compensation,and maximum consensus protocol is proposed.The proposed scheme starts with the detection of the malicious attacks and the clock data under attacks is eliminated.On the basis,software clock parameters are updated so that all the nodes in the network can have the same software skew and offset,so the clock synchronization can be achieved.Furthermore,it is theoretically proved that the proposed scheme can achieve the attack detection correctly,and further can guarantee a secure and accurate clock synchronization.In addition,extensive simulations are also conducted to validate the effectiveness of the proposed scheme.

A Compact Trust Computation and Management Approach for Defending against Derailed Attacks for Wireless Sensor Networks and Its Applications

One of the most effective measurements of intercommunication and collaboration in wireless sensor networks which leads to provide security is Trust Management. Most popular decision making systems used to collaborate with a stranger are tackled by two different existing trust management systems: one is a policy-based approach which verifies the decision built on logical properties and functionalities;the other approach is reputation-based approach which verifies the decision built on physical properties and functionalities of WSN. Proofless authorization, unavailability, vagueness and more complexity cause decreased detection rate and spoil the efficacy of the WSN in existing approaches. Some of the integrated approaches are utilized to improve the significance of the trust management strategies. In this paper, a Compact Trust Computation and Management (CTCM) approach is proposed to overcome the limitations of the existing approaches, also it provides a strong objective security with the calculability and the available security implications. Finally, the CTCM approach incorporates the optimum trust score for logical and physical investigation of the network resources. The simulation based experiment results show that the CTCM compact trust computation and management approach can provide an efficient defending mechanism against derailing attacks in WSN.

Low Area PRESENT Cryptography in FPGA Using TRNG-PRNG Key Generation

Lightweight Cryptography(LWC)is widely used to provide integrity,secrecy and authentication for the sensitive applications.However,the LWC is vulnerable to various constraints such as high-power consumption,time consumption,and hardware utilization and susceptible to the malicious attackers.In order to overcome this,a lightweight block cipher namely PRESENT architecture is proposed to provide the security against malicious attacks.The True Random Number Generator-Pseudo Random Number Generator(TRNG-PRNG)based key generation is proposed to generate the unpredictable keys,being highly difficult to predict by the hackers.Moreover,the hardware utilization of PRESENT architecture is optimized using the Dual port Read Only Memory(DROM).The proposed PRESENT-TRNGPRNG architecture supports the 64-bit input with 80-bit of key value.The performance of the PRESENT-TRNG-PRNG architecture is evaluated by means of number of slice registers,flip flops,number of slices Look Up Table(LUT),number of logical elements,slices,bonded input/output block(IOB),frequency,power and delay.The input retrieval performances analyzed in this PRESENT-TRNG-PRNG architecture are Peak Signal to Noise Ratio(PSNR),Structural Similarity Index(SSIM)and Mean-Square Error(MSE).The PRESENT-TRNG-PRNG architecture is compared with three different existing PRESENT architectures such as PRESENT On-TheFly(PERSENT-OTF),PRESENT Self-Test Structure(PRESENT-STS)and PRESENT-Round Keys(PRESENT-RK).The operating frequency of the PRESENT-TRNG-PRNG is 612.208 MHz for Virtex 5,which is high as compared to the PRESENT-RK.

Security Analysis of a Privacy-Preserving Identity-Based Encryption Architecture

Identity-Based Encryption (IBE) has seen limited adoption, largely due to the absolute trust that must be placed in the private key generator (PKG)—an authority that computes the private keys for all the users in the environment. Several constructions have been proposed to reduce the trust required in the PKG (and thus preserve the privacy of users), but these have generally relied on unrealistic assumptions regarding non-collusion between various entities in the system. Unfortunately, these constructions have not significantly improved IBE adoption rates in real-world environments. In this paper, we present a construction that reduces trust in the PKG without unrealistic non-collusion assumptions. We achieve this by incorporating a novel combination of digital credential technology and bilinear maps, and making use of multiple randomly-chosen entities to complete certain tasks. The main result and primary contribution of this paper are a thorough security analysis of this proposed construction, examining the various entity types, attacker models, and collusion opportunities in this environment. We show that this construction can prevent, or at least mitigate, all considered attacks. We conclude that our construction appears to be effective in preserving user privacy and we hope that this construction and its security analysis will encourage greater use of IBE in real-world environments.

Towards resilient average consensus in multi-agent systems:a detection and compensation approach

Consensus is one of the fundamental distributed control technologies for collaboration in multi-agent systems such as collaborative handling in intelligent manufacturing.In this paper,we study the problem of resilient average consensus for multi-agent systems with misbehaving nodes.To protect consensus value from being influenced by misbehaving nodes,we address this problem by detecting misbehaviors,mitigating the corresponding adverse impact,and achieving the resilient average consensus.General types of misbehaviors are considered,including attacks,accidental faults,and link failures.We characterize the adverse impact of misbehaving nodes in a distributed manner via two-hop communication information and develop a deterministic detection compensation based consensus(D-DCC)algorithm with a decaying fault-tolerant error bound.Considering scenarios wherein information sets are intermittently available due to link failures,a stochastic extension named stochastic detection compensation based consensus(S-DCC)algorithm is proposed.We prove that D-DCC and S-DCC allow nodes to asymptotically achieve resilient accurate average consensus and unbiased resilient average consensus in a statistical sense,respectively.Then,the Wasserstein distance is introduced to analyze the accuracy of S-DCC.Finally,extensive simulations are conducted to verify the effectiveness of the proposed algorithms.

A comparative study of network robustness measures

The robustness is an important functionality of networks because it manifests the ability of networks to resist failures or attacks. Many robustness measures have been proposed from different aspects, which provide us various ways to evaluate the network robustness. However, whether these measures can properly evaluate the network robustness and which aspects of network robustness these measures can evaluate are still open questions. Therefore, in this paper, a thorough introduction over attacks and robustness measures is first given, and then nine widely used robustness mea- sures are comparatively studied. To validate whether a robustness measure can evaluate the network robustness properly, the sensitivity of robustness measures is first studied on both initial and optimized networks. Then, the performance of robustness measures in guiding the optimization process is studied, where both the optimization process and the ob- tained optimized networks are studied. The experimental re- suits show that, first, the robustness measures are more sen- sitive to the changes in initial networks than to those in op- timized networks; second, an optimized network may not be useful in practical situations because some useful function- alities, such as the shortest path length and communication efficiency, are sacrificed too much to improve the robustness; third, the robustness of networks in terms of closely corre- lated robustness measures can often be improved together. These results indicate that it is not wise to just apply the opti- mized networks obtained by optimizing over one certain robustness measure into practical situations. Practical requirements should be considered, and optimizing over two or more suitable robustness measures simultaneously is also a promising way.