Biblio

Connected cars have received massive attention in Intelligent Transportation System. Many potential services, especially safety-related ones, rely on spatial-temporal messages periodically broadcast by cars. Without a secure authentication algorithm, malicious cars may send out invalid spatial-temporal messages and then deny creating them. Meanwhile, a lot of private information may be disclosed from these spatial-temporal messages. Since cars move on expressways at high speed, any authentication must be performed in real-time to prevent crashes. In this paper, we propose a Fast and Anonymous Spatial-Temporal Trust (FastTrust) mechanism to ensure these properties. In contrast to most authentication protocols which rely on fixed infrastructures, FastTrust is distributed and mostly designed on symmetric-key cryptography and an entropy-based commitment, and is able to fast authenticate spatial-temporal messages. FastTrust also ensures the anonymity and unlinkability of spatial-temporal messages by developing a pseudonym-varying scheduling scheme on cars. We provide both analytical and simulation evaluations to show that FastTrust achieves the security and privacy properties. FastTrust is low-cost in terms of communication and computational resources, authenticating 20 times faster than existing Elliptic Curve Digital Signature Algorithm.

The growing prevalence of cyber threats in the world are affecting every network user. Numerous security monitoring systems are being employed to protect computer networks and resources from falling victim to cyber-attacks. There is a pressing need to have an efficient security monitoring system to monitor the large network datasets generated in this process. A large network datasets representing Malware attacks have been used in this work to establish an expert system. The characteristics of attacker's IP addresses can be extracted from our integrated datasets to generate statistical data. The cyber security expert provides to the weight of each attribute and forms a scoring system by annotating the log history. We adopted a special semi supervise method to classify cyber security log into attack, unsure and no attack by first breaking the data into 3 cluster using Fuzzy K mean (FKM), then manually label a small data (Analyst Intuition) and finally train the neural network classifier multilayer perceptron (MLP) base on the manually labelled data. By doing so, our results is very encouraging as compare to finding anomaly in a cyber security log, which generally results in creating huge amount of false detection. The method of including Artificial Intelligence (AI) and Analyst Intuition (AI) is also known as AI2. The classification results are encouraging in segregating the types of attacks.

In the open network environment, the strange entities can establish the mutual trust through Automated Trust Negotiation (ATN) that is based on exchanging digital credentials. In traditional ATN, the attribute certificate required to either satisfied or not, and in the strategy, the importance of the certificate is same, it may cause some unnecessary negotiation failure. And in the actual situation, the properties is not just 0 or 1, it is likely to between 0 and 1, so the satisfaction degree is different, and the negotiation strategy need to be quantified. This paper analyzes the fuzzy negotiation process, in order to improve the trust establishment in high efficiency and accuracy further.

Named Data Networking (NDN) is a content-oriented future Internet architecture, which well suits the increasingly mobile and information-intensive applications that dominate today's Internet. NDN relies on in-network caching to facilitate content delivery. This makes it challenging to enforce access control since the content has been cached in the routers and the content producer has lost the control over it. Due to its salient advantages in content delivery, network coding has been introduced into NDN to improve content delivery effectiveness. In this paper, we design ACNC, the first Access Control solution specifically for Network Coding-based NDN. By combining a novel linear AONT (All Or Nothing Transform) and encryption, we can ensure that only the legitimate user who possesses the authorization key can successfully recover the encoding matrix for network coding, and hence can recover the content being transmitted. In addition, our design has two salient merits: 1) the linear AONT well suits the linear nature of network coding; 2) only one vector of the encoding matrix needs to be encrypted/decrypted, which only incurs small computational overhead. Security analysis and experimental evaluation in ndnSIM show that our design can successfully enforce access control on network coding-based NDN with an acceptable overhead.

Attack graph technique is a common tool for the evaluation of network security. However, attack graphs are generally too large and complex to be understood and interpreted by security administrators. This paper proposes an analysis framework for security attack graphs for a given IT infrastructure system. First, in order to facilitate the discovery of interconnectivities among vulnerabilities in a network, multi-host multi-stage vulnerability analysis (MulVAL) is employed to generate an attack graph for a given network topology. Then a novel algorithm is applied to refine the attack graph and generate a simplified graph called a transition graph. Next, a Markov model is used to project the future security posture of the system. Finally, the framework is evaluated by applying it on a typical IT network scenario with specific services, network configurations, and vulnerabilities.

