Recently, machine learning techniques, especially supervised learning techniques, have been adopted in the Intrusion Detection System (IDS). Due to the limit of supervised learning, most state-of-the-art IDSs do not perform well on unknown attacks and incur high computational overhead in the Internet of Things (IoT). To overcome these challenges, we propose a novel IDS based on unsupervised techniques, namely, UTEN-IDS. UTEN-IDS uses the ensemble of autoencoders to handle the network data and performs the anomaly detection by an Isolation Forest algorithm. The effectiveness of the proposed method is verified using two benchmark datasets. The results show that our approach has significant advantages in classification performance and proves its utility in the IoT network when compared to other approaches.

Public chains represented by Bitcoin and Ethereum do not require users to use their real names, and transaction data are open to the whole network. Analysed based on this, researchers have achieved the deanonymization of blockchain transactions to a certain extent. Based on the existing blockchain transaction privacy protection scheme, the true link relationship between the transaction sender and receiver is hidden, which brings difficulties to regulation. In this paper, we propose a cryptocurrency mixing service RBSmix, which allows users to reestablish their financial privacy in Bitcoin and related cryptocurrencies. RBSmix, through blind signature to prevent attackers from linking input and output addresses, by the threshold secret sharing algorithm, encryption technology, and a regulation team, combined with the idea of voting, tracks the source of funds for illegal addresses. Experiments show that the scheme scales to large numbers of users and can provide users with better privacy protection.

As the most successful cryptocurrency, bitcoin has become the primary target of attackers. The security risks existing in bitcoin network (P2P networks) may pose serious threats to itself. It has been proved that network attackers of the autonomous system level could isolate a specific set of bitcoin nodes using prefix hijacking attacks; since this attack achieves bitcoin partition by deleting all data packets of the victim node, it is easy to be discovered by the victim node, and cannot maintain a long-term connection (the partition will disappear after canceling the BGP hijacking) (Apostolaki M et al. (2017)). This paper proposes a new attack scheme—eclipse attack method based on BGP hijacking (BHE). The attack can occupy the network connection of the victim node, and only need to delete part of the TCP handshaking packets of the victim node during the attack, and it makes the attack more hidden and can occupy the network connection of the victim node for a long time. The innovation of the BHE attack is that it can control the peering decision of the victim node by controlling the victim node’s internal peer database (new table and tried table) and preventing the victim node from establishing a good connection. It enables the attacker to occupy all network connections of the victim node and become its natural network middleman. We verify the feasibility of the BHE attack through experimental evaluation and demonstrate that an attacker who can launch BGP hijacking may occupy all connections of the victim node within 20 minutes (ignoring the time of traffic diversion). To reduce the attack’s impact, the paper provides some countermeasures that can use in practice according to the basic characteristics of the attack.