Social violence presents a compelling challenge to public safety, yet existing multimodal detection systems exhibit excessive reliance on RGB image semantics and opaque decision-making processes. Despite leveraging visual and auditory data, current models demonstrate RGB bias in feature prioritization, as evidenced by explainability analyzes, thereby limiting their generalization for behavioral understanding. Additionally, modality inconsistency and inefficient fusion mechanisms impair model transparency and training stability. To bridge these gaps, this study proposes modality-aligned preprocessing (VAJ) that structurally unifies visual-auditory features through conflict resolution and input optimization, explicitly suppressing color dominance while enhancing interpretable feature representations. Complementing this, we design DTVDS, an interpretable detection framework integrating knowledge distillation to transfer distilled behavioral insights from a cumbersome teacher network to an efficient student model. This dual strategy not only addresses computational overhead but also clarifies decision logic through simplified inference pathways. Evaluations on XD-Violence and UCF-Crime benchmarks demonstrate superior performance, with AP (89.64%) and AUC (88.35%) outperforming existing methods. Qualitative evaluations further validate interpretability, revealing modality-coherent attention maps and human-aligned rationale visualization. The proposed method advances violence detection by addressing persistent shortcomings in multimodal alignment and model explainability.

This paper deals with the problem of collaboratively secure document editing in cloud environment. Using cloud document editing service, several users can create and edit a document collaboratively. However, as the cloud service provider is not trusted to guarantee the confidentiality of these documents, existing methods encrypt the documents before uploading them to the cloud. While these approaches can be inefficient for collaborative editing, we propose to organize the content of a document using a Red-Black tree and encrypt each block of data separately, so as to improve the performance of collaborative editing systems. Although creating and maintaining the Red-Black tree introduces extra cost, compared to the whole document encryption strategy the experimental results show that for text editing operations, such as insertion and removal, the use of Red-Black tree algorithm improves efficiency by 31.04% if 3DES encryption is applied and by 23.94% if applying AES encryption.

A network intrusion detection system (NIDS) based on genetic-fuzzy association rules is presented in the paper, which mines rules in an incremental manner in order to meet the real-time requirement of a NIDS. More precisely, the proposed NIDS adopts the incremental mining of fuzzy association rules from network traffic, in which membership functions of fuzzy variables are optimized by a genetic algorithm. The proposed online system belongs to anomaly detection, not misuse detection. Some denial-of-service (DoS) attacks were experimented in this study to show the performance of the proposed NIDS. The results show that the proposed NIDS can detect DoS attacks in both effectiveness and efficiency.

Abstract Traditionally, a sniffing attack is classified as a passive attack, as it follows all regular protocols without generating any forged messages, simply silently sniffing packets and retrieving valuable information. In mobile ad hoc networks (MANETs), some malicious applications can only work when the resided node is in sniffing mode, and performs the same routing protocol as other normal nodes. This paper proposes a modified Ad hoc On‐demand Distance Vector (AODV) routing protocol for the detection and isolation of sniffing nodes in MANETs, so as to prevent such sniffing‐based malicious applications. With the proposed protocol, sniffing nodes in MANETs can be found and isolated by their neighboring nodes, ensuring the failure of follow‐up attacks. In this study, the NS‐2 simulation tool was used to evaluate the designed routing protocol. The results showed that the proposed protocol could effectively detect and isolate sniffing nodes, and would not cause significant network overhead. Copyright © 2010 John Wiley & Sons, Ltd.

In this paper, IDS (Intrusion Detection System) nodes are deployed in MANETs in order to mitigate black hole attacks. The IDS nodes must be set in sniff mode in order to perform the so-called ABM (Anti-Blackhole Mechanism) function, which is mainly used to estimate a suspicious value of a node according to the abnormal difference between the routing messages transmitted from the node. When a suspicious value exceeds a threshold, an IDS nearby will broadcast a block message, informing all nodes on the network, asking them to cooperatively isolate the malicious node.

This paper presents an online real-time network response system, which can determine whether a LAN is suffering from a flooding attack within a very short time unit. The detection engine of the system is based on the incremental mining of fuzzy association rules from network packets, in which membership functions of fuzzy variables are optimized by a genetic algorithm. The proposed online system belongs to anomaly detection, not misuse detection. Moreover, a mechanism for dynamic firewall updating is embedded in the proposed system for the function of eliminating suspicious connections when necessary.

