The decentralized nature of blockchain technologies can well match the needs integrity and provenances evidences collecting in digital forensics (DF) across jurisdictional borders. In this paper, a novel blockchain-based DF investigation framework Internet Things (IoT) social systems environment is proposed, which provide proof existence privacy preservation for evidence items examination. To implement such features, we present block-enabled IoT, namely, IoT forensic chain (IoTFC), offer...

Emotion recognition based on electroencephalography (EEG) has attracted significant attention due to its wide range of applications, especially in Human-Computer Interaction(HCI). Previous research treats different segments EEG signals uniformly, ignoring the fact that emotions are unstable and discrete during an extended period. In this paper, we propose a novel two-step spatial-temporal emotion framework. First, considering human not only "short-term continuity" but also "long-term...

Due to the massive amount of data in high-speed network traffic and limit on processing capability, it is a great challenge accurately measure monitor over links online. A new structure presented this paper for locating hosts associated with large connection degrees or significant changes based reversible degree sketch anomalous traffic. The builds compact summary host efficiently accurately. For each packet coming, only needs set several bits selected bit array by group hash functions....

Logs are generated by systems to record the detailed runtime information about system operations, and log analysis plays an important role in anomaly detection at host or network level. Most existing methods require a priori knowledge, which cannot be used detect new unknown anomalies. Moreover, growing volume of logs poses challenges detection. In this paper, we propose integrated method using K-prototype clustering k-NN classification algorithms, uses novel clustering-filtering-refinement...

Rumors can spread very rapidly through online social networks (OSNs), leading to huge negative impact on human society. Hence, there is an urgent need develop models that minimize the of rumors. In this article, we propose a novel framework improve cost and efficiency rumor propagation control. First, reduce controlling mechanism users' normal activities, introduce soft dynamic quarantine strategy into control new model named susceptible-infected-removed-quarantined ignorants-quarantined...

The tectonic evolutionary history between the Xing'an Block (XB) and Songliao–Xilinhot (SXB) has been hotly debated. Here, we present precise geochronological ages whole‐rock geochemical data in central Great Range for Carboniferous felsic rocks to reveal this history, as petrogenesis of these were closely related activity XB SXB. age with detailed analyses indicate three important stages magmatism: early Carboniferous, Late middle Carboniferous. granodiorites formed from partial melting...

System security monitoring has become more and difficult with the ever-growing complexity dynamicity of Internet Things (IoT). In this paper, we develop an Intelligent Maintenance Lightweight Anomaly Detection (IMLADS) for efficient management IoT. Firstly, unlike traditional system use static agents, employ mobile agent to perform data collection analysis, which can automatically transfer other nodes according pre-set task. The mobility is handled by running platform, irrelevant node or its...

The host connection degree distribution (HCDD) is an important metric for network security monitoring. However, it difficult to accurately obtain the HCDD in real time high-speed links with a massive amount of traffic data. In this paper, we propose new sketch method build probabilistic summary host's flows using uniform Flajolet-Martin combined small bitmap. To study its performance comparison previous sampling and methods, present general model that encompasses all these methods. With...

Measuring and monitoring the changes of network traffic patterns in large-scale networks are crucial for effective management. In this paper, we present a framework method detecting measuring dynamic pivotal patterns. A bidirectional regional flow model is established to aggregate packets extract metrics profiles. The characteristics flows analyzed interesting findings obtained. directed graph applied describe six features extracted capture measurements based on Renyi entropy developed...

The emergence of online social network has changed the Internet users' behaviors dramatically. Microblog, as an emerging service, attracted hundreds millions users to produce and share all kinds content since its foundation. How improve Quality Experience service keep passions for participant become one most important problems confronted by quick development microblogging services. On other hand, QoE a influences is influenced activities. In this paper, we analyzed activities in Sina Weibo,...

The timing and direction of narrowing closure the Nenjiang Ocean (NJO) by plate subduction remain poorly constrained. This paper presents geochemical, isotopic, geochronological results for Late Devonian to early Carboniferous intrusive rocks in western Songliao–Xilinhot block constrain evolution NJO region. syenogranites monzogranites formed at 366–360 Ma are classified as A‐type granites. wide range ε Hf (t) values (−17.62 +8.13) T DM2 ages (789–2,208 Ma) indicate that primary magma was...

Locating hosts with large connection degree is very important for monitoring anomalous network traffics. The in-degree (out-degree), defined as the number of distinct sources (destinations) that a host connected (connects) during given time interval. Due to massive amount data in high speed traffics and limit on processing capability, it difficult accurately locate over links line. In this paper we present new streaming method locating based reversible sketch monitor required memory space...

With the development of personalized services, collaborative filtering techniques have been successfully applied to network recommendation system. But sparse data seriously affect performance algorithms. To alleviate impact sparseness, using user interest information, an improved user-based clustering Collaborative Filtering (CF) algorithm is proposed in this paper, which improves by two ways: similarity calculating method and user-item rating matrix extended. The experimental results show...

Mastering user's behavior character is important for efficient network management and security monitoring. In this paper, we develop a novel framework named as multilevel user cluster mining (MUCM) to measure similarity under different prefix levels. Focusing on aggregated traffic prefixes cannot only reduce the number of flows but also reveal detailed patterns group users sharing similar behaviors. First, employ bidirectional flow bipartite graphs model characteristics in large-scale...

Anomaly detection is an important technique used to identify patterns of unusual network behavior and keep the under control. Today, attacks are increasing in terms both their number sophistication. To avoid causing significant traffic being detected by existing techniques, many new tend involve gradual adjustment behaviors, which always generate incomplete sessions due running mechanisms. Accordingly, this work, we employ symmetry degree profile anomalies further behaviors. We first...

Graph alignment aims to find correspondent nodes between two graphs. Most existing algorithms assume that in different graphs have similar local structures. However, this principle may not apply some real-world application scenarios when densities. Some node pairs very structures these cases. Nevertheless, are expected importance, inspiring us exploit global topology consistency for graph alignment. This paper presents GTCAlign, an unsupervised framework based on consistency. An indicating...