108,121 research outputs found
Characterizing the Power of Moving Target Defense via Cyber Epidemic Dynamics
Moving Target Defense (MTD) can enhance the resilience of cyber systems
against attacks. Although there have been many MTD techniques, there is no
systematic understanding and {\em quantitative} characterization of the power
of MTD. In this paper, we propose to use a cyber epidemic dynamics approach to
characterize the power of MTD. We define and investigate two complementary
measures that are applicable when the defender aims to deploy MTD to achieve a
certain security goal. One measure emphasizes the maximum portion of time
during which the system can afford to stay in an undesired configuration (or
posture), without considering the cost of deploying MTD. The other measure
emphasizes the minimum cost of deploying MTD, while accommodating that the
system has to stay in an undesired configuration (or posture) for a given
portion of time. Our analytic studies lead to algorithms for optimally
deploying MTD.Comment: 12 pages; 4 figures; Hotsos 14, 201
Tailored Source Code Transformations to Synthesize Computationally Diverse Program Variants
The predictability of program execution provides attackers a rich source of
knowledge who can exploit it to spy or remotely control the program. Moving
target defense addresses this issue by constantly switching between many
diverse variants of a program, which reduces the certainty that an attacker can
have about the program execution. The effectiveness of this approach relies on
the availability of a large number of software variants that exhibit different
executions. However, current approaches rely on the natural diversity provided
by off-the-shelf components, which is very limited. In this paper, we explore
the automatic synthesis of large sets of program variants, called sosies.
Sosies provide the same expected functionality as the original program, while
exhibiting different executions. They are said to be computationally diverse.
This work addresses two objectives: comparing different transformations for
increasing the likelihood of sosie synthesis (densifying the search space for
sosies); demonstrating computation diversity in synthesized sosies. We
synthesized 30184 sosies in total, for 9 large, real-world, open source
applications. For all these programs we identified one type of program analysis
that systematically increases the density of sosies; we measured computation
diversity for sosies of 3 programs and found diversity in method calls or data
in more than 40% of sosies. This is a step towards controlled massive
unpredictability of software
Analysis of Radar Doppler Signature from Human Data
This paper presents the results of time (autocorrelation) and time-frequency (spectrogram) analyses of radar signals returned from the moving human targets. When a radar signal falls on the human target which is moving toward or away from the radar, the signals reflected from different parts of his body produce a Doppler shift that is proportional to the velocity of those parts. Moving parts of the body causes the characteristic Doppler signature. The main contribution comes from the torso which causes the central Doppler frequency of target. The motion of arms and legs induces modulation on the returned radar signal and generates sidebands around the central Doppler frequency, referred to as micro-Doppler signatures. Through analyses on experimental data it was demonstrated that the human motion signature extraction is better using spectrogram. While the central Doppler frequency can be determined using the autocorrelation and the spectrogram, the extraction of the fundamental cadence frequency using the autocorrelation is unreliable when the target is in the clutter presence. It was shown that the fundamental cadence frequency increases with increasing dynamic movement of people and simultaneously the possibility of its extraction is proportional to the degree of synchronization movements of persons in the group
- …