The fuzzy association rule has been proven to be effective to present users’ network behavior offline from a huge amount of collected packets. However, not only effectiveness, efficiency is important as well for Network Intrusion Detection Systems (NIDSs). None of those proposed NIDSs subject to fuzzy association rule can meet the real-time requirement because they all applied static mining approach. In the paper, we propose a real-time NIDS by incremental mining for fuzzy association rules. By consistently comparing the two rule sets, one mined from online packets and the other mined from training attack free packets, our system can make a decision per time unit, 2 seconds in the paper. Experiments have been done to demonstrate its excellent effectiveness and efficiency of the system.

The problem of spyware is incredibly serious and exceeds anyone's imagination. Combining static and dynamic analyses, we propose an integrated architecture to defend against surveillance spyware in this paper. Features extracted from both static and dynamic analyses are ranked according to their information gains. Then using top significant features we construct a Support Vector Machine (SVM) classifier for each client. In order to keep the classifier update-to-date, there is a machine playing as server to collect reports from all clients, retrain, and redistribute the new classifier to each client. Our surveillance spyware detection system (SSDS) has an overall accuracy rate up to 97.9% for known surveillance spywares and 96.4% for unknown ones.

Two main goals of our e-mail client system are filtering out junk e-mails and blocking e-mail sent out by malicious code. The famous Ling-Spam Corpus was experimented to show the good performance of our system. Moreover, our system can prevent malicious code impersonating SMTP to send out infected e-mail or secrecy of the computer system.

A recursive network can be constructed with basic building blocks in a recursive manner. For example the hypercube is a recursive network because an n-dimensional hypercube consists of two (n-1)-dimensional hypercubes. A recursive network is said to be with complete connection if the subnetwork that constitute it are connected as a complete graph. A general broadcasting scheme is proposed for recursive networks with complete connection. The scheme is simple, efficient, and easy to be implemented. Moreover, no redundant message will be generated. Four networks: WK-recursive networks, hypercomplete networks, hypernet networks, and star networks, are taken as examples to show the effectiveness of the scheme.

Recently, WK-recursive networks have received much attention due to their many favorable properties. However, they suffered from a rigorous restriction on their sizes. Incomplete WK-recursive networks were proposed to relieve this restriction. In this paper, the topological properties of incomplete WK-recursive networks are investigated. It is shown that they contain Hamiltonian cycles if their connectivities are greater than one. A sufficient and necessary condition is also proposed for those with connectivity one to contain a Hamiltonian path. A linear-time algorithm using the prune-and-search technique is presented to compute their diameters. © 1998 John Wiley & Sons, Inc. Networks 32: 23–45, 1998

The WK-recursive networks own two structural advantages: expansibility and equal degree. A network is expansible if no changes to node configuration and link connection are necessary when it is expanded, and of equal degree if its nodes have the same degree no matter what the size is. However, the number of nodes contained in a WK-recursive network is restricted to d/sup t/, where d>1 is the size of the basic building block and t/spl ges/1 is the level of expansion. The incomplete WK-recursive networks, which were proposed to relieve this restriction, are allowed to contain an arbitrary number of basic building blocks, while presenting the advantages of the WK-recursive networks. Designing shortest-path routing algorithms for incomplete networks is in general more difficult than for complete networks. The reason is that most incomplete networks lack a unified representation. One of the contributions of this paper is to demonstrate a useful representation, i.e., the multistage graph representation, for the incomplete WK-recursive networks. On the basis of it, a shortest-path routing algorithm is then proposed. With O(d/spl middot/t) time preprocessing, this algorithm takes O(t) time for each intermediate node to determine the next node along the shortest path.

The WK-recursive networks, which were originally proposed by Vecchia and Sanges, have suffered from the rigorous restriction on the number of nodes. Like the other incomplete networks, the incomplete WK-recursive networks have been proposed to relieve this restriction. In this paper, it is first shown that the structures of the incomplete WK-recursive networks are conveniently represented with multistage graphs. This representation can provide a uniform look at the incomplete WK-recursive networks. With its help, a linear-time algorithm using the prune-and-search technique is presented for computing the diameters of the incomplete WK-recursive networks.