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We introduce a methodology for efficient monitoring of processes running on hosts in a corporate network. The methodology is based on collecting streams of system calls produced by all or selected processes on the hosts, and sending them over the network to a monitoring server, where machine learning algorithms are used to identify changes in process behavior due to malicious activity, hardware failures,...
Remote access Trojans (RATs) are used by attackers to compromise and control the victim machine. In this work, a novel Network-based framework is introduced for detecting RAT bots based on data mining techniques. Several machine learning (ML) techniques are used to differentiate between benign and RAT infected machines. Various performance measurements are used to evaluate the performance of the proposed...
Lateral movement-based attacks are increasingly leading to compromises in large private and government networks, often resulting in information exfiltration or service disruption. Such attacks are often slow and stealthy and usually evade existing security products. To enable effective detection of such attacks, we present a new approach based on graph-based modeling of the security state of the target...
Cyber threats push the researchers towards developing detection frameworks for protecting Internet users. Remote administration tool (RAT) is one of the serious cyber tools used by the attackers to fully control the targeted victim machine. In this paper a host based detection framework is introduced for RAT detection. The proposed framework depends on fully analysis of the system behavior of the...
Detecting RAT (Remote Access Trojan or Remote Administration Tool) used in APT (Advanced Persistent Threat) attacks is a challenging task. Many previous methods to detect RATs on the network require monitoring all network traffic. However, it is difficult to keep all network traffic because the size is too huge. Actually, we would have to detect RAT activity through insufficient information such as...
In the continual battle between malware attacks and antivirus technologies, both sides strive to deploy their techniques at always lower layers in the software system stack. The goal is to monitor and control the software executing in the levels above their own deployment, to detect attacks or to defeat defenses. Recent antivirus solutions have gone even below the software, by enlisting hardware support...
Physical activity monitoring represents an important tool in supporting/encouraging vulnerable persons in their struggle to recover from surgery or long term illness promoting a healthy lifestyle. The paper proposes a smart, low power activity monitoring platform capable to acquire data from 4 inertial sensor modules placed on human body, temporarily store it on a mobile phone for real time data display...
The maintenance and management for the current Fourth Generation (4G) networks are still in a manual and semi-automatic manner, which are costly and time-consuming. This imposes a great challenge on the network management of heterogeneous, software-defined and virtualized Fifth Generation (5G) systems. With the advent of network intelligence, a possibility on intelligent management is opened for the...
According to a recent study, 30% of VMs in private cloud data centers are "comatose", in part because there is generally no strong incentive for their human owners to delete them at an appropriate time. These inactive VMs are still scheduled and executed on physical cloud resources, taking valuable access away from productive VMs. In an extreme, cloud infrastructure may deny legitimate requests...
The alarming statistics of Diabetes Mellitus (DM) Type 2 as the most common and prevalent disease in India and world over [1] has fuelled research in the direction of non-invasive and continuous monitoring of this disease. This paper describes a demonstration of an inexpensive mobile-phone based android application which can collect Photoplethysmogram (PPG) from fingertip via built-in camera and flash...
Wireless EEG monitoring systems have been successfully used for seizure detection outside clinical settings. The wireless EEG sensor nodes consume a considerable amount of battery energy to acquire, encode and transmit the data to the server side. In this paper, we introduce energy-efficient monitoring systems to increase the sensors' battery lifetime. Specifically, we propose a feature extraction...
Distributed Denial-of-Service (DDoS) attacks continue to constitute a pernicious threat to the delivery of services within the Internet domain. These attacks harness the power of thousands, and sometimes tens or hundreds of thousands of compromised computers to attack web-services and online trading sites, resulting in significant down-time and financial loss. The problem of detecting DDoS attacks...
One of the most serious cyber-security threats is the botnet. The botnet runs in the background of the compromised machine and maintains the communication with the C&C server to receive malicious commands. Botnet master uses botnet to launch dangerous attacks. %such as Distributed Denial of Service (DDoS), data stealing and spamming. This paper addresses the problem of detecting P2P botnet flow...
With the security situation in Cyberspace constantly becoming worse, Cyber threat detection has attracted a lot of researching attentions. In this paper, existing detection technologies are firstly reviewed. Secondly, a framework of capturing the abnormal traffic of botnets is proposed. Major modules and key detection techniques are presented at the same time. The hidden threat detection in physically...
Data centers are extremely important facilities that contain core business information and applications, but the energy consumption is an inevitable issue, so the thermal distribution monitoring is critical for data centers reliable and stable operation. Thermal information enables monitoring and autonomic thermal management in large data centers. Recent approaches that employed a mobile robot or...
The continued growth of the Internet has resulted in the increasing sophistication of toolkit and methods to conduct computer attacks and intrusions that are easy to use and publicly available to download, such as Zeus botnet toolkit. Botnets are responsible for many cyber-attacks, such as spam, distributed denial-of-service (DDoS), identity theft, and phishing. Most of existence botnet toolkits release...
In this paper, we propose a novel approach to detect a targeted attack by visualizing the paths of lateral movement in which the attacker compromises several hosts in the targeted network step by step to achieve his final goal. To this end, we first identify a pair of hosts that has a relationship in which a host can have compromised the other host based on the suspiciousness of their activities and...
In order to achieve object trajectory tracking without blind angle, we propose a pedestrian movement monitoring system with face recognition outdoor and RFID radio frequency equipment indoor, which connect people, object and events. While granting integrated human movement information, we also provide two-dimensional trajectory panoramic map browsing, preview video clips on designated area, video...
This paper presents the architecture of an extended area monitoring system based on crowdsourcing and mobile devices. In particular areas (as very large historical sites) it can be difficult or impossible to install fixed cameras due to the huge number of candidate points of interest (POI) to monitoring or to the significant impact on site (i.e. cameras or other sensors could be too invasive towards...
In recent years, IT Service Providers have been rapidly transforming to an automated service delivery model. This is due to advances in technology and driven by the unrelenting market pressure to reduce cost and maintain quality. Tremendous progress has been made to date towards attainment of truly automated service delivery; that is, the ability to deliver the same service automatically using the...
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