To improve the flow of quality information and combat fake news on social media, it is essential to identify the origins and evolution patterns of false information. However, scholarship dedicated to ...this area is lacking. Using a recent development in the field of computational network science (i.e., evolution tree analysis), this study examined this issue in the context of the 2016 US presidential election. By retrieving 307,738 tweets about 30 fake and 30 real news stories, we examined the root content, producers of original source, and evolution patterns. The findings revealed that root tweets about fake news were mostly generated by accounts from ordinary users, but they often included a link to non-credible news websites. Additionally, we observed significant differences between real and fake news stories in terms of evolution patterns. In our evolution tree analysis, tweets about real news showed wider breadth and shorter depth than tweets about fake news. The results also indicated that tweets about real news spread widely and quickly, but tweets about fake news underwent a greater number of modifications in content over the spreading process.
•The evolution tree analysis was performed on tweets about real and fake news stories.•Most root tweets about fake news were generated by ordinary users.•Root tweets about fake news often included a link to non-credible news websites.•Tweets about fake news undergo frequent modifications in the original content over the spreading process.•Tweets about real news spread widely without modifications in the original content.
A variety of anti-malware scanners have been developed for malware detection. Previous research has indicated that combining multiple different scanners can achieve better result compared to any ...single scanner. However, given the diversity in detection rates and accuracy of different anti-malware scanners, how to determine the best possible outcome of multi-scanner systems in terms of accuracy and how to achieve this best outcome remain formidable tasks. In this paper, we propose three models to capture the combined output of different combinations of anti-malware scanners based on the limited amount of historical information available. These models enable us to predict the accuracy level of each combination, which helps us to determine the optimal configuration of the multi-scanner detection system to achieve maximum accuracy. We also introduce two methods to identify a near-optimal subset of scanners that can help reduce scanning cost while under time constraint. From simulations over randomly generated hypothetical datasets and experiments conducted with real world malware and goodware datasets and anti-virus scanners, we found that our models perform well in predicting the optimal configuration and can achieve an accuracy as high as within 1% of true maximum.
The SYN flooding attack is widely used in cyber attacks because it paralyzes the network by causing the system and bandwidth resources to be exhausted. This paper proposed a self‐information approach ...for detecting the SYN flooding attack and provided a detection algorithm with a hierarchical policy on a detection time domain. Compared with other detection methods of entropy measurement, the proposed approach is more efficient in detecting the SYN flooding attack, providing low misjudgment, hierarchical detection policy, and low time complexity. Furthermore, we proposed a detection algorithm with limiting system resources. Thus, the time complexity of our approach is only (log n) with lower time complexity and misjudgment rate than other approaches. Therefore, the approach can detect the denial‐of‐service/distributed denial‐of‐service attacks and prevent SYN flooding attacks.
We present a security management strategy of cyber-deception to protect the content-data cache sites of a Content Distribution Network. The design goal is to reduce the variance between client ...experienced delays in accessing content-data. This creates a homogeneous attack surface for an adversary who is unable to exploit latency differentials to learn the network topology which is a crucial prerequisite for carrying out attacks like LFAs (link flooding attacks). We show how this minimum variance paradigm results in a comprehensive scheme for cyber-deception management. The novelty of this approach is that it specifies not only the optimal network reconfigurations but also transition probabilities, unifying two common themes in security management: i) proactive obfuscation to increase the complexity of the attack surface and ii) reactive randomization of the target based on the attacker model. We illustrate this method of security management with several numerical examples.
Cooperative Adaptive Cruise Control (CACC) provides benefits of increasing roadway capacity and reducing energy consumption, but it can cause safety problems if a CACC vehicle has a faulty sensor ...which does not measure inter-vehicle distance correctly. In this paper, we assess the impact of faulty sensors on CACC vehicles in various traffic scenarios generated using the OSMWebWizard of the SUMO traffic simulator. We involve vehicles that use CACC and ACC in the tested traffic scenarios and simulate faulty equipment by varying the tau variable below the default step-length and note down the number of collisions that occur as a result. We also measure the impact of varying the deceleration rate to see if harder or softer braking can reduce the number of collisions. Based on the results, we recommend using a bidirectional topology instead of the traditional look ahead topology and to exert softer breaking when detecting that the distance from the front vehicle is less than the normal gap value.
With the rapid advancement and wide application of blockchain technology, blockchain consensus protocols, which are the core part of blockchain systems, along with the privacy issues, have drawn much ...attention from researchers. A key aspect of privacy in the blockchain is the sensitive content of transactions in the permissionless blockchain. Meanwhile, some blockchain applications, such as cryptocurrencies, are based on low-efficiency and high-cost consensus protocols, which may not be practical and feasible for other blockchain applications. In this paper, we propose an efficient and privacy-preserving consensus protocol, called Delegated Proof of Secret Sharing (DPoSS), which is inspired by secure multiparty computation. Specifically, DPoSS first uses polynomial interpolation to select a dealer group from many nodes to maintain the consensus of the blockchain system, in which the dealers in the dealer group take turns to pack the new block. In addition, since the content of transactions is sensitive, our proposed design utilizes verifiable secret sharing to protect the privacy of transmission and defend against the malicious attacks. Extensive experiments show that the proposed consensus protocol achieves fairness during the process of reaching consensus.
