Biblio
Failure to detect malware at its very inception leaves room for it to post significant threat and cost to cyber security for not only individuals, organizations but also the society and nation. However, the rapid growth in volume and diversity of malware renders conventional detection techniques that utilize feature extraction and comparison insufficient, making it very difficult for well-trained network administrators to identify malware, not to mention regular users of internet. Challenges in malware detection is exacerbated since complexity in the type and structure also increase dramatically in these years to include source code, binary file, shell script, Perl script, instructions, settings and others. Such increased complexity offers a premium on misjudgment. In order to increase malware detection efficiency and accuracy under large volume and multiple types of malware, this research adopts Convolutional Neural Networks (CNN), one of the most successful deep learning techniques. The experiment shows an accuracy rate of over 90% in identifying malicious and benign codes. The experiment also presents that CNN is effective with detecting source code and binary code, it can further identify malware that is embedded into benign code, leaving malware no place to hide. This research proposes a feasible solution for network administrators to efficiently identify malware at the very inception in the severe network environment nowadays, so that information technology personnel can take protective actions in a timely manner and make preparations for potential follow-up cyber-attacks.
We consider transmissions of secure messages over a burst erasure wiretap channel under decoding delay constraint. For block codes we introduce and study delay optimal secure burst erasure correcting (DO-SBE) codes that provide perfect security and recover a burst of erasures of a limited length with minimum possible delay. Our explicit constructions of DO-SBE block codes achieve maximum secrecy rate. We also consider a model of a burst erasure wiretap channel for the streaming setup, where in any sliding window of a given size, in a stream of encoded source packets, the eavesdropper is able to observe packets in an interval of a given size. For that model we obtain an information theoretic upper bound on the secrecy rate for delay optimal streaming codes. We show that our block codes can be used for construction of delay optimal burst erasure correcting streaming codes which provide perfect security and meet the upper bound for a certain class of code parameters.
Cyber security is a vital performance metric for networks. Wiretap attacks belong to passive attacks. It commonly exists in wired or wireless networks, where an eavesdropper steals useful information by wiretapping messages being shipped on network links. It seriously damages the confidentiality of communications. This paper proposed a secure network coding system architecture against wiretap attacks. It combines and collaborates network coding with cryptography technology. Some illustrating examples are given to show how to build such a system and prove its defense is much stronger than a system with a single defender, either network coding or cryptography. Moreover, the system is characterized by flexibility, simplicity, and easy to set up. Finally, it could be used for both deterministic and random network coding system.
With the rapid development of the contemporary society, wide use of smart phone and vehicle sensing devices brings a huge influence on the extensive data collection. Network coding can only provide weak security privacy protection. Aiming at weak secure feature of network coding, this paper proposes an information transfer mechanism, Weak Security Network Coding with Homomorphic Encryption (HE-WSNC), and it is integrated into routing policy. In this mechanism, a movement model is designed, which allows information transmission process under Wi-Fi and Bluetooth environment rather than consuming 4G data flow. Not only does this application reduce the cost, but also improve reliability of data transmission. Moreover, it attracts more users to participate.
Nowadays, a major challenge to network security is malicious codes. However, manual extraction of features is one of the characteristics of traditional detection techniques, which is inefficient. On the other hand, the features of the content and behavior of the malicious codes are easy to change, resulting in more inefficiency of the traditional techniques. In this paper, a K-Means Clustering Analysis is proposed based on Adaptive Weights (AW-MMKM). Identifying malicious codes in the proposed method is based on four types of network behavior that can be extracted from network traffic, including active, fault, network scanning, and page behaviors. The experimental results indicate that the AW-MMKM can detect malicious codes efficiently with higher accuracy.
This paper introduces complex network into software clone detection and proposes a clone code detection method based on software complex network feature matching. This method has the following properties. It builds a software network model with many added features and codes written with different languages can be detected by a single method. It reduces the space of code comparison, and it searches similar subnetworks to detect clones without knowing any clone codes information. This method can be used in detecting open source code which has been reused in software for security analysis.
For secure and high-quality wireless transmission, we propose a chaos multiple-input multiple-output (C-MIMO) transmission scheme, in which physical layer security and a channel coding effect with a coding rate of 1 are obtained by chaotic MIMO block modulation. In previous studies, we introduced a log-likelihood ratio (LLR) to C-MIMO to exploit LLR-based outer channel coding and turbo decoding, and obtained further coding gain. However, we only studied the concatenation of turbo code, low-density parity check (LDPC) code, and convolutional code which were relatively high-complexity or weak codes; thus, outer code having further low-complexity and strong error correction ability were expected. In particular, a transmission system with short and good code is required for control signaling, such as in 5G networks. Therefore, in this paper, we propose a polar code concatenation to C-MIMO, and introduce soft successive decoding (SCAD) and soft successive cancellation list decoding (SSCLD) as LLR-based turbo decoding for polar code. We numerically evaluate the bit error rate performance of the proposed scheme, and compare it to the conventional LDPC-concatenated transmission.
