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The DNS (Domain Name System) protocol has been in use since the early days of the Internet. Although DNS as a de facto networking protocol had no security considerations in its early years, there have been many security enhancements, such…
Application of deep learning to enhance the accuracy of intrusion detection in modern computer networks were studied in this paper. The identification of attacks in computer networks is divided in to two categories of intrusion detection…
Recommender systems play a crucial role in helping users to find their interested information in various web services such as Amazon, YouTube, and Google News. Various recommender systems, ranging from neighborhood-based,…
Focus on Deep Neural Network based malicious and normal computer Network Traffic classification. (such as attacks, phishing, any other illegal activity and normal traffic identification). In this paper, the main idea is to review, existed…
The popularity of Software Defined Networks (SDNs) has grown in recent years, mainly because of their ability to simplify network management and improve network flexibility. However, this also makes them vulnerable to various types of cyber…
Confidential services running in hardware-protected Trusted Execution Environments (TEEs) can provide higher security assurance, but this requires custom clients and protocols to distribute, update, and verify their attestation evidence.…
Due to significant improvements in performance in recent years, neural networks are currently used for an ever-increasing number of applications. However, neural networks have the drawback that their decisions are not readily interpretable…
Deep neural networks (DNNs) are vulnerable to backdoor attacks which can hide backdoor triggers in DNNs by poisoning training data. A backdoored model behaves normally on clean test images, yet consistently predicts a particular target…
The success of DNNs has driven the extensive applications of person re-identification (ReID) into a new era. However, whether ReID inherits the vulnerability of DNNs remains unexplored. To examine the robustness of ReID systems is rather…
Deep neural networks are susceptible to poisoning attacks by purposely polluted training data with specific triggers. As existing episodes mainly focused on attack success rate with patch-based samples, defense algorithms can easily detect…
We address the problem of securing distributed storage systems against eavesdropping and adversarial attacks. An important aspect of these systems is node failures over time, necessitating, thus, a repair mechanism in order to maintain a…
Clean-label poisoning attacks inject innocuous looking (and "correctly" labeled) poison images into training data, causing a model to misclassify a targeted image after being trained on this data. We consider transferable poisoning attacks…
The Domain Name System (DNS) serves as the backbone of the Internet, primarily translating domain names to IP addresses. Over time, various enhancements have been introduced to strengthen the integrity of DNS. Among these, DNSSEC stands out…
The domain name system (DNS) is a crucial backbone of the Internet and millions of new domains are created on a daily basis. While the vast majority of these domains are legitimate, adversaries also register new hostnames to carry out…
Since security was not among the original design goals of the Domain Name System (herein called Vanilla DNS), many secure DNS schemes have been proposed to enhance the security and privacy of the DNS resolution process. Some proposed…
Modern web applications are dominated by HTTP/HTTPS messages that consist of one or more headers, where most of the exploits and payloads can be injected by attackers. According to the OWASP, the 80 percent of the web attacks are done…
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks have emerged as a popular means of causing collection particular overhaul disruptions, often for total periods of instance. The relative ease and low costs of…
We introduce a novel concept, called Name Confusion, and demonstrate how it can be employed to thwart multiple classes of code-reuse attacks. By building upon Name Confusion, we derive Phantom Name System (PNS): a security protocol that…
DNS is one of the cornerstones of the Internet. Nowadays, a substantial fraction of DNS queries are handled by public resolvers (e.g., Google Public DNS and Cisco's OpenDNS) rather than ISP nameservers. This behavior makes it difficult for…
Providing explanations for deep neural network (DNN) models is crucial for their use in security-sensitive domains. A plethora of interpretation models have been proposed to help users understand the inner workings of DNNs: how does a DNN…