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Long non-coding RNAs (lncRNAs) are endogenous molecules longer than 200 nucleotides, and lack coding potential. LncRNAs that interact with microRNAs (miRNAs) are known as a competing endogenous RNAs (ceRNAs) and have the ability to regulate the expression of target genes. The ceRNAs play an important role in the initiation and progression of various cancers. However, until now, there is no a database including a collection of experimentally verified, human ceRNAs. We developed the LncCeRBase database, which encompasses 432 lncRNA–miRNA–mRNA interactions, including 130 lncRNAs, 214 miRNAs and 245 genes from 300 publications. In addition, we compiled the signaling pathways associated with the included lncRNA–miRNA–mRNA interactions as a tool to explore their functions. LncCeRBase is useful for understanding the regulatory mechanisms of lncRNA.Database URL: http://lnccerbase.it1004.com

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With the trend of digital transformation of enterprises, the use of Internet of Things (IoT) devices is increasing. IoT devices that are not protected by security measures have gradually become targets of attackers. Attackers use weak passwords and software vulnerabilities in the device to invade the device and control it to become a node of the botnet. The Mozi botnet was discovered in December 2019, and its attention has increased day by day, and its influence once exceeded Mirai. After a preliminary reverse analysis of the Mozi samples, we have continued to track the development and changes of the Mozi botnet since February 2021. First, through the in-depth analysis of the communication principles of the Mozi botnet and the distributed sloppy hash table protocol, we have proposed an in-depth analysis of the Mozi botnet. The active detection method of Mozi, through daily and continuous tracking of the number of Mozi nodes, is infinitely close to the boundary of the Mozi network. On the basis of the collected detection data, we give our conclusions on Mozi's node size, global geographic distribution, 24-hour global activity, equipment composition, and Mozi botnet countermeasures.Through this study, we found that the security of IoT devices around the world is not optimistic, and there is an urgent need to increase the security protection

As information technology develops, cloud storage has been widely accepted for keeping volumes of data. Remote data auditing scheme enables cloud user to confirm the integrity of her outsourced file via the auditing against cloud storage, without downloading the file from cloud. In view of the significant computational cost caused by the auditing process, outsourced auditing model is proposed to make user outsource the heavy auditing task to third party auditor (TPA). Although the first outsourced auditing scheme can protect against the malicious TPA, this scheme enables TPA to have read access right over user's outsourced data, which is a potential risk for user data privacy. In this paper, we introduce the notion of User Focus for outsourced auditing, which emphasizes the idea that lets user dominate her own data. Based on User Focus, our proposed scheme not only can prevent user's data from leaking to TPA without depending on data encryption but also can avoid the use of additional independent random source that is very difficult to meet in practice. We also describe how to make our scheme support dynamic updates. According to the security analysis and experimental evaluations, our proposed scheme is provably secure and significantly efficient.

Software-defined networking (SDN) is a new networking paradigm that realizes the fast management and optimal configuration of network resources by decoupling control logic and forwarding functions. However, centralized network architecture brings new security problems, and denial-of-service (DoS) attacks are among the most critical threats. Due to the lack of an effective message-verification mechanism in SDN, attackers can easily launch a DoS attack by faking the source address information. This paper presents DoSGuard, an efficient and protocol-independent defense framework for SDN networks to detect and mitigate such attacks. DoSGuard is a lightweight extension module on SDN controllers that mainly consists of three key components: a monitor, a detector, and a mitigator. The monitor maintains the information between the switches and the hosts for anomaly detection. The detector utilizes OpenFlow message and flow features to detect the attack. The mitigator protects networks by filtering malicious packets. We implement a prototype of DoSGuard in the floodlight controller and evaluate its effectiveness in a simulation environment. Experimental results show the DoSGuard achieves 98.72% detecion precision, and the average CPU utilization of the controller is only around 8%. The results demonstrate that DoSGuard can effectively mitigate DoS attacks against SDN with limited overhead.