Named Data Networking (NDN) intrinsically supports in-network caching and multipath forwarding. The two salient features offer the potential to simultaneously transmit content segments that comprise the requested content from original content publishers and in-network caches. However, due to the complexity of maintaining the reachability information of off-path cached content at the fine-grained packet level of granularity, the multipath forwarding and off-path cached copies are significantly underutilized in NDN so far. Network coding enabled NDN, referred to as NC-NDN, was proposed to effectively utilize multiple on-path routes to transmit content, but off-path cached copies are still unexploited. This work enhances NC-NDN with an On-demand Off-path Cache Exploration based Multipath Forwarding strategy, dubbed as O2CEMF, to take full advantage of the multipath forwarding to efficiently utilize off-path cached content. In O2CEMF, each network node reactively explores the reachability information of nearby off-path cached content when consumers begin to request a generation of content, and maintains the reachability at the coarse-grained generation level of granularity instead. Then the consumers simultaneously retrieve content from the original content publisher(s) and the explored capable off-path caches. Our experimental studies validate that this strategy improves the content delivery performance efficiently as compared to that in the present NC-NDN.
The network coding optimization based on niche genetic algorithm can observably reduce the network overhead of encoding technology, however, security issues haven't been considered in the coding operation. In order to solve this problem, we propose a network coding optimization scheme for niche algorithm based on security performance (SNGA). It is on the basis of multi-target niche genetic algorithm(NGA)to construct a fitness function which with k-secure network coding mechanism, and to ensure the realization of information security and achieve the maximum transmission of the network. The simulation results show that SNGA can effectively improve the security of network coding, and ensure the running time and convergence speed of the optimal solution.
Network security and data confidentiality of transmitted information are among the non-functional requirements of industrial wireless sensor networks (IWSNs) in addition to latency, reliability and energy efficiency requirements. Physical layer security techniques are promising solutions to assist cryptographic methods in the presence of an eavesdropper in IWSN setups. In this paper, we propose a physical layer security scheme, which is based on both insertion of an random error vector to forward error correction (FEC) codewords and transmission over decentralized relay nodes. Reed-Solomon and Golay codes are selected as FEC coding schemes and the security performance of the proposed model is evaluated with the aid of decoding error probability of an eavesdropper. The results show that security level is highly based on the location of the eavesdropper and secure communication can be achieved when some of channels between eavesdropper and relay nodes are significantly noisier.
Traditional network routing protocol exhibits high statics and singleness, which provide significant advantages for the attacker. There are two kinds of attacks on the network: active attacks and passive attacks. Existing solutions for those attacks are based on replication or detection, which can deal with active attacks; but are helpless to passive attacks. In this paper, we adopt the theory of network coding to fragment the data in the Software-Defined Networks and propose a network coding-based resilient multipath routing scheme. First, we present a new metric named expected eavesdropping ratio to measure the resilience in the presence of passive attacks. Then, we formulate the network coding-based resilient multipath routing problem as an integer-programming optimization problem by using expected eavesdropping ratio. Since the problem is NP-hard, we design a Simulated Annealing-based algorithm to efficiently solve the problem. The simulation results demonstrate that the proposed algorithms improve the defense performance against passive attacks by about 20% when compared with baseline algorithms.
Routing protocols in wireless sensor network are vulnerable to various malicious security attacks that can degrade network performance and lifetime. This becomes more important in cluster routing protocols that is composed of multiple node and cluster head, such as low energy adaptive clustering hierarchy (LEACH) protocol. Namely, if an attack succeeds in failing the cluster head, then the entire set of nodes fail. Therefore, it is necessary to develop robust recovery schemes to overcome security attacks and recover packets at short times. Hence this paper proposes a detection and recovery scheme for selective forwarding attacks in wireless sensor networks using LEACH protocol. The proposed solution features near-instantaneous recovery times, without the requirement for feedback or retransmissions once an attack occurs.
Network coding has been proposed to be built into Named Data Networking (NDN) for achieving efficient simultaneous content delivery. Network coding allows intermediate nodes to perform arbitrary coding operations on Data packets. One salient feature of NDN is its content-based security by protecting each Data packet with a signature signed by its publisher. However, in the network coding-based NDN, it remains unclear how to securely and efficiently sign a recoded Data packet at an intermediate router. This work proposes a mechanism to enable linearly homomorphic signatures in network coding-based NDN so as to directly generate a signature for a recoded Data packet by combining the signatures of those Data packets on which the recoding operation is performed.