29 research outputs found

    An Integrated Approach for Jammer Detection using Software Defined Radio

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    AbstractDue to shared nature of wireless communication any malicious user can easily monitored communication between two devices and emits false message to block communication. Nowadays increased use of software defined radio (SDR) technology makes any types of jammer device using same hardware with little modification in software. A jammer transmits radio signal to block legitimate communication either overlapping signal with more power or reducing signal to noise ratio. In this paper we have survey different jammer detection methods for efficient detection of jammers presence in system. Existing jammer detection methods like packet delivery ratio (PDR), packet send ratio (PSR), bad packet ratio (BPR) and signal to noise ratio (SNR) can effectively detects jammer, here we have proposed novel method for jammer detection using communication parameter used in SDR like synchronization indicator, iteration and adaptive signal to jammer plus noise ratio (ASNJR). This system uses that parameter which is readily available in system so computation has been reduced and ASNJR also has been adaptively updated with and without presence of jammer. Experimental result show that this system based on SDR effectively detects presence of jammer

    An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks

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    An active jammer could severely degrade the communication quality for wireless networks. Since all wireless nodes openly access the shared media, the harsh effects are exaggerated by retransmission attempts of affected devices. Fast and precise detection of the jammer is of vital importance for heterogeneous wireless environments such as the Internet of things (IoT). It could activate a series of corrective countermeasures to ensure the robust operation of the network. In this paper, we propose a local, straightforward, and numerical metric called the number of jammed slots (NJS), by which we can quickly detect the presence of a jammer and identify the jammed nodes at the software level in broadcast networks. NJS calculation is carried out by a central node which collects the MAC-layer statuses of all wireless nodes in a periodical fashion. Our simulation results indicate that NJS outperforms current detection methods in terms of accuracy and precision

    A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends

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    This paper examines the security vulnerabilities and threats imposed by the inherent open nature of wireless communications and to devise efficient defense mechanisms for improving the wireless network security. We first summarize the security requirements of wireless networks, including their authenticity, confidentiality, integrity and availability issues. Next, a comprehensive overview of security attacks encountered in wireless networks is presented in view of the network protocol architecture, where the potential security threats are discussed at each protocol layer. We also provide a survey of the existing security protocols and algorithms that are adopted in the existing wireless network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term evolution (LTE) systems. Then, we discuss the state-of-the-art in physical-layer security, which is an emerging technique of securing the open communications environment against eavesdropping attacks at the physical layer. We also introduce the family of various jamming attacks and their counter-measures, including the constant jammer, intermittent jammer, reactive jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the integration of physical-layer security into existing authentication and cryptography mechanisms for further securing wireless networks. Finally, some technical challenges which remain unresolved at the time of writing are summarized and the future trends in wireless security are discussed.Comment: 36 pages. Accepted to Appear in Proceedings of the IEEE, 201

    Security techniques for sensor systems and the Internet of Things

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    Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

