Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Mobile Protocol Stack Simulator

Nykypäivän maailma tukeutuu verkkoihin. Tietokoneverkot ja langattomat puhelimet ovat jo varsin tavallisia suurelle joukolle ihmisiä. Uusi verkkotyyppi on ilmestynyt edelleen helpottamaan ihmisten verkottunutta elämää. Ad hoc –verkot mahdollistavat joustavan verkonmuodostuksen langattomien päätelaitteiden välille ilman olemassa olevaa infrastruktuuria. Diplomityö esittelee uuden simulaatiotyökalun langattomien ad hoc –verkkojen simulointiin protokollatasolla. Se esittelee myös kyseisten verkkojen taustalla olevat periaatteet ja teoriat. Lähemmin tutkitaan OSI-mallin linkkikerroksen kaistanjakoprotokollia ad hoc –verkoissa sekä vastaavan toteutusta simulaattorissa. Lisäksi esitellään joukko simulaatioajoja esimerkiksi simulaattorin toiminnasta ja mahdollisista käyttökohteista.

Mobile marketing process of an international event – Case: Falun2015 FIS Nordic World Ski Championships

Any other technology has never affected daily life at this level and witnessed as speedy adaptation as the mobile phone. At the same time, mobile media has developed to be a serious marketing tool for all kinds of businesses, and the industry has grown explosively in recent years. The objective of this thesis is to inspect the mobile marketing process of an international event. This thesis is a qualitative case study. The chosen case for this thesis is the mobile marketing process of Falun2015 FIS Nordic World Ski Championships due to researcher’s interest on the topic and contacts to the people around the event. The empirical findings were acquired by conducting two interviews with three experts from the case organisation and its partner organisation. The interviews were performed as semi-structured interviews utilising the themes arising from the chosen theoretical framework. The framework distinguished six phases in the process: (i) campaign initiation, (ii) campaign design, (iii) campaign creation, (iv) permission management, (v) delivery, and (vi) evaluation and analysis. Phases one and five were not examined in this thesis because campaign initiation was not purely seen as part of the campaign implementation, and investigating phase five would have required a very technical viewpoint to the study. In addition to the interviews, some pre-established documents were exploited as a supporting data. The empirical findings of this thesis mainly follow the theoretical framework utilised. However, some modifications to the model could be made mainly related to the order of different phases. In the revised model, the actions are categorised depending on the time they should be conducted, i.e. before, during or after the event. Regardless of the categorisation, the phases can be in different order and overlapping. In addition, the business network was highly emphasised by the empirical findings and is thus added to the modified model. Five managerial recommendations can be concluded from the empirical findings of this thesis: (i) the importance of a business network should be highly valued in a mobile marketing process; (ii) clear goals should be defined for mobile marketing actions in order to make sure that everyone involved is aware them; (iii) interactivity should be perceived as part of a mobile marketing communication; (iv) enough time should be allowed for the development of a mobile marketing process in order to exploit all the potential it can offer; and (v) attention should be paid to measuring and analysing matters that are of relevance