220 research outputs found

    Preventing DDoS using Bloom Filter: A Survey

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    Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending a DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.Comment: 9 pages, 1 figure. This article is accepted for publication in EAI Endorsed Transactions on Scalable Information System

    Reviewing effectivity in security approaches towards strengthening internet architecture

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    The usage of existing Internet architecture is shrouded by various security loopholes and hence is highly ineffective towards resisting potential threats over internet. Hence, it is claimed that future internet architecture has been evolved as a solution to address this security gaps of existing internet architecture. Therefore, this paper initiates its discussion by reviewing the existing practices of web security in conventional internet architecture and has also discussed about some recent solutions towards mitigating potentially reported threats e.g. cross-site scripting, SQL inject, and distributed denial-of-service. The paper has also discussed some of the recent research contribution towards security solution considering future internet architecture. The proposed manuscripts contributes to showcase the true effectiveness of existing approaches with respect to advantages and limitation of existing approaches along with explicit highlights of existing research problems that requires immediate attention

    IoT-MQTT based denial of service attack modelling and detection

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    Internet of Things (IoT) is poised to transform the quality of life and provide new business opportunities with its wide range of applications. However, the bene_ts of this emerging paradigm are coupled with serious cyber security issues. The lack of strong cyber security measures in protecting IoT systems can result in cyber attacks targeting all the layers of IoT architecture which includes the IoT devices, the IoT communication protocols and the services accessing the IoT data. Various IoT malware such as Mirai, BASHLITE and BrickBot show an already rising IoT device based attacks as well as the usage of infected IoT devices to launch other cyber attacks. However, as sustained IoT deployment and functionality are heavily reliant on the use of e_ective data communication protocols, the attacks on other layers of IoT architecture are anticipated to increase. In the IoT landscape, the publish/- subscribe based Message Queuing Telemetry Transport (MQTT) protocol is widely popular. Hence, cyber security threats against the MQTT protocol are projected to rise at par with its increasing use by IoT manufacturers. In particular, the Internet exposed MQTT brokers are vulnerable to protocolbased Application Layer Denial of Service (DoS) attacks, which have been known to cause wide spread service disruptions in legacy systems. In this thesis, we propose Application Layer based DoS attacks that target the authentication and authorisation mechanism of the the MQTT protocol. In addition, we also propose an MQTT protocol attack detection framework based on machine learning. Through extensive experiments, we demonstrate the impact of authentication and authorisation DoS attacks on three opensource MQTT brokers. Based on the proposed DoS attack scenarios, an IoT-MQTT attack dataset was generated to evaluate the e_ectiveness of the proposed framework to detect these malicious attacks. The DoS attack evaluation results obtained indicate that such attacks can overwhelm the MQTT brokers resources even when legitimate access to it was denied and resources were restricted. The evaluations also indicate that the proposed DoS attack scenarios can signi_cantly increase the MQTT message delay, especially in QoS2 messages causing heavy tail latencies. In addition, the proposed MQTT features showed high attack detection accuracy compared to simply using TCP based features to detect MQTT based attacks. It was also observed that the protocol _eld size and length based features drastically reduced the false positive rates and hence, are suitable for detecting IoT based attacks

    Trends on Computer Security: Cryptography, User Authentication, Denial of Service and Intrusion Detection

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    The new generation of security threats has beenpromoted by digital currencies and real-time applications, whereall users develop new ways to communicate on the Internet.Security has evolved in the need of privacy and anonymity forall users and his portable devices. New technologies in everyfield prove that users need security features integrated into theircommunication applications, parallel systems for mobile devices,internet, and identity management. This review presents the keyconcepts of the main areas in computer security and how it hasevolved in the last years. This work focuses on cryptography,user authentication, denial of service attacks, intrusion detectionand firewalls