    Performance analysis of wireless intrusion detection systems

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    Wireless intrusion detection system (WIDS) has become a matter of increasing concern in recent years as a crucial element in wireless network security. WIDS monitors 802.11 traffic to identify the intrusive activities, and then alerts the complementary prevention part to combat the attacks. Selecting a reliable WIDS system necessitates inevitably taking into account a credible evaluation of WIDSs performance. WIDS effectiveness is considered the basic factor in evaluating the WIDS performance, thus it receives great attention in this thesis. Most previous experimental evaluations of intrusion detection systems (IDSs) were concerned with the wired IDSs, with an apparent lack of evaluating the wireless IDSs (WIDSs). In this thesis, we try to manipulate three main critiques of most pervious evaluations; lack of comprehensive evaluation methodology, holistic attack classification, and expressive evaluation metrics. In this thesis, we introduce a comprehensive evaluation methodology that covers all the essential dimensions for a credible evaluation of WIDSs performance. The main pivotal dimensions in our methodology are characterizing and generating the evaluation dataset, defining reliable and expressive evaluation metrics, and overcoming the evaluation limitations. Basically, evaluation dataset consists of two main parts; normal traffic (as a background) and malicious traffic. The background traffic, which comprises normal and benign activities in the absence of attacks, was generated in our experimental evaluation tests as real controlled traffic. The second and important part of the dataset is the malicious traffic which is composed of intrusive activities. Comprehensive and credible evaluation of WIDSs necessitates taking into account all possible attacks. While this is operationally impossible, it is necessary to select representative attack test cases that are extracted mainly from a comprehensive classification of wireless attacks. Dealing with this challenge, we have developed a holistic taxonomy of wireless security attacks from the perspective of the WIDS evaluator. The second pivotal dimension in our methodology is defining reliable evaluation metrics. We introduce a new evaluation metric EID (intrusion detection effectiveness) that manipulates the drawbacks of the previously proposed metrics, especially the common drawback of their main notion that leads to measuring a relative effectiveness. The notion of our developed metric EID helps in measuring the actual effectiveness. We also introduce another metric RR (attack recognition rate) to evaluate the ability of WIDS to recognize the attack type. The third important dimension in our methodology is overcoming the evaluation limitations. The great challenge that we have faced in the experimental evaluation of WIDSs is the uncontrolled traffic over the open wireless medium. This uncontrolled traffic affects the accuracy of the measurements. We overcame this problem by constructing an RF shielded testbed to take all the measurements under our control without any interfering from any adjacent stations. Finally, we followed our methodology and conducted experimental evaluation tests of two popular WIDSs (Kismet and AirSnare), and demonstrated the utility of our proposed solutions