Application repackaging is a severe threat to Android users and the market. Not only does it infringe on intellectual property, but it is also one of the most common ways of propagating mobile ...malware. Existing countermeasures mostly detect repackaging based on app similarity measurement, which tends to be imprecise when obfuscations are applied to repackaged apps. Moreover, they rely on a central party, typically the hosting app store, to perform the detection, but many app stores fail to commit proper effort to piracy detection. We consider building the application repackaging detection capability into apps, such that user devices are made use to detect repackaging in a decentralized fashion. The main challenge is how to protect the detection code from being manipulated by attacks . We propose a creative use of logic bombs , which are otherwise regularly used in malware. The trigger conditions of bombs are constructed to exploit the differences between the attacker and users, such that a bomb that lies dormant on the attacker side will be activated on the user side. The detection code, which is part of the bomb payload , is executed only if the bomb is activated. We introduce cryptographically obfuscated logic bomb to enhance the bomb: (1) the detection code is woven into the neighboring original app code, (2) the mixed code gets encrypted using a key, and (3) the key is deleted from the app and can only be derived when the bomb is activated. Thus, attacks that try to modify or delete the detection code will corrupt the app itself, and searching the key in the application will be in vain. Moreover, we propose a bomb spraying technique that allows many bombs to be injected into an app, multiplying the needed adversary effort for bypassing the detection. In addition to repackaging detection, we present application tampering detection to fight attacks that insert malicious code into repackaged apps. We have implemented a prototype, named BombDroid , that builds repackaging and tampering detection into apps through bytecode instrumentation. The evaluation and the security analysis show that the technique is effective, efficient, and resilient to various bomb analysis techniques including fuzzing, symbolic execution, multi-path exploration, and program slicing. Ethical issues due to the use of logic bombs are also discussed.
The global coronavirus pandemic is reshaping our daily lives and has forced many people to work and socialize remotely. This trend also increases the demand for highly available and trustworthy ...Internet access. Compared with 4G networks, 5G mobile networks are designed to accommodate the increasing number of mobile devices with higher transfer speed, lower latency and improved security. The 5G standard in USA uses millimeter waves, which is much shorter than 4G LTE signals. The shorter wavelength means 5G can transfer data much faster than 4G, but it also results in a much shorter travel range. When a user is moving among 5G cells, repeated authentications will increase delay time which contradicts 5G objective. The blockchain technology has the advantage of better transparency, enhanced security and high efficiency. In this paper, we propose an efficient authentication approach for 5G network using blockchain technology to reduce repeated authentications and keep the cost low and practical. We will compare it with some existing protocols and analyze its security against several possible attacks.
Due to deep automation, the configuration of many Cloud infrastructures is static and homogeneous, which, while easing administration, significantly decreases a potential attacker's uncertainty on a ...deployed Cloud-based service and hence increases the chance of the service being compromised. Moving-target defense (MTD) is a promising solution to the configuration staticity and homogeneity problem. This paper presents our findings on whether and to what extent MTD is effective in protecting a Cloud-based service with heterogeneous and dynamic attack surfaces - these attributes, which match the reality of current Cloud infrastructures, have not been investigated together in previous works on MTD in general network settings. We 1) formulate a Cloud-based service security model that incorporates Cloud-specific features such as VM migration/snapshotting and the diversity/compatibility of migration, 2) consider the accumulative effect of the attacker's intelligence on the target service's attack surface, 3) model the heterogeneity and dynamics of the service's attack surfaces, as defined by the (dynamic) probability of the service being compromised, as an S-shaped generalized logistic function, and 4) propose a probabilistic MTD service deployment strategy that exploits the dynamics and heterogeneity of attack surfaces for protecting the service against attackers. Through simulation, we identify the conditions and extent of the proposed MTD strategy's effectiveness in protecting Cloud-based services. Namely, 1) MTD is more effective when the service deployment is dense in the replacement pool and/or when the attack is strong, and 2) attack-surface heterogeneity-and-dynamics awareness helps in improving MTD's effectiveness.
Recent research activities are focused on improving Vehicle-to-Vehicle Communication (V2V) based on the 5G Technology. V2V applications are important because they are expected to reduce the risk of ...accidents up to 80%, enhance traffic management, mitigate congestion, and optimize fuel consumption. Typical autonomous vehicle applications require a high bandwidth transmission channel, so the 5G communication channel might be a reliable solution to support this technology. The dedicated short-range communications (DSRC), characterized by a frequency bandwidth of 5.9 GHz, were used as vehicular connectivity with bandwidth up to 200 mb/s and limited capacity, and it is here utilized for comparison to 5G. The 5G band can support connected autonomous vehicles with higher data rates and larger bandwidth. The 5G communication channel is suitable for vehicular connectivity since it has a very high bandwidth in the millimeter waves spectrum range. The quality of 5G wireless communication channels between connected vehicles is affected by weather conditions such as rain, snow, fog, dust, and sand. In this paper, the effect of dust and sand on the propagation of millimeter waves is presented. The effect of dust and sand on the communication path loss of DSRC and 5G frequency band is investigated in the case of Urban area and Highway condition. Results show that the attenuation caused by dust and sand depends on the particle size of sand,frequency of propagating wave, and concentration of dust. Finally, a new model of link margin is proposed to estimate the effect of dust and sand on DSRC (5.9 GHz) and 5G (28 GHz-73.5 GHz) communication path loss.
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