    Software security requirements management as an emerging cloud computing service

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    © 2016 Elsevier Ltd. All rights reserved.Emerging cloud applications are growing rapidly and the need for identifying and managing service requirements is also highly important and critical at present. Software Engineering and Information Systems has established techniques, methods and technology over two decades to help achieve cloud service requirements, design, development, and testing. However, due to the lack of understanding of software security vulnerabilities that should have been identified and managed during the requirements engineering phase, we have not been so successful in applying software engineering, information management, and requirements management principles that have been established for the past at least 25 years, when developing secure software systems. Therefore, software security cannot just be added after a system has been built and delivered to customers as seen in today's software applications. This paper provides concise methods, techniques, and best practice requirements engineering and management as an emerging cloud service (SSREMaaES) and also provides guidelines on software security as a service. This paper also discusses an Integrated-Secure SDLC model (IS-SDLC), which will benefit practitioners, researchers, learners, and educators. This paper illustrates our approach for a large cloud system Amazon EC2 service

    Denial of service attack detection through machine learning for the IoT

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    Sustained Internet of Things (IoT) deployment and functioning are heavily reliant on the use of effective data communication protocols. In the IoT landscape, the publish/subscribe-based Message Queuing Telemetry Transport (MQTT) protocol is popular. Cyber security threats against the MQTT protocol are anticipated to increase at par with its increasing use by IoT manufacturers. In particular, IoT is vulnerable to protocol-based Application layer Denial of Service (DoS) attacks, which have been known to cause widespread service disruption in legacy systems. In this paper, we propose an Application layer DoS attack detection framework for the MQTT protocol and test the scheme on legitimate and protocol compliant DoS attack scenarios. To protect the MQTT message brokers from such attacks, we propose a machine learning-based detection framework developed for the MQTT protocol. Through experiments, we demonstrate the impact of such attacks on various MQTT brokers and evaluate the effectiveness of the proposed framework to detect these malicious attacks. The results obtained indicate that the attackers can overwhelm the server resources even when legitimate access was denied to MQTT brokers and resources have been restricted. In addition, the MQTT features we have identified showed high attack detection accuracy. The field size and length-based features drastically reduced the false-positive rates and are suitable in detecting IoT based attacks

    WARDOG: Awareness detection watchbog for Botnet infection on the host device

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    Botnets constitute nowadays one of the most dangerous security threats worldwide. High volumes of infected machines are controlled by a malicious entity and perform coordinated cyber-attacks. The problem will become even worse in the era of the Internet of Things (IoT) as the number of insecure devices is going to be exponentially increased. This paper presents WARDOG – an awareness and digital forensic system that informs the end-user of the botnet’s infection, exposes the botnet infrastructure, and captures verifiable data that can be utilized in a court of law. The responsible authority gathers all information and automatically generates a unitary documentation for the case. The document contains undisputed forensic information, tracking all involved parties and their role in the attack. The deployed security mechanisms and the overall administration setting ensures non-repudiation of performed actions and enforces accountability. The provided properties are verified through theoretic analysis. In simulated environment, the effectiveness of the proposed solution, in mitigating the botnet operations, is also tested against real attack strategies that have been captured by the FORTHcert honeypots, overcoming state-of-the-art solutions. Moreover, a preliminary version is implemented in real computers and IoT devices, highlighting the low computational/communicational overheads of WARDOG in the field

    New Approaches to Mitigation of Malicious Traffic in VoIP Networks

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    Voice over IP (VoIP) telephony is becoming widespread in use, and is often integrated into computer networks. Because of this, malicious software threatens VoIP systems in the same way that traditional computer systems have been attacked by viruses, worms, and other automated agents. VoIP networks are a challenge to secure against such malware as much of the network intelligence is focused on the edge devices and access environment. This paper describes the design and implementation of a novel VoIP security architecture in which evaluation of, and mitigation against, malicious traffic is demonstrated by the use of virtual machines to emulate vulnerable clients and servers through the use of apparent attack vectors. This new architecture, which is part of an ongoing research project, establishes interaction between the VoIP backend and the end users, thus providing information about ongoing and unknown attacks to users
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