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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.

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.

Analyzing security protocol web implementations is a crucial part of web security. Based on the model extraction technology, this paper first defines SubJavaScript and SubPython languages, and then establishes mapping models from SubPython and SubJavaScript to Applied PI Calculus respectively, after that, develops the semi-automatic model extraction tools SubPython2PV and SubJavaScript2PV to analyze the four widely used security protocol web implementations. The experiment shows that the four typical security protocol web implications have confidentiality, but lack of authentication.

The security analysis of Security Protocol Implementations(SPI) is an important part of cybersecurity. However, with the strength of property protection and the widely used applications of code obfuscation technology, the previous security analysis method based on SPI is hard to carry out. Therefore, under the condition that SPI is not available, this paper analyzes the security of the SPI using the unpurified security protocol traces and security protocol implementation ontology. First, we construct the implementation ontology to describes the attributes of the ontology terms. Second, the format analysis method is presented based on unpurified flow. Third, the mapping method is proposed to build the mapping between the security protocol trace and the implementation ontology. Fourth, a is presented to analyze the security of SPI. Finally, FSIA software is designed and implemented according to the method we proposed to analyze the login module of a university information system, the result shows that there is a risk of Ticket leakage in the login module. Compared to the previous method,our proposed method can deal with unpurified network traces and find the vulnerabilities of network and system.

Mobile multihop relay (MMR) WiMAX networks have attracted lots of interest in the wireless communication industry recently because of its scalable coverage, improved data rates, and relatively low cost. However, security of MMR WiMAX networks is the main challenge to be addressed. In this paper, we first identify several possible attacks on MMR WiMAX networks in which a rogue base station (BS) or relay station (RS) can get authenticated and gain control over the connections and show that the current standard does not address this problem well. We then propose a set of new authentication protocols for protecting MMR WiMAX networks from rogue BS attack, rogue RS attack, and suppress-replay attack. Our protocols can provide centralized authentication by using a trusted authentication server to support mutual authentication between RS and BS, between RS and RS, and between mobile station (MS) and RS. Moreover, our protocols can also provide distributed authentication with a license issued by the trusted server. We use a formal tool called Scyther to analyze and verify the security properties of our protocols. The results show that our protocols can counter rogue BS and RS attacks and suppress-replay attack and are not susceptible to any known attacks.

Effectively adding security measures to a multicast service is an intriguing problem, especially when the service isdeployed in a wireless setting. Next generation IEEE 802.16standard WirelessMAN networks are a perfect example of this problem, and the latest draft specification of the standard includes a secure protocol solution called Multicast and Broadcast Rekeying Algorithm (MBRA). In this paper, we expose the security problems of MBRA, including non-scalability and omission of backward and forward secrecy, and propose new approaches, ELAPSE and ELAPSE+, to address these problems. In particular, ELAPSE+ makes use of membership and mobility information gathered in the application layer to augment the adaptive group management in the MAC layer. We analyze the security property of ELAPSE and ELAPSE+, and compare their performances with MBRA by simulating group rekeying scenarios.

Research in bioinformatics primarily involves collection and analysis of a large volume of genomic data. Naturally, it demands efficient storage and transfer of this huge amount of data. In recent years, some research has been done to find efficient compression algorithms to reduce the size of various sequencing data. One way to improve the transmission time of large files is to apply a maximum lossless compression on them. In this paper, we present SAMZIP, a specialized encoding scheme, for sequence alignment data in SAM (Sequence Alignment/Map) format, which improves the compression ratio of existing compression tools available. In order to achieve this, we exploit the prior knowledge of the file format and specifications. Our experimental results show that our encoding scheme improves compression ratio, thereby reducing overall transmission time significantly.