Related papers: On Identifying Anomalies in Tor Usage with Applica…
Several hundred Tor exit relays together push more than 1 GiB/s of network traffic. However, it is easy for exit relays to snoop and tamper with anonymised network traffic and as all relays are run by independent volunteers, not all of them…
Monitoring network traffic data to detect any hidden patterns of anomalies is a challenging and time-consuming task that requires high computing resources. To this end, an appropriate summarization technique is of great importance, where it…
A very large number of people use Online Social Networks daily. Such platforms thus become attractive targets for agents that seek to gain access to the attention of large audiences, and influence perceptions or opinions. Botnets,…
IThe botnet is considered as a critical issue of the Internet due to its fast growing mechanism and affect. Recently, Botnets have utilized the DNS and query DNS server just like any legitimate hosts. In this case, it is difficult to…
Tor, one of the most popular censorship circumvention systems, faces regular blocking attempts by censors. Thus, to facilitate access, it relies on "pluggable transports" (PTs) that disguise Tor's traffic and make it hard for the adversary…
We present a series of algorithms in tensor networks for anomaly detection in datasets, by using data compression in a Tensor Train representation. These algorithms consist of preserving the structure of normal data in compression and…
We present Montre, a monitoring tool to search patterns specified by timed regular expressions over real-time behaviors. We use timed regular expressions as a compact, natural, and highly-expressive pattern specification language for…
Time-to-Live data in the IP header offers two interesting characteristics: First, different IP stacks pick different start TTL values. Second, each traversed router should decrement the TTL value. The combination of both offers host and…
Detecting anomalies from a series of temporal networks has many applications, including road accidents in transport networks and suspicious events in social networks. While there are many methods for network anomaly detection, statistical…
Approximate variational inference has shown to be a powerful tool for modeling unknown complex probability distributions. Recent advances in the field allow us to learn probabilistic models of sequences that actively exploit spatial and…
Anomaly detection, a critical facet in data analysis, involves identifying patterns that deviate from expected behavior. This research addresses the complexities inherent in anomaly detection, exploring challenges and adapting to…
In this paper we focus on the detection of network anomalies like Denial of Service (DoS) attacks and port scans in a unified manner. While there has been an extensive amount of research in network anomaly detection, current state of the…
Content moderation (removing or limiting the distribution of posts based on their contents) is one tool social networks use to fight problems such as harassment and disinformation. Manually screening all content is usually impractical given…
Dynamic networks, also called network streams, are an important data representation that applies to many real-world domains. Many sets of network data such as e-mail networks, social networks, or internet traffic networks are best…
Deviations from expected behavior during runtime, known as anomalies, have become more common due to the systems' complexity, especially for microservices. Consequently, analyzing runtime monitoring data, such as logs, traces for…
Many real-world scenarios involving streaming information can be represented as temporal graphs, where data flows through dynamic changes in edges over time. Anomaly detection in this context has the objective of identifying unusual…
Network operators and system administrators are increasingly overwhelmed with incessant cyber-security threats ranging from malicious network reconnaissance to attacks such as distributed denial of service and data breaches. A large number…
Deep within the networks of distributed systems, one often finds anomalies that affect their efficiency and performance. These anomalies are difficult to detect because the distributed systems may not have sufficient sensors to monitor the…
Journal Impact Factor is a popular metric for determining the quality of a journal in academia. The number of citations received by a journal is a crucial factor in determining the impact factor, which may be misused in multiple ways.…
The popularity and amazing attractiveness of cryptocurrencies, and especially Bitcoin, absorb countless enthusiasts daily. Although Blockchain technology prevents fraudulent behavior, it cannot detect fraud on its own. There are always…