Location-Based Service (LBS) becomes increasingly important for our daily life. However, the localization information in the air is vulnerable to various attacks, which result in serious privacy concerns. To overcome this problem, we formulate a multi-objective optimization problem with considering both the query probability and the practical dummy location region. A low complexity dummy location selection scheme is proposed. We first find several candidate dummy locations with similar query probabilities. Among these selected candidates, a cloaking area based algorithm is then offered to find K - 1 dummy locations to achieve K-anonymity. The intersected area between two dummy locations is also derived to assist to determine the total cloaking area. Security analysis verifies the effectiveness of our scheme against the passive and active adversaries. Compared with other methods, simulation results show that the proposed dummy location scheme can improve the privacy level and enlarge the cloaking area simultaneously.

In this paper, cyber physical system is analyzed from security perspective. A double closed-loop security control structure and algorithm with defense functions is proposed. From this structure, the features of several cyber attacks are considered respectively. By this structure, the models of information disclosure, denial-of-service (DoS) and Man-in-the-Middle Attack (MITM) are proposed. According to each kind attack, different models are obtained and analyzed, then reduce to the unified models. Based on this, system security conditions are obtained, and a defense scenario with detail algorithm is design to illustrate the implementation of this program.

Social media has become an important platform for people to express opinions, share information and communicate with others. Detecting and tracking topics from social media can help people grasp essential information and facilitate many security-related applications. As social media texts are usually short, traditional topic evolution models built based on LDA or HDP often suffer from the data sparsity problem. Recently proposed topic evolution models are more suitable for short texts, but they need to manually specify topic number which is fixed during different time period. To address these issues, in this paper, we propose a nonparametric topic evolution model for social media short texts. We first propose the recurrent semantic dependent Chinese restaurant process (rsdCRP), which is a nonparametric process incorporating word embeddings to capture semantic similarity information. Then we combine rsdCRP with word co-occurrence modeling and build our short-text oriented topic evolution model sdTEM. We carry out experimental studies on Twitter dataset. The results demonstrate the effectiveness of our method to monitor social media topic evolution compared to the baseline methods.

Compared to other remote attestation methods, the binary-based approach is the most direct and complete one, but privacy protection has become an important problem. In this paper, we presented an Extended Hash Algorithm (EHA) for privacy protection based on remote attestation method. Based on the traditional Merkle Hash Tree, EHA altered the algorithm of node connection. The new algorithm could ensure the same result in any measure order. The security key is added when the node connection calculation is performed, which ensures the security of the value calculated by the Merkle node. By the final analysis, we can see that the remote attestation using EHA has better privacy protection and execution performance compared to other methods.

The publish/subscribe paradigm can be used to build IoT service communication infrastructure owing to its loose coupling and scalability. Its features of decoupling among event producers and event consumers make IoT services collaborations more real-time and flexible, and allow indirect, anonymous and multicast IoT service interactions. However, in this environment, the IoT service cannot directly control the access to the events. This paper proposes a cross-layer security solution to address the above issues. The design principle of our security solution is to embed security policies into events as well as allow the network to route events according to publishers' policies and requirements. This solution helps to improve the system's performance, while keeping features of IoT service interactions and minimizing the event visibility at the same time. Experimental results show that our approach is effective.

Exploratory evaluation is an effective way to analyze and improve the security of information system. The information system structure model for security protection capability is set up in view of the exploratory evaluation requirements of security protection capability, and the requirements of agility, traceability and interpretation for exploratory evaluation are obtained by analyzing the relationship between information system, protective equipment and protection policy. Aimed at the exploratory evaluation description problem of security protection capability, the exploratory evaluation problem and exploratory evaluation process are described based on the Granular Computing theory, and a general mathematical description is established. Analysis shows that the standardized description established meets the exploratory evaluation requirements, and it can provide an analysis basis and description specification for exploratory evaluation of information system security protection capability.