    Analyse de performance des systèmes de détection d’intrusion sans-fil

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    La sécurité des réseaux sans fil fait l’objet d’une attention considérable ces dernières années. Toutefois, les communications sans fil sont confrontées à plusieurs types de menaces et d’attaques. Par conséquent, d’importants efforts, visant à sécuriser davantage les réseaux sans fil, ont dû être fournis pour en vue de lutter contre les attaques sans fil. Seulement, croire qu’une prévention intégrale des attaques peut s’effectuer au niveau de la première ligne de défense d’un système (pare-feux, chiffrement, …) n’est malheureusement qu’illusion. Ainsi, l’accent est de plus en plus porté sur la détection des attaques sans fil au travers d’une seconde ligne de défense, matérialisée par les systèmes de détection d’intrusions sans fil (WIDS). Les WIDS inspectent le trafic sans fil, respectant la norme 802.11, ainsi que les activités du système dans le but de détecter des activités malicieuses. Une alerte est ensuite envoyée aux briques chargées de la prévention pour contrer l’attaque. Sélectionner un WIDS fiable dépend principalement de l’évaluation méticuleuse de ses performances. L’efficacité du WIDS est considérée comme le facteur fondamental lors de l’évaluation de ses performances, nous lui accordons donc un grand intérêt dans ces travaux de thèse. La majeure partie des études expérimentales visant l’évaluation des systèmes de détection d’intrusions (IDS) s’intéressait aux IDS filaires, reflétant ainsi une carence claire en matière d’évaluation des IDS sans fil (WIDS). Au cours de cette thèse, nous avons mis l’accent sur trois principales critiques visant la plupart des précédentes évaluations : le manque de méthodologie d’évaluation globale, de classification d’attaque et de métriques d’évaluation fiables. Au cours de cette thèse, nous sommes parvenus à développer une méthodologie complète d’évaluation couvrant toutes les dimensions nécessaires pour une évaluation crédible des performances des WIDSs. Les axes principaux de notre méthodologie sont la caractérisation et la génération des données d’évaluation, la définition de métriques d’évaluation fiables tout en évitant les limitations de l’évaluation. Fondamentalement, les données d’évaluation sont constituées de deux principales composantes à savoir: un trafic normal et un trafic malveillant. Le trafic normal que nous avons généré au cours de nos tests d’évaluation était un trafic réel que nous contrôlions. La deuxième composante des données, qui se trouve être la plus importante, est le trafic malveillant consistant en des activités intrusives. Une évaluation complète et crédible des WIDSs impose la prise en compte de tous les scénarios et types d’attaques éventuels. Cela étant impossible à réaliser, il est nécessaire de sélectionner certains cas d’attaque représentatifs, principalement extraits d’une classification complète des attaques sans fil. Pour relever ce défi, nous avons développé une taxinomie globale des attaques visant la sécurité des réseaux sans fil, d’un point de vue de l’évaluateur des WIDS. Le deuxième axe de notre méthodologie est la définition de métriques fiables d’évaluation. Nous avons introduit une nouvelle métrique d’évaluation, EID (Efficacité de la détection d’intrusion), visant à pallier les limitations des précédentes métriques proposées. Nous avons démontré l’utilité de la métrique EID par rapport aux autres métriques proposées précédemment et comment elle parvenait à mesurer l’efficacité réelle tandis que les précédentes métriques ne mesuraient qu’une efficacité relative. L’EID peut tout aussi bien être utilisé pour l’évaluation de l’efficacité des IDS filaires et sans fil. Nous avons aussi introduit une autre métrique notée RR (Taux de Reconnaissance), pour mesurer l’attribut de reconnaissance d’attaque. Un important problème se pose lorsque des tests d’évaluation des WIDS sont menés, il s’agit des données de trafics incontrôlés sur le support ouvert de transmission. Ce trafic incontrôlé affecte sérieusement la pertinence des mesures. Pour outrepasser ce problème, nous avons construit un banc d’essai RF blindé, ce qui nous a permis de prendre des mesures nettes sans aucune interférence avec quelconque source de trafic incontrôlé. Pour finir, nous avons appliqué notre méthodologie et effectué des évaluations expérimentales relatives à deux WIDSs populaires (Kismet et AirSnare); nous avons démontré à l’issue de ces évaluations pratiques et l’utilité de nos solutions proposées. ABSTRACT : Wireless intrusion detection system (WIDS) has become a matter of increasing concern in recent years as a crucial element in wireless network security. WIDS monitors 802.11 traffic to identify the intrusive activities, and then alerts the complementary prevention part to combat the attacks. Selecting a reliable WIDS system necessitates inevitably taking into account a credible evaluation of WIDSs performance. WIDS effectiveness is considered the basic factor in evaluating the WIDS performance, thus it receives great attention in this thesis. Most previous experimental evaluations of intrusion detection systems (IDSs) were concerned with the wired IDSs, with an apparent lack of evaluating the wireless IDSs (WIDSs). In this thesis, we try to manipulate three main critiques of most pervious evaluations; lack of comprehensive evaluation methodology, holistic attack classification, and expressive evaluation metrics. In this thesis, we introduce a comprehensive evaluation methodology that covers all the essential dimensions for a credible evaluation of WIDSs performance. The main pivotal dimensions in our methodology are characterizing and generating the evaluation dataset, defining reliable and expressive evaluation metrics, and overcoming the evaluation limitations. Basically, evaluation dataset consists of two main parts; normal traffic (as a background) and malicious traffic. The background traffic, which comprises normal and benign activities in the absence of attacks, was generated in our experimental evaluation tests as real controlled traffic. The second and important part of the dataset is the malicious traffic which is composed of intrusive activities. Comprehensive and credible evaluation of WIDSs necessitates taking into account all possible attacks. While this is operationally impossible, it is necessary to select representative attack test cases that are extracted mainly from a comprehensive classification of wireless attacks. Dealing with this challenge, we have developed a holistic taxonomy of wireless security attacks from the perspective of the WIDS evaluator. The second pivotal dimension in our methodology is defining reliable evaluation metrics. We introduce a new evaluation metric EID (intrusion detection effectiveness) that manipulates the drawbacks of the previously proposed metrics, especially the common drawback of their main notion that leads to measuring a relative effectiveness. The notion of our developed metric EID helps in measuring the actual effectiveness. We also introduce another metric RR (attack recognition rate) to evaluate the ability of WIDS to recognize the attack type. The third important dimension in our methodology is overcoming the evaluation limitations. The great challenge that we have faced in the experimental evaluation of WIDSs is the uncontrolled traffic over the open wireless medium. This uncontrolled traffic affects the accuracy of the measurements. We overcame this problem by constructing an RF shielded testbed to take all the measurements under our control without any interfering from any adjacent stations. Finally, we followed our methodology and conducted experimental evaluation tests of two popular WIDSs (Kismet and AirSnare), and demonstrated the utility of our proposed